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The Health Status of Soon-To-Be-Released Inmates Vol 2, NCCHC, 2002

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A Report to Congress
Volume 2

The Health Status of
Soon-To-Be-Released
Inmates

Volume 2

April 2002

iii

Preface
Through the mid-1990s, a number of studies,
limited in scope, found a higher prevalence of
certain infectious diseases, chronic diseases, and
mental illness among prison and jail inmates.
Further, each year the Nation’s prisons and jails
release more than 11.5 million inmates. The
potential that ex-offenders may be contributing to
the spread of infectious disease in the community
became of increasing concern. In addition, as
these ex-offenders’ diseases get worse, society
may have to pay substantially more to treat them
than if these conditions had been treated at an
earlier stage—or prevented altogether—while
these individuals were still incarcerated.
In 1997 Congress instructed the U.S. Department
of Justice to determine whether these concerns
were well founded and, if so, to recommend
solutions. The National Institute of Justice (NIJ),
the research arm of the Department of Justice,
entered into a cooperative agreement with the
National Commission on Correctional Health
Care (NCCHC) to study the problem. The Health
Status of Soon-To-Be-Released Inmates report is
the result of that research.
The NCCHC commissioned a series of papers
(summarized in volume 1 of this report and
provided in full in volume 2) that documents
indisputably that tens of thousands of inmates are
being released into the community every year
with undiagnosed or untreated communicable
disease, chronic disease, and mental illness.
Another set of commissioned papers clearly
shows that it not only would be cost effective to
treat several of these diseases, but in several
instances, it would even save money in the long
run.

The report concludes with policy recommendations designed to improve disease prevention,
screening, and treatment programs in prisons and
jails. The recommendations have been carefully
crafted. First, they are based on a consensus
among a number of the Nation’s leading experts
in correctional health care and public health.
Second, they propose interventions for which
there is strong, and in many cases overwhelming,
scientific evidence of therapeutic effectiveness.
Third, they reflect a realistic consideration of
what correctional systems can reasonably be
expected to accomplish.
There are serious political, logistical, and
financial barriers to improving health services in
prisons and jails. As documented in this report,
however, a number of jurisdictions have found
ways to overcome some of these barriers, often
through collaborations with public health
departments and national or community-based
organizations.
Prisons and jails offer a unique opportunity to
establish better disease control in the community
by providing improved health care and disease
prevention to inmates before they are released.
Implementing the recommendations in this
carefully researched report will go a long way
toward taking advantage of this opportunity and
contribute significantly to improving the health of
both inmates and the larger community.
Edward A. Harrison, CCHP
President
National Commission on Correctional Health
Care

v

Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Survey
Health Care for Soon-To-Be-Released Inmates: A Survey of State Prison Systems . . . . . . . . . . . . . . . . 1
Carlton A. Hornung, B. Jaye Anno, Robert B. Greifinger, and Soniya Gadre
Prevalence Studies
The Burden of Infectious Disease Among Inmates and Releasees From Correctional Facilities . . . . . . 13
Theodore M. Hammett, Patricia Harmon, and William Rhodes
A Projection Model of the Prevalence of Selected Chronic Diseases in the Inmate Population . . . . . . 39
Carlton A. Hornung, Robert B. Greifinger, and Soniya Gadre
Prevalence Estimates of Psychiatric Disorders in Correctional Settings . . . . . . . . . . . . . . . . . . . . . . . . 57
Bonita M. Veysey and Gisela Bichler-Robertson
Cost-Effectiveness Studies
Cost-Effectiveness of Routine Screening for Sexually Transmitted Diseases Among Inmates
in United States Prisons and Jails . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
Julie R. Kraut, Anne C. Haddix, Vilma Carande-Kulis, and Robert B. Greifinger
Cost-Effectiveness of Preventing Tuberculosis in Prison Populations (overhead slides) . . . . . . . . . . . 109
Zachary Taylor and Cristy Nguyen
Cost-Effectiveness of HIV Counseling and Testing in U.S. Prisons . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Beena Varghese and Thomas A. Peterman
What Is the Value of Immunizing Prison Inmates Against Hepatitis B? (overhead slides) . . . . . . . . . 135
Robert Lyerla
Cost-Effectiveness Analysis of Annual Screening and Intensive Treatment for Hypertension and
Diabetes Mellitus Among Prisoners in the United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
Donna M. Tomlinson and Clyde B. Schechter
Providing Psychiatric Services in Correctional Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Bonita M. Veysey and Gisela Bichler-Robertson

vi
Other Commissioned Paper
Communicable Diseases in Inmates: Public Health Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
Jonathan Shuter
Appendixes
Appendix A:

NCCHC/NIJ Project Participants, Author/Experts, Consultants . . . . . . . . . . . . . . . . . 203

Appendix B:

Biographies of Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

Appendix C:

Information About the National Commission on Correctional Health Care and
Its Position Statements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221

vii

Executive Summary
In the Omnibus Consolidated Appropriations Act
of 1997, Congress instructed the U.S. Department
of Justice to set aside funding for a study of The
Health Status of Soon-To-Be-Released Inmates.
As a result of these earmarked funds, the National
Institute of Justice (NIJ), the research and evaluation arm of the U.S. Department of Justice,
entered into a cooperative agreement with the
National Commission on Correctional Health
Care (NCCHC) to conduct the study. This report
is the culmination of the project’s work. The
project has shown unmistakably that a unique
opportunity exists to reduce the health risks and
financial costs to the community that are associated with releasing large numbers of inmates
with undiagnosed and untreated diseases.
Volume 1 of The Health Status of Soon-To-BeReleased Inmates has seven chapters. This summary
outlines the information presented in considerably
more detail in volume 1. It is important to read the
entire volume to gain a full understanding of the
problems and opportunities associated with the
health status of inmates. Volume 2 of the report
includes the papers commissioned for the project.
They form the basis for the project’s findings and
policy recommendations.

Introduction
The inmate population in the United States has
been growing rapidly since the early 1970s: As
of 1999, an estimated 2 million persons were
incarcerated in the Nation’s jails and prisons,
compared with 325,400 in 1970—an increase of
about 500 percent.1 Approximately 11.5 million
inmates were released into the community in
1998, most from city and county jails.2 As
explained below, these inmates have high rates of
communicable disease, chronic disease, and
mental illness. Coupled with the expanding
inmate population, these high rates of disease
create a critical need for preventing, screening,
and treating illness before inmates are released
into the community.3 Why?

•

Some of the serious diseases affecting
inmates, including sexually transmitted
diseases (STDs), human immunodeficiency
virus/acquired immunodeficiency syndrome
(HIV/AIDS), hepatitis B and C, and tuberculosis (TB), can be transmitted to other
inmates.

•

The Nation’s one-half million correctional
employees4—and thousands of daily visitors
to prisons and jails—may be at risk of
becoming infected from inmates with
communicable diseases if appropriate
precautions are not implemented.

•

Inmates with communicable diseases who are
released without having been effectively
treated may transmit these conditions in the
community, threatening public health.

•

Inmates who are released with untreated
conditions may become a serious financial
burden on community health care systems.

Because they have a large and concentrated
population of individuals at high risk for disease,
prisons and jails offer a unique opportunity for
improving disease control in the community by
providing comprehensive health care and disease
prevention programs to inmates.5 Prisons and jails
make it possible to reach a population that is
largely underserved and difficult to identify and
treat in the general community. Because inmates
are literally a “captive” audience, it is vastly more
efficient and effective to screen and treat them
while they are incarcerated than it is to conduct
extensive outreach in local communities designed
to encourage at-risk individuals to go to a clinic
for testing and treatment.

History of the Project
The Health Status of Soon-To-Be-Released
Inmates project involved several components.
A steering committee coordinated the work and

viii
provided expert guidance to the project. Three
expert panels, one each on communicable disease,
chronic disease, and mental illness, provided
expert guidance to the steering committee. Panel
members included many of the Nation’s most
respected researchers, practitioners, and scholars
in the fields of public and correctional health care
(see appendixes A and B). Centers for Disease
Control and Prevention (CDC) staff were especially helpful in guiding the scholarly work
of the expert panels.
After identifying the specific communicable
diseases, chronic diseases, and mental illnesses
the project would examine, each expert panel
estimated the extent of illness among inmates
for the more common but remediable health
problems; determined the cost-effectiveness of
preventing or treating these health problems; and
developed public policy recommendations for
capitalizing on these opportunities.
The steering committee conducted a mail survey
of State prison systems to collect information on
policies and procedures for discharge planning
and for providing medications to inmates with
chronic disease and mental illness when they
were released. The survey also asked about the
availability of databases on the prevalence of
chronic disease and mental illness.6
The steering committee commissioned eight
papers and two sets of presentation materials from
nationally known experts in the correctional and
public health care fields. The authors estimated
the prevalence of the selected diseases in prisons
and jails and calculated whether it would save
money or be cost effective to prevent, screen for,
or treat these diseases. The papers present the
principal empirical support for the project’s
policy recommendations.

Prevalence of Communicable Disease,
Chronic Disease, and Mental Illness
Among the Inmate Population
Different procedures were used to estimate the
prevalence of disease and mental illness among
the inmate population, but the estimates rely on
well-established national databases.

Communicable disease7—prevalence
The approximate number of inmates with selected
communicable diseases in 1997 was calculated by
applying national prevalence estimates for each
condition to the total number of inmates in U.S.
prisons and jails on June 30, 1997. The approximate number of releasees with these conditions
was obtained by applying the same prevalence
percentages to the total unduplicated number of
persons released from prisons and jails during
1996 (the most recent data available at the time
the estimates were done). Because the estimates
for releasees are based on total numbers of
persons released during a full year, an especially
high figure for jails, they are much higher than the
estimates for inmates, which are based on the
correctional population on a given day. Statistics
on total number of individuals incarcerated during
a full year are not available.
The estimated prevalence of selected communicable diseases in prisons and jails is as follows:
•

An estimated 34,800 to 46,000 inmates in
1997 were infected with HIV. An estimated
98,500 to 145,500 HIV-positive inmates were
released from prisons and jails in 1996.

•

Included among the HIV-positive inmates in
1997 were an estimated 8,900 inmates with
AIDS. An estimated 38,500 inmates with
AIDS were released from prisons and jails in
1996.

•

There were an estimated 107,000 to 137,000
cases of STDs among inmates in 1997 and at
least 465,000 STD cases among releasees:
36,000 inmates in 1997 and 155,000 releasees
in 1996 had current or chronic hepatitis B
infection; between 303,000 and 332,000
prison and jail inmates were infected with
hepatitis C in 1997; and between 1.3 and 1.4
million inmates released from prison or jail
in 1996 were infected with hepatitis C.8

•

About 12,000 people who had active TB
disease during 1996 served time in a
correctional facility during that year.9 More
than 130,000 inmates tested positive for latent

ix
TB infection in 1997. An estimated 566,000
inmates with latent TB infection were
released in 1996.
Thus, a highly disproportionate number of
inmates suffer from infectious disease compared
with the rest of the Nation’s population. During
1996, about 3 percent of the U.S. population spent
time in a prison or jail; however, between 12 and
35 percent of the total number of people with
selected communicable diseases in the Nation
passed through a correctional facility during that
same year.
•

•

•

•

•

Seventeen percent of the estimated 229,000
persons living with AIDS in the United States
in 1996 passed through a correctional facility
that year.10 The prevalence of AIDS among
inmates is five times higher than among the
general U.S. population.11

Chronic disease14—prevalence
•

The prevalence of asthma among Federal,
State, and local inmates in 1995 is estimated
to be between 8 and 9 percent, for a total of
more than 140,000 cases nationwide. Prevalence rates for asthma are higher among
inmates than among the total U.S. population.

•

The prevalence of diabetes in inmates is
estimated to be about 5 percent, for a total of
nearly 74,000.

•

More than 18 percent of inmates are estimated to have hypertension, for a total of
more than 283,000 inmates.

Mental illness15—prevalence
The estimated prevalence of mental illness among
jail inmates is as follows:

The estimated 98,000 to more than 145,000
prison and jail releasees with HIV infection in
1997 represented 13 to 19 percent of all HIVpositive individuals in the United States.

•

An estimated 1 percent have schizophrenia or
another psychotic disorder.

•

About 8–15 percent have major depression.

The estimated 155,000 releasees with current
or chronic hepatitis B infection in 1996
indicate that between 12 and 15 percent of all
individuals in the United States with chronic
or current hepatitis B infection in 1996 spent
time in a correctional facility that year.

•

Between 1 and 3 percent have bipolar
disorder.

•

Between nearly 2 and less than 5 percent of
jail inmates are estimated to have dysthymia
(less severe but longer term depression).

The estimated 1.3–1.4 million releasees
infected with hepatitis C in 1996 suggest that
an extremely high 29–32 percent of the
estimated 4.5 million people infected with
hepatitis C in the United States12 served time
in a correctional facility that year. The
17.0–18.6 percent prevalence range of
hepatitis C among inmates—probably an
underestimate—is 9–10 times higher than the
estimated hepatitis C prevalence in the
Nation’s population as a whole.13

•

Between 14 and 20 percent have some type of
anxiety disorder.16

•

Another 4 to less than 9 percent suffer from
post-traumatic stress disorder.

Of all people in the Nation with active TB
disease in 1996, an estimated 35 percent
(12,200) served time in a correctional facility
that year. The prevalence of active TB among
inmates is between 4 and 17 times greater
than among the total U.S. population.

The estimated prevalence of mental disorders
among State prison inmates is as follows:
•

An estimated 2–4 percent have schizophrenia
or another psychotic disorder.

•

Between 13 and less than 19 percent have
major depression.

•

Between 2 and less than 5 percent have
bipolar disorder.

x
•

Between 8 and less than 14 percent have
dysthymia.

•

Between 22 and 30 percent have an anxiety
disorder.

•

Between 6 and 12 percent have post-traumatic
stress disorder.

Improving Correctional Health Care:
A Unique Opportunity to Protect
Public Health
The large concentration of prison and jail inmates
with serious disease or mental illness affords a
unique opportunity to provide needed treatment
and prevention and to help protect public health
in general. To what extent are prisons and jails
seizing this opportunity? Many correctional
agencies are doing too little to address communicable disease, chronic disease, and mental
illness.

Communicable disease17—current state of
corrections prevention, screening, and
treatment programs
•

•

•

Few prison or jail systems have implemented
comprehensive HIV-prevention programs18 in
all their facilities.
On average, less than one-quarter of jail
inmates undergo routine laboratory testing for
syphilis during incarceration. In some jails,
only 2–7 percent of inmates are tested.
More than 90 percent of State and Federal
prisons, and about half of jails, routinely
screen at intake for latent TB infection and
active TB disease. Particularly in jails,
however, many inmates are released before
skin tests can be read. Most prisons and jails
report that they isolate inmates with suspected
or confirmed TB disease in negative pressure
rooms. Some facilities, however, do not test
the rooms to ensure that the air exchange is
working properly, or they continue to use the
rooms even when the air exchange is known
to be out of order.

Chronic disease—current state of
corrections prevention, screening, and
treatment programs
Of the 41 State correctional systems that responded to a survey conducted for The Health Status of
Soon-To-Be-Released Inmates project,19 only 24
reported they had protocols for diabetes, 25 for
hypertension, and 26 for asthma. A content
analysis revealed that many of these “guidelines”
were incomplete or out of date.

Mental illness—current state of
corrections prevention, screening, and
treatment programs
Few jails provide a comprehensive range of
mental health services.20 Only 60 percent provide
mental health evaluations, 42 percent provide
psychiatric medications, 43 percent provide crisis
intervention services, and 72 percent provide
access to inpatient hospitalization.21 A majority
of State adult prisons provide screening and
assessment for mental illness, medication and
medication monitoring, counseling or verbal
therapy, and access to inpatient care. Only 36
percent of prisons have specialized housing for
individuals with stable mental health conditions.22
Continuity of care for inmates released with
communicable disease, chronic disease, and
mental illness is especially inadequate. Only 21
percent of jails provide case management or
prerelease planning for mentally ill inmates.23

Corrections’ Mixed Record of
Compliance With National Clinical
Guidelines
Many prisons and jails fail to conform to
nationally accepted clinical guidelines. For
example, consider the following:
•

A significant proportion of prisons and jails
do not adhere to CDC standards with regard
to screening for and treating latent TB
infection and active disease. About 10 percent
of State and Federal prisons, and about 50
percent of jails, do not have mandatory TB
screening for inmates at intake and annually
thereafter.24

xi
•

Most prisons and jails fail to conform to
nationally accepted health care guidelines for
mental health screening and treatment.
Seventeen percent of jails and prisons do not
provide recommended intake screening for
mental illness, and 40 percent of jails and
17 percent of prisons do not provide
recommended mental health evaluations.25

By rectifying these gaps in prevention, screening,
and treatment services in prisons and jails,
communities can take advantage of a tremendous
opportunity to improve public health by reducing
the problems associated with untreated inmates
returning to the community. Furthermore,
addressing these health care deficiencies would
be cost effective.

•

For correctional systems with HIV prevalence rates as low as 1.5 percent, an HIVprevention program of voluntary counseling
and testing for HIV-infected inmates in prison
would be a cost saving. Offering counseling
to 10,000 prison inmates would prevent three
future cases of HIV if 60 percent of those
inmates agreed to be counseled and tested. On
the three cases alone, $140,000 could be
saved. Counseling and testing 10,000 inmates
would cost the prison system about $117,000,
or approximately $39,000 per case of HIV
prevented.28

•

For correctional systems with HIV prevalence
rates of at least 2.3 percent—the overall
infection rate in prisons and jails nationwide—
universal screening for tuberculosis in prisons
would be a cost saving because of the
heightened susceptibility to TB of individuals
with HIV. The 989 cases of active TB that
would be prevented for every 100,000
inmates tested, with treatment of those
inmates found to have latent TB infection,29
would save $7,174,509, or $7,254 per case
prevented.30

•

Universal screening in prisons and jails for
hypertension and diabetes would be cost
effective.31

Cost-Effectiveness of Prevention,
Screening, and Treatment of Disease
Among Inmates
A cost-saving intervention saves more money in
averted medical costs than is needed to implement
it. An intervention is cost effective if the benefits
it will achieve are worth the price—even if the
intervention costs more than the money saved.

Cost-effectiveness findings
The members of the project steering committee
and expert panels found that several interventions
would be a cost saving or cost effective.
•

•

Universal screening for syphilis at intake in
both prisons and jails would be a cost saving
(and, therefore, cost effective) if at least 1
percent of the inmates had the disease. Routine syphilis screening and treatment would
save almost $1.6 million for every 10,000
inmates screened.26
Routine screening of men and women in
prisons and jails for gonorrhea and chlamydia
would be cost effective. Universal screening
of women for gonorrhea and chlamydia at
intake to prisons and jails would also be a
cost saving if at least 8 percent of female
inmates had gonorrhea and 9 percent had
chlamydia.27

Scientifically effective interventions
Obviously, only effective medical interventions
can be a cost saving or cost effective. Fortunately,
correctional agencies can introduce many scientifically tested interventions to target inmate
diseases. The following interventions have proven
to be effective for communicable diseases:32
•

Sexually transmitted diseases: Peer-led
educational sessions addressing safer sexual
practices, rapid screening for and treatment of
syphilis, and screening and treatment for
gonorrhea and chlamydia.

•

HIV/AIDS: Encouraging all inmates with
risk factors to agree to be tested, providing
educational programming to help inmates
avoid acquiring and transmitting HIV/AIDS,

xii
and offering appropriate standard-of-care
treatment to all inmates with HIV infection.
•

•

Tuberculosis: Training correctional staff to
be alert for inmates with TB symptoms,
screening all new admissions, testing current
inmates and all staff annually, having access
to properly operating negative pressure
isolation rooms, providing prompt and
effective treatment under direct observation,
and providing for followup in the community
when release precedes completion of
treatment.

Logistical barriers, such as short periods of
incarceration, security-conscious administration procedures for distributing medications,
and difficulty coordinating discharge
planning.

•

Limited resources that require difficult
budgeting decisions to meet the high cost of
many health care services and some medications, and that make it difficult to provide
adequate space for medical services.

•

Correctional policies, such as failure to
specify minimum levels of required care in
contracts with private health care vendors,
delays caused by the need to escort inmates to
medical treatment, poor communication
between public health agencies and prisons
and jails, and lack of adequate clinical
guidelines.

Hepatitis B and C: Routinely vaccinating all
inmates, or susceptible inmates, against
hepatitis B and offering educational sessions
that present strategies to avoid acquiring and
transmitting infection.

Empirically based interventions are known to
reduce illness and death associated with several
chronic diseases, including asthma, diabetes, and
hypertension. Appendix D in volume 1, “Sample
Draft Clinical Guidelines,” provides examples of
these proven interventions.33

Barriers to Effective Prevention,
Screening, and Treatment—and
Overcoming Them
Despite the compelling reasons for improving the
prevention, screening, and treatment of disease
among inmates, significant barriers may make it
difficult for prisons and jails to improve these
services. Most barriers fall into one of four
categories:
•

•

Lack of leadership, such as failure to
recognize the need for improved health care
services, reluctance to consider that
improving public health is a correctional
responsibility, and unwillingness of public
health agencies to advocate for improving
correctional health care or to collaborate to
promote improvement.

Most of these barriers to improved health care for
inmates can be overcome. First, position statements that a number of well-respected, national
professional groups have developed describing
appropriate health care for inmates can be used as
leverage to encourage correctional administrators
to find ways of resolving barriers to providing
adequate care. A list of NCCHC position statements appears in appendix C. Second, collaboration among correctional agencies, public health
departments, and community-based organizations
can help overcome the lack of correctional health
care funds and staff. Public health departments
may be willing to contribute funds, staff, and
expertise if they understand that this use of their
resources can advance the cause of public health
in their communities. Public health departments
in some jurisdictions already contribute
significantly to testing and screening of inmates,
providing prevention and treatment programs in
prisons and jails, and following up on inmates
after release to ensure a continuum of care. Many
community-based organizations are interested in
and willing to provide services to inmates.
•

The Hampden County Correctional Center,
which serves 500,000 residents of Massachusetts’ second largest metropolitan area,

xiii
has developed a public health model of
correctional health care that focuses on
disease screening, prevention, treatment,
discharge planning, and continuity of care
for releasees. The program costs about $6
per inmate day, or 9 percent of the facility’s
budget. Based on ZIP Code of residence,
inmates with HIV/AIDS and other serious
medical and mental health conditions are
assigned to one of four health teams that work
jointly in the correctional center and in four
community health centers. Case managers
who work in both agencies provide discharge
planning services for all inmates with HIV/
AIDS and serious mental health problems.
A discharge planning nurse at the facility
provides similar services for inmates with
chronic diseases. Releasees are linked with
community-based agencies that address issues
of family reintegration, housing, employment
training and readiness, and benefit programs.34
•

The Fairfax County (Virginia) Jail has
overcome the pervasive barriers to discharge
planning for mentally ill inmates. A private
nonprofit organization links detainees with
mental health-related services upon release
and maintains the detainee’s family ties while
the person is incarcerated. This affords the
inmate a source of additional support after
release. The organization’s eight staff provide
or arrange for the following services:

Policy Recommendations
The expert panels assembled for The Health
Status of Soon-To-Be-Released Inmates project
developed policy recommendations for improving the health care of prison and jail inmates. The
project steering committee refined the panels’
recommendations. The recommendations are
based on expert consensus that there is sufficient—if not always definitive—scientific
evidence to justify their implementation. Much
of this scientific evidence is presented in this
report.
Many prisons and jails have implemented
interventions that are not reflected in these
recommendations. That this report does not
include an intervention that correctional systems are currently implementing does not mean
that these systems should discontinue the intervention—or that other systems should not
consider introducing it. In fact, professional
organizations, including the National Commission
on Correctional Health Care, will likely develop
new recommendations as clinical studies
demonstrate the effectiveness of additional
interventions.
The policy recommendations to Congress, listed
in full below, are followed by actions that the
steering committee proposes that specified
Federal, State, and local agencies take in order to
support implementation of the recommendations.

S

Transportation and housing assistance to
mentally ill inmates upon release.

S

Teaching, mentoring, and tutoring in the
facilities.

S

Teaching life skills to releasees.

S

Group therapy for inmates and their
families.

S

Support groups for families and close
friends of inmates.

The principal use of disease surveillance in correctional facilities is to monitor disease incidence,
prevalence, and outcomes in the inmate population. Surveillance includes collecting health data
and evaluating the data collection system to assist
correctional health officials in characterizing the
health status of the inmate population. The information obtained from the surveillance system is
used to plan, implement, and evaluate health
needs of the inmate population and their anticipated health needs upon release.

S

Emergency funds for families to buy food
and clothing while providers are in jail.35

I. Congress should promote surveillance of
selected communicable diseases, chronic diseases,

Surveillance36

xiv
and mental illnesses among inmates in all
correctional jurisdictions. Appropriate Federal
agencies in partnership with national healthrelated organizations should:
A. Develop surveillance guidelines to promote
uniform national reporting of selected
conditions to enhance epidemiologic research
of these conditions and assist with accurate
health care planning. Ensure that data
collected in prisons and jails as part of the
surveillance program are collected in the
same manner as they are collected in the
community.37 Surveillance guidelines should
incorporate processes for protecting
confidentiality of data.
B. Create a national correctional health care
database.
1. Develop standardized definitions and
measures for reporting to assess the
prevalence of selected communicable
diseases, chronic diseases, and mental
illnesses.38

They guide the clinician in areas where scientific
evidence of the value of selected interventions
exists to improve survival and clinical outcomes
and to reduce morbidity and the cost of care.
Clinical guidelines are widely used outside
corrections.
II. Congress should promote the use of nationally
accepted evidence-based clinical guidelines for
prisons and jails. This will help assure appropriate
use of resources to prevent, diagnose, and treat
selected communicable diseases, common chronic
diseases, and mental illnesses that are prevalent
among inmates. Appropriate Federal agencies in
partnership with national health-related organizations should:
A. Ensure that the clinical guidelines are
consistent with nationally accepted disease
definitions and evidence-based guidelines
used for the nonincarcerated population.40
B. Disseminate the clinical guidelines to
correctional health care professionals, public
health agencies, and public policymakers.

2. Mandate national reporting of these
prevalence data.

C. Update the clinical guidelines as often as
needed.

3. Design an information system and make
it available for use by local, State, and
Federal correctional authorities to
measure and report the data with the
ability to categorize the data by age, race,
and gender.

D. Develop standardized performance measures
for State and local correctional authorities to
determine adherence to nationally accepted
clinical guidelines.

C. Produce statistical reports of local, State, and
national rates of selected communicable
diseases, chronic diseases, and mental illnesses in prisons and jails to aid planning
correctional and public health programs and
allocate local resources.39
D. Evaluate the utility of surveillance activities
and implement improvements as appropriate.

Clinical guidelines
Clinical guidelines provide definitions and
abbreviated decision trees for the diagnosis and
management of various diseases and conditions.

E. Train correctional health and public health
professionals in the use of these clinical
guidelines and performance measures.
F. Develop tools for correctional systems to
assess over-prescribing and under-prescribing
of psychotropic medications.

Immunizations
Immunizations prevent the development of a
variety of communicable diseases in individuals.
In the case of diseases such as hepatitis B, poliomyelitis, measles, mumps, or rubella, immunizations prevent the transmission of disease to
susceptible individuals in the general population.
Such immunizations are nationally accepted and

xv
promoted by the Centers for Disease Control and
Prevention. Some immunizations are directly cost
saving and others are highly cost effective.
III. Congress should establish and fund a national
vaccine program for inmates to protect them and
the public from selected vaccine-preventable
communicable diseases.
A. The vaccination program should be similar to
the National Vaccine Program for Children.
B. The program should conform to the
recommendations of the CDC’s Advisory
Committee on Immunization Practices
(ACIP).41

National correctional health care literature
database
To function competently, correctional health care
clinicians require access to the medical literature,
especially as it relates to correctional health care
issues. Existing resources do not provide this
level of specificity.
IV. Congress, through appropriate Federal
agencies and health-related national
organizations, should develop and maintain a
national literature database for correctional health
care professionals, including a compendium of
policies, standards, guidelines, and peer-reviewed
literature.

Ethical decisionmaking
Correctional health care professionals function in
a uniquely restrictive environment with limited
opportunity for peer review of medical policies
and administrative actions. A national forum is
needed to discuss issues, such as confidentiality,
informed consent, clinical management of
hepatitis C42 and HIV, and the availability of
biomedical research.
V. Congress should establish a national advisory
panel on ethical decisionmaking among correctional and health authorities to assist those authorities in addressing ethical dilemmas encountered
in correctional health care.

Eliminate barriers to inmate health care
In correctional facilities, health care professionals
face unique barriers to the delivery of health
services. These include constraints on policy,
budgets, priorities, and staffing. Correctional
institutions are positioned to provide individual
care to inmates and protect the public health
through aggressive health promotion and disease
prevention efforts. At all levels of government,
public policymakers should recognize that
eliminating barriers to health care for inmates
provides long-term public health benefits.
VI. Congress, through appropriate Federal and
State agencies and health-related national
organizations, should identify and eliminate
barriers to the successful implementation of
public health policy.
A. Reduce obstructions to effective public health
programs within correctional facilities and in
the community.
B. Promote continuity of inmate health care by
maintaining Medicaid benefits for eligible
inmates throughout their incarceration.
C. Promote continuity of ex-offender health care
by mandating immediate Medicaid eligibility
upon release.
D. Provide incentives to jails and prisons to
expand their alcohol and other drug treatment
programs. These services should be gender
specific and made available to inmates from
admission through release, with special
attention paid to inmates with both mental
illness and substance abuse problems.

Correctional health care research
Too little is known about the epidemiology of
disease in correctional populations and too little
has been done to evaluate programs designed to
improve inmate health.
VII. Congress, through appropriate Federal
agencies and health-related national
organizations, should support research in

xvi
correctional health care to identify and address
problems unique to correctional settings.
A. Fund projects to evaluate models that
emphasize creative, cost-effective options
for continuity of care following release.
B. Fund research programs to define effective
health education and risk reduction strategies
for inmates. These strategies need to deal
with relevant differences between inmate and
noninmate populations. The research
programs should work through public,
private, and community-based health care
agencies.
C. Fund research programs to identify
correctional system barriers that prevent
correctional health care staff from implementing prudent medical care and public
health recommendations.

Improve delivery of health care
For a variety of reasons, the scope and content of
correctional health care services vary. The quality
of care is not as high as it might be, resulting in
unnecessary morbidity, premature mortality, and
increased costs.
VIII. Congress, through appropriate Federal
agencies and medically based accrediting
organizations, should promote improvements to
the delivery of inmate health care.43
A. Require Federal, State, and local correctional
systems to adhere to nationally recognized
standards for the delivery of health care
services in corrections.44 These standards
should include access to care, quality of care,
quality of service, and appropriate credentialing of health care professionals.
B. Provide sufficient resources for correctional
systems to adhere to national standards.
C. Weigh the correctional system’s adherence to
national standards for health care delivery
whenever determining funding levels for the
system.

Disease prevention
Primary prevention is designed to keep disease
from occurring. Examples include lifestyle
choices and vaccination against selected communicable diseases. Primary prevention is widely
believed to be the best and most cost-effective
use of health care dollars. In some cases, it is
also a cost saving—that is, prevention program
saves more money than it costs to implement.
Secondary prevention (screening) is the early
detection of disease that already exists but may
not be apparent to the patient.45
IX. Congress, through appropriate Federal
agencies and national organizations, should
encourage primary and secondary disease
prevention efforts.
A. Promote primary disease prevention measures
by requiring Federal, State, and local
correctional agencies to:
1. Provide all inmates with a smoke-free
correctional environment. Offer tobacco
cessation programs for all staff and
inmates as a method of achieving
tobacco-free facilities.
2. Offer heart-healthy choices on institutional menus and in commissaries.
3. Make daily aerobic exercise available to
all inmates.
4. Consistent with the recommendations of
the ACIP, make hepatitis B vaccines
available to all inmates, even when their
length of incarceration is short or
indeterminate.
5. Screen all females for pregnancy. Test
women found to be pregnant for hepatitis,
HIV infection, syphilis, gonorrhea, and
chlamydia. Provide HIV treatment to
HIV-infected mothers to prevent transmission of the disease to the newborn.
6. Although not a correctional system
responsibility, administrators should seek

xvii
to collaborate with community health care
providers to ensure the timely immunization of all infants born to mothers who
test positive for hepatitis B.
7. Offer scientifically based risk reduction
education on HIV infection and STD to
all inmates.
B. Promote secondary disease prevention
measures by using nationally accepted
evidence-based clinical guidelines as
appropriate.
1. Provide hypertension, obesity, asthma,
and seizure disorder screening for all
prison inmates.
2. Provide diabetes and hyperlipidemia
screening for jail and prison inmates at
high risk.
3. Provide suicide prevention programs,
including timely screening for inmates
at high risk for suicide.
4. Prevent the spread of tuberculosis.
a. Consistent with nationally accepted
guidelines,46 routinely screen inmates
for TB disease and infection, and
provide preventive treatment for
inmates with latent TB infection.
b. Promote the use of short-course
preventive therapy (delivered over
2 months) in correctional settings.
c. Strengthen links of TB control efforts
between correctional facilities and
public health departments.
d. On employment and annually thereafter, screen all correctional staff who
have inmate contact for latent TB
infection.
5. Prevent the spread of HIV infection.
a. Encourage voluntary HIV counseling
and testing of inmates.

b. Provide appropriate treatment for HIVpositive, pregnant inmates to prevent
HIV transmission to their babies.47
6. Screen inmates for syphilis, gonorrhea,
and chlamydia routinely upon reception at
prisons and jails, and treat inmates who
test positive for these infections.48

Prerelease planning
Many inmates are released into the community
while still being treated for communicable and
chronic diseases or mental illness. Ensuring
continuity of care upon release can reduce health
risks to the public, such as in cases of tuberculosis
and sexually transmitted diseases. Continuity of
care upon release for inmates with co-occurring
mental illness and substance abuse disorders can
reduce the risk of illicit drug use in the community. It is cost effective to the community to provide
continuity of care on release for inmates with
chronic disease.
X. Congress, through appropriate Federal
agencies and national organizations, should
encourage Federal, State, and local correctional
facilities to provide prerelease planning for health
care for all soon-to-be-released inmates.
A. Address the medical, housing, and postrelease
needs of inmates in prerelease planning and
make use of appropriate resources and new
technologies.
B. Coordinate discharge planning efforts between appropriate public agencies—such as
correctional, parole, mental health, substance
abuse, and public health agencies—to prevent
disease transmission and to reduce society’s
costs from untreated and undertreated illness.

Recommended actions by government
agencies
The steering committee and expert panels recognized that many Federal agencies have a role in
affecting the health status of soon-to-be-released
inmates. Within the U.S. Department of Health
and Human Services (DHHS), for example,
agencies such as the Centers for Disease Control
and Prevention (CDC), the Health Resources and
Services Administration (HRSA), the Substance

xviii
Abuse and Mental Health Services
Administration (SAMHSA), the National Institute
of Drug Abuse (NIDA), the Office of Women’s
Health (OWH), the Public Health Service (PHS),
the Indian Health Service (IHS), and the Office of
Minority Health (OMH) are actively engaged in
health services programs that impact on inmates.
In addition, within the U.S. Department of Justice
(DOJ), agencies such as the National Institute of
Justice (NIJ), the Immigration and Naturalization
Service (INS), the Bureau of Prisons (BOP)
including the National Institute of Corrections
(NIC), the Corrections Program Office (CPO),
and the Office of Justice Programs (OJP) conduct
programs and activities that ultimately influence
inmate health. Finally, the Office of the Surgeon
General (OSG) and the White House Executive
Office of National Drug Control Policy (ONDCP)
also impact the health care of inmates.
The steering committee and expert panels
recommend that Congress provide the necessary
authorization, funding, and other assistance to the
appropriate agencies to implement the following
recommendations.
I.

The Secretary of DHHS should direct
appropriate agencies to collaborate with
other agencies in analyzing the potential
economic benefits to the community of early
diagnosis and treatment of communicable
diseases, chronic diseases, and mental
illnesses.

II. The Secretary should direct CDC to collaborate with NIJ, NIC, CPO, and other DOJ
divisions in developing tools to assist State
and local agencies in deciding when and
whom to screen for communicable diseases
in correctional settings.
III. The Secretary should direct all appropriate
agencies within the department to work
toward reducing interagency regulatory and
bureaucratic barriers to testing and counseling for HIV, TB, and STDs among
inmates.
IV. The Secretary and the Attorney General
should involve correctional health professionals in public health planning and the

evaluation of correctional health care
programs.
V. The Secretary and the Attorney General
should direct appropriate agencies to support
field tests of innovative medical information
systems to improve the continuity of care for
inmates transferred between correctional facilities or released into the community. These
efforts should concentrate on removing
barriers that impede the transfer of appropriate medical information.
VI. The Secretary and the Attorney General
should direct appropriate agencies to develop
educational programs to inform policymakers
and the public about the public health and
social benefits of investing in health care for
inmates.
VII. A Federal interagency task force, currently
established and cochaired by CDC and NIJ,
should report annually to the Secretary and
the Attorney General on the status of correctional health care in the Nation and on
progress made toward implementing the
recommendations included in this report.

Notes
1. Beck, A.J., Prisoners in 1999, Bulletin, Washington,
DC: U.S. Department of Justice, Bureau of Justice
Statistics, August 2000, NCJ 183476.
2. Beck, Allen, U.S. Department of Justice, Bureau of
Justice Statistics, personal interview, May 15, 2000.
3. Corrections departments also have a legal obligation
to treat inmates. The most important single ruling has
been the U.S. Supreme Court’s 1976 finding in Estelle
v. Gamble, 429 U.S. 97, that “deliberate indifference”
(not mere medical malpractice) to “serious medical
needs” of inmates violates the eighth amendment’s
prohibition against cruel and unusual punishment.
4. An estimated 339,070 people were employed in
State and Federal correctional facilities in 1995 and
165,500 were employed in jails. See Stephan, J.J.,
Census of State and Federal Correctional Facilities,
1995, Bureau of Justice Statistics Executive Summary,
Washington, DC: U.S. Department of Justice, Bureau
of Justice Statistics, August 1997, NCJ 166582; and
Perkins, C.A., J.J. Stephan, and A.J. Beck, Jails and

xix
Jail Inmates, 1993–94, Bulletin, Washington, DC: U.S.
Department of Justice, Bureau of Justice Statistics,
April 1995, NCJ 151651.

(0.627) was then applied to the number of incident
cases for 1996 (21,337) to obtain the estimate of
34,000 prevalent cases in 1996.

5. See, for example, Glaser, J.B., and R.B. Greifinger, “Correctional Health Care: A Public Health
Opportunity,” Annals of Internal Medicine 118(2)
(1993): 139–145.

10. Centers for Disease Control and Prevention,
HIV/AIDS Surveillance Report, 1997, Atlanta, GA:
U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention, 1997.

6. Hornung, C.A., B.J. Anno, R.B. Greifinger, and S.
Gadre, “Health Care for Soon-To-Be-Released
Inmates: A Survey of State Prison Systems,” paper
prepared for the National Commission on Correctional
Health Care, Chicago, Illinois, n.d. (Copy in this
volume.)

11. A more recent study concluded that the 1996 AIDS
rate for incarcerated persons was at least six times the
national rate. See Dean-Gaitor, H.D., and P.L.
Fleming, “Epidemiology of AIDS in Incarcerated
Persons in the United States, 1994–1996,” AIDS
13(17) (1999): 2429–2435.

7. Hammett, T.M., P. Harmon, and W. Rhodes, “The
Burden of Infectious Disease Among Inmates and
Releasees From Correctional Facilities,” paper prepared for the National Commission on Correctional
Health Care, Chicago, Illinois, May 2000. (Copy in
this volume.)

12. Based on the prevalence estimate in McQuillan,
G.M., M.J. Alter, L.A. Moyer, S.B. Lambert, and H.S.
Margolis, “A Population-Based Serologic Survey of
Hepatitis C Virus Infection in the U.S.,” in Viral
Hepatitis and Liver Disease, M. Rizzetto, R.H. Purcell,
G.L. Gerin, and G. Verme, eds., Turin, Italy: Edizioni
Minerva Medica, 1997: 267–270.

8. The U.S. Department of Justice, Bureau of Justice
Statistics, is preparing a report for release in 2002
on the prevalence of hepatitis among correctional
populations, based on data from the 2001 census of
State and Federal adult correctional facilities.
9. This figure was derived by applying the prevalence
of TB disease among inmates in prisons (0.04 percent)
and jails (0.17 percent) to the estimated number of
releasees from prisons and jails. The estimate of
releases was calculated by applying a point prevalence
rate for inmates (i.e., the percentage of inmates who
were under treatment for TB disease on a given day in
1997) to the total number of releasees during all of
1996. The estimate suggests that about 12,000 people
who were released from a correctional facility during
1996 had TB disease at some time during that year, but
it does not mean that they all had TB disease at the
time of their release from prison or jail. Most of them
probably did not have TB disease at the time of their
release because, if properly treated, TB disease
typically lasts only a short time. The denominator
(34,000) is an estimate of the total number of persons
with TB in the United States during 1996. The Centers
for Disease Control and Prevention’s TB Registry
Reports, which provided the numbers of cases in a
given year, were discontinued in 1994. The only report
for subsequent years is CDC’s TB surveillance report,
which provides incident (new) cases each year. Therefore, an average ratio of incident cases to prevalent
cases was calculated for the last 3 years in which
Registry Reports were available (1992–94). This ratio

13. Hammett, Harmon, and Rhodes, “The Burden of
Infectious Disease Among Inmates and Releasees” (see
note 7). The 17.0–18.6 percent estimate is probably
very low, given that studies conducted in individual
prison systems have found prevalence rates of 30–40
percent.
14. Hornung C.A., R.B. Greifinger, and S. Gadre,
“A Projection Model of the Prevalence of Selected
Chronic Disease in the Inmate Population,” paper
prepared for the National Commission on Correctional
Health Care, Chicago, Illinois, n.d. (Copy in this
volume.)
15. Veysey, B.M., and G. Bichler-Robertson, “Prevalence Estimates of Psychiatric Disorders in Correctional Settings,” paper prepared for the National Commission on Correctional Health Care, Chicago, Illinois,
May 1999. (Copy in this volume.)
16. Dysthymia and anxiety range from completely
disabling (e.g., agoraphobia) to not even mildly
incapacitating (e.g., generalized anxiety disorder).
Depending on the severity of their condition, many
individuals with dysthymia and anxiety do not require
medical treatment.
17. Hammett, T.M., P. Harmon, and L.M. Marushak,
1996–1997 Update: HIV/AIDS, STDs, and TB in
Correctional Facilities, Issues and Practices, Washington, DC: U.S. Department of Justice, National
Institute of Justice, July 1999, NCJ 176344.

xx
18. A comprehensive HIV-prevention program
provides HIV counseling and testing, instructor-led
education, peer-based programs, and multisession
HIV-prevention counseling in each correctional
facility.

Thoracic Society and the Centers for Disease Control
and Prevention, “Diagnostic Standards and Classification of Tuberculosis in Adults and Children,”
American Journal of Respiratory and Critical Care
Medicine 161 (2000): 1376–1395.

19. Hornung, C.A., B.J. Anno, R.B. Greifinger, and
S. Gadre, “Health Care for Soon-To-Be-Released
Inmates: A survey of State Prison Systems” (see
note 6).

30. Taylor, Z., and C. Nguyen, “Cost-Effectiveness
of Preventing Tuberculosis in Prison Populations,”
presentation prepared for the National Commission
on Correctional Health Care, Chicago, Illinois, n.d.
(Copy in this volume.)

20. Steadman, H.J., and B.M. Veysey, Providing
Services for Jail Inmates With Mental Disorders,
Research in Brief, Washington, DC: U.S. Department
of Justice, National Institute of Justice, January 1997,
NCJ 162207.
21. Ibid.
22. Manderscheid, R.W., and M.A. Sonnenschein,
eds., Mental Health, United States, 1992, Rockville,
Maryland: U.S. Department of Health and Human
Services, 1992.
23. Steadman, H.J., and B.M. Veysey, Providing
Services for Jail Inmates With Mental Disorders
(see note 20).
24. Hammett, T.M., P. Harmon, and L.M. Maruschak,
1996–1997 Update: HIV/AIDS, STDs, and TB in
Correctional Facilities (see note 17).
25. Steadman, H.J., and B.M. Veysey, Providing
Services for Jail Inmates With Mental Disorders
(see note 20).
26. Kraut, J.R., A.C. Haddix, V. Carande-Kulis, and
R.B. Greifinger, “Cost-Effectiveness of Routine
Screening for Sexually Transmitted Disease Among
Inmates in United States Prisons and Jails,” paper
prepared for the National Commission on Correctional
Health Care, Chicago, Illinois, February 2000.
(Copy in this volume.)
27. Ibid.
28. Varghese, B., and T.A. Peterman, “CostEffectiveness of HIV Counseling and Testing in U.S.
Prisons,” paper prepared for the National Commission
on Correctional Health Care, n.d. (Copy in this volume.)
29. American Thoracic Society and the Centers for
Disease Control and Prevention, “Targeted Tuberculin
Testing and Treatment of Latent Tuberculosis Infection,” American Journal of Respiratory and Critical
Care Medicine 161 (2000): 221S–247S; American

31. Tomlinson, D.M., and C.B. Schechter, “CostEffectiveness Analysis of Annual Screening and
Intensive Treatment for Hypertension and Diabetes
Mellitus Among Prisoners in the United States,” paper
prepared for the National Commission on Correctional
Health Care, Chicago, Illinois, n.d. (Copy in this
volume.)
32. Shuter, J., “Communicable Diseases in Inmates:
Public Health Opportunities,” paper prepared for the
National Commission on Correctional Health Care,
Chicago, Illinois, n.d. (Copy in this volume.)
33. Draft clinical guidelines submitted to the National
Commission on Correctional Health Care, Chicago,
Illinois, currently under consideration for adoption.
(Copy in appendix D of volume 1 of this report.)
34. Hammett, T.M., P. Harmon, and L.M. Maruschak,
1996–1997 Update: HIV/AIDS, STDs, and TB in
Correctional Facilities (see note 17).
35. Morris, S.M., H.J. Steadman, and B.M. Veysey,
“Mental Health Services in United States Jails: A
Survey of Innovative Practices,” Criminal Justice and
Behavior 24 (1) (1997): 3–19.
36. Surveillance is the ongoing systematic collection,
analysis, and interpretation of health data.
37. See, for example, National Center for Health
Statistics, National Health and Nutrition Examination
Survey III [NHANES–III], Atlanta, GA: U.S. Department of Health and Human Services, Centers for
Disease Control and Prevention, 1997.
38. The definitions of mental disorders and presentation of their prevalence in American Psychiatric
Association, Diagnostic and Statistical Manual of
Mental Disorders, 4th ed., Washington, DC: American
Psychiatric Press, 1994, are a good illustration of the
standardized definitions and measures that are needed
in the field of correctional health care.

xxi
39. “Summary of Notifiable Diseases, United States,
1998,” Morbidity and Mortality Weekly Report 47(53)
(December 31, 1999).
40. See, for example, “Guidelines for the Use of
Anti-retroviral Agents in HIV-Infected Adults and
Adolescents,” Rockville, MD: U.S. Department of
Health and Human Services, available at http://
www.hivatis.org/guidelines/adult/Apr23_01/pdf/
AAAPR23S.PDF (updated April 23, 2001); American
Diabetes Association, “Standards for Medical Care for
Patients With Diabetes Mellitus,” Clinical Practice
Recommendations 2000, Diabetes Care (supp. 1)
(2000): 1–23; American Diabetes Association, “Management of Diabetes in Correctional Institutions,”
Clinical Practice Recommendations 2000, Diabetes
Care 21 (supp. 1) (2000): 1–3; National Institutes of
Health, National Asthma Education and Prevention
Program, Expert Panel Report 2: Guidelines for the
Diagnosis and Management of Asthma, Bethesda, MD:
National Heart, Blood, and Lung Institute, February
1997; National Institutes of Health, “Sixth Report of
the Joint National Committee on Prevention, Detection,
Evaluation, and Treatment of High Blood Pressure,”
Bethesda, MD: National Heart, Lung, and Blood
Institute, November 1997; “Clinical Guidelines: Report
of the NIH Panel to Define Principles of Therapy of
HIV Infection and Guidelines for the Use of Antiretroviral Agents in HIV-Infected Adults and
Adolescents,” Bethesda, MD: National Institutes
of Health (updated May 5, 1999); and Centers for
Disease Control and Prevention, “Clinical Guidelines:
1999 USPHS/IDSA Guidelines for the Prevention of
Opportunistic Infections in Persons Infected With
Human Immunodeficiency Virus,” Morbidity and
Mortality Weekly Report 48 (RR–10) (August 20,
1999): 1–59, 61–66.
41. The recommendations of the CDC’s Advisory
Committee on Immunization Practices can be found at
CDC’s Web site: http://www.cdc.gov/nip/publications/
ACIP-list.htm.

42. See the Centers for Disease Control and
Prevention, “Recommendations for Prevention and
Control of Hepatitis C Virus (HCV) Infection and
HCV-Related Chronic Disease,” Morbidity and
Mortality Weekly Report 47 (RR–19) (October 16,
1998): 1–39.
43. For a comparison of accreditation services for
correctional institutions, see Anno, B.J., Correctional
Health Care: Guidelines for the Management of an
Adequate Delivery System, Washington, DC: U.S.
Department of Justice, National Institute of Corrections (in press).
44. See National Commission on Correctional Health
Care, Standards for Health Services in Jails, Chicago,
IL: Author (in press).
45. A detailed discussion of the differences between
primary and secondary prevention may be found in
Last, J.M., Public Health and Human Ecology, 2d ed.,
Stamford, Connecticut: Appleton & Lange, 1998.
46. An excellent source for a tuberculosis clinical
guideline is the Centers for Disease Control and
Prevention at their Web site: www.cdc.gov.
47. See U.S. Department of Health and Human
Services, “Guidelines for the Use of Antiretroviral
Agents in HIV-Infected Adults and Adolescents”
(see note 40).
48. The Centers for Disease Control and Prevention
have prepared “HIV Prevention Through Early
Detection and Treatment of Other Sexually Transmitted
Diseases—United States. Recommendations of the
Advisory Committee for HIV and STD Prevention,”
Morbidity and Mortality Weekly Report 47 (RR–12)
(July 31, 1998).

1

Health Care for Soon-To-Be-Released
Inmates: A Survey of State Prison
Systems

Carlton A. Hornung, Ph.D., M.P.H., Department of Medicine, Center for Health Services and Policy
Research, University of Louisville School of Medicine; B. Jaye Anno, Ph.D., CCHP-A; Robert B.
Greifinger, M.D., National Commission on Correctional Health Care; and Soniya Gadre, M.P.H.,
Department of Medicine, Center for Health Services and Policy Research, University of Louisville
School of Medicine

Introduction
A higher percentage of the population is incarcerated in the United States than in any other
country. In the decade between 1985 and 1995,
the population in prisons and jails increased
dramatically. During this period, the total
correctional population increased by 78.5 percent.
Accounting for this was a 57.3 percent increase in
the number of individuals on probation, a 95.8
percent increase in the number in jail, a 121.2
percent increase in the number in prison, and a
133.2 percent increase in the number on parole.
The rate of growth of the prison population has
averaged about 8.3 percent per year, while jail
inmate population growth averaged 7.0 percent
between 1985 and 1995. According to the Bureau
of Justice Statistics (BJS), in 1995 approximately
3,096,529 persons were on probation, 1,078,500
individuals were in State prisons, another 499,300
were in local jails, and 700,174 were on parole. In
1995, prisons saw 521,970 new admissions of
inmates with a sentence of 1 year or more and
455,139 releases.1
The rebellions that occurred in prisons across
the Nation in the 1960s and 1970s called for
improved health care as one of their central
demands. The U.S. Supreme Court responded in
1976 with the Estelle v. Gamble decision that said
deliberate indifference to the serious medical
needs of prisoners constitutes the “unnecessary
and wanton infliction of pain” prohibited by the
eighth amendment.2 This decision affirmed
inmates’ constitutional right to health care.

Inmates demanded better health care in jails and
prisons before the epidemic of human immunodeficiency virus/acquired immunodeficiency
syndrome (HIV/AIDS) and the concurrent rise in
multiple drug-resistant tuberculosis (TB). These
demands also occurred before Federal initiatives
to reduce the use of illegal drugs. The most
important of these initiatives was the National
Drug Control Strategy, announced in 1989, which
called for mandatory minimum sentences for drug
crimes. This resulted in a 423 percent increase
(from 24,200 in 1985 to 104,400 in 1990) in the
number of new court commitments to State
prisons of individuals whose most serious offense
was a drug offense. While 13.2 percent of newly
sentenced prisoners admitted to State prisons in
1985 were for drug offenses, in 1990 the percentage jumped to 31.7 percent—a 240 percent
increase. The proportion of those newly sentenced
for a drug offense as their most serious crime has
remained at about 31 percent through 1995.3
During the same period, the percentage of inmates
newly sentenced to State prisons for property
crimes (e.g., burglary, larceny/theft, motor vehicle
theft, fraud) dropped from 42.4 to 28.9 percent
(a 31.8 percent decline), and the percentage
sentenced for violent offenses declined from 35.1
to 29.5 percent (a 16 percent decline).
The increase in the percentage of newly sentenced
inmates for drug offenses, coupled with longer
sentences, has dramatically altered the composition of the prison inmate population. In 1985,
only 38,900 inmates out of a total inmate population of 451,812 (8.6 percent) were in State

2
prisons for drug offenses as their most serious
crime.4 By 1995, this number had increased by
478 percent to 224,900 out of a total State prison
inmate population of 989,007 (22.7 percent).
The increase in the numbers of inmates incarcerated for drug offenses has led to concomitant
changes in the demographic profile of inmates.
The numbers of female, nonwhite, and foreignborn inmates have increased disproportionately to
the inmate population as a whole. The significance of these changes cannot be overstated. Most
inmates are poor, have little education, and come
from disadvantaged communities where health
care services other than hospital emergency
rooms are scant or underutilized.
Although considerable data exist about the
prevalence of HIV/AIDS, sexually transmitted
diseases (STDs), and TB in the prison and jail
population,5 little has been published about the
prevalence of hepatitis and still less about the
prevalence of chronic diseases and mental
disorders among inmates. In an effort to acquire
information about the prevalence of chronic
diseases and mental illness in the State prison
inmate population, State departments of
correction were surveyed to determine which
States had information about the demographic
composition of their inmate population, which
maintained databases containing information on
the prevalence of chronic diseases and mental
disorders, and which had information about the
health status of inmates that they had released
recently into the community.
The State prison survey was designed to collect
these data as the first phase of a research plan. A
planned second phase was to review the medical
records of a sample of inmates who had been
recently released from prison in those States that
appeared to have the most complete data on the
health status of their inmate population. The
objective of this second phase was to collect the
information necessary to assess the health status
and health care needs of soon-to-be-released
inmates. Such an assessment, supported by
empirical data, is needed for informed policy

decisions and actions by prison and public health
officials to insure that inmates with communicable
or chronic diseases or mental disorders do not
pose a threat to the health of the communities into
which they are released.

Methods
A mailback questionnaire (see appendix C in
volume 1) was sent to corrections officials in each
State, the District of Columbia, and the Federal
Bureau of Prisons. The survey instrument consists
of three sections and is designed to be completed
by different individuals in the prison health
system. Section 1 requests the following
information:
•

What data are available on the prison system
census.

•

Whether inmate demographic data are
computerized.

•

Whether the prison administration can
determine the demographic profiles of the
current inmate population by age, gender,
and race.

Section 2 of the instrument focuses on chronic
diseases and the availability of medications for
inmates, and seeks the following information:
•

Routine screening practices for hypertension
and diabetes.

•

Policies and procedures for vaccinating
inmates for hepatitis B.

•

The prevalence of certain chronic medical
conditions (i.e., asthma, diabetes, hypertension, and heart disease).

•

The ability of the prison administration to
determine the age-, race-, and gender-specific
prevalence rates of those conditions.

•

The existence of systemwide clinical
protocols or treatment guidelines for the

3
management of asthma, diabetes,
hypertension, and heart disease.
•

Whether pharmacy data are computerized.

•

The number of inmates taking selected
medications.

•

Policies and procedures about giving inmates
medication when they are released into the
community.

•

The ability to identify recently released
inmates with chronic conditions.

Section 3 of the survey asks administrators the
following questions about mental health:
•

Whether they have data on the number of
inmates with mental disorders.

•

How mental disorders are classified.

•

Whether inmates with selected mental
disorders can be identified by age, gender,
and race.

•

The prevalence of coexisting alcohol or other
substance dependency.

•

What treatment protocols are used.

•

Whether inmates recently released with a
mental disorder can be identified.

It was hoped that the information provided from
the survey would enable the research team to
identify those State prison systems with the most
comprehensive data on the health status of their
inmate populations and of inmates released into
the community within the past 6 and 12 months.
Once those State systems could be identified, the
second phase of the research plan called for
selecting a sample of prison facilities in these
systems at which medical record reviews could be
conducted to collect comprehensive data on the
health status of a sample of inmates who were
recently released into the community. Researchers

were particularly interested in the prevalence of
communicable diseases, chronic diseases, and
mental health problems as well as provisions for
continuity of health care. State prison systems and
facilities would be selected to reflect States or
regions with known high and low prevalence of
disease (e.g., HIV/AIDS).
The surveys were mailed to the State departments
of correction by the National Commission on
Correctional Health Care (NCCHC). States that
did not respond within 1 month were contacted
by telephone by the Data Coordinating Center,
NCCHC, and/or the project director. At least two
calls were made to encourage response.

Results
Forty-one States,6 including all of the Midwestern
States and the District of Columbia, responded,
although missing information was a significant
problem. Three of the responding States did not
provide reliable prevalence data and were not
included in that analysis. One State reported
hospital discharge figures, another reported
chronic disease percentages, and the third reported
prevalence for one institution in a State system.
No response was obtained from the Federal
Bureau of Prisons or from 10 States: 1 in the
Northeast, 5 in the South, and 4 in the West.
The first section of the survey requested information on the inmate census. Table 1 presents the
average daily population, total annual intakes, and
total annual releases for the most current year
available for those States that responded to the
survey.
Responding States reported an average daily
population (ADP) of a little more than 17,800
inmates for a total census of 641,137. The total
represents approximately 76 percent of the
prisoners under the jurisdiction of State
correctional authorities at yearend 1996. These
States reported more than 333,587 new intakes
and 309,929 releases for the most recent period
for which they had data (the period ending June
1997 to the period ending January 1998).

4
Table 1. Inmate Census Data for States Responding to the Survey*
Average Daily Population

Total Annual Intakes

Total Annual Releases

Range
Minimum

840

578

520

Maximum

69,671

29,868

30,469

Mean

17,809

9,266

8,609

Medium

12,134

6,610

5,576

641,137
333,587
Sum
* Based on 36 of 41 responses; 2 States provided no data; data from 3 States were not usable.

Forty States indicated they had computerized
systems for recording inmate demographic data,
yet only 38 reported having the capability to
determine the current population by their
demographic characteristics (e.g., age, race, and
gender). All 41 responding States said they could
determine the gender distribution of their inmate
population; 39 could determine the age and the
race distribution. Most important, 37 States
reported they had the capability to determine the
age, race, and gender distribution of their inmates
(e.g., the number of Hispanic/Latino males aged
35–40).
Eight States (20 percent of those responding)
reported that they designate certain facilities for
housing inmates with specific chronic diseases or
cluster inmates with chronic conditions in certain
facilities. These eight State prison systems had an
ADP totaling 217,492, with a total annual intake
of 96,734 and total annual releases of 94,766.
This amounts to 26.5 percent of the total inmate
population in the responding States, 20.6 percent
of total annual intakes in those States, and 21.9
percent of total annual releases among responding
States. Those State systems that have designated
facilities for housing inmates with specific

309,929

chronic diseases or that cluster inmates with
chronic conditions in certain facilities have larger
populations than States that did not designate one
or more facilities to manage inmates with chronic
conditions (mean ADP 27,187 vs. 19,504; mean
annual intake 12,092 vs. 12,047; and mean total
annual releases 11,846 vs. 10,887).
The 10 States that did not respond to the survey
have generally smaller prison populations
according to BJS.7 Two nonresponding States had
inmate populations of fewer than 2,000; two had
populations of about 3,500; three had populations
of nearly 10,000; and two had populations of
approximately 15,000. Only one had a population
of more than 115,000.

Screening for Diabetes and
Hypertension
States were asked if they routinely screened
inmates for fasting blood sugar and for blood
pressure at intake to their prisons. Table 2 shows
the number of State prison systems that routinely
screen inmates at intake, their total annual intake,
and the percentage of all annual intakes in all 39
responding States who are screened for diabetes
and hypertension.

Table 2. Intake Screening for Diabetes and Hypertension
Screened for:

# of States

Mean Annual Intake

% Total Annual Intake Screened*

Fasting blood sugar

12

9,266

25.4

Blood pressure
* Responding States only.

38

12,310

99.5

5
Only 25 percent, or 119,267, of the approximately
470,000 annual intakes into these 39 prison
systems are screened for diabetes using fasting
blood sugar; more than 99 percent have their
blood pressures measured at intake. No information was collected on how the results of screening
tests were treated. It is not known what is done
when an inmate coming into the system has a
fasting blood sugar greater than 110 mg/dL,
which constitutes glucose intolerance according
to the most recent guidelines of the National
Institutes of Health (NIH), or 126 mg/dL, which
constitutes diabetes according to the most recent
NIH guidelines.8 Similarly, although almost every
new inmate has his or her blood pressure taken,
no data were collected on whether the screening
procedures conform to NIH standards or whether
the diagnostic or treatment guidelines published
by the Joint National Committee (JNC–VI)9 were
followed.

Prevalence of Chronic Diseases
Nineteen States reported that they had data on the
number of inmates in their system with chronic
diseases. These States tend to be smaller in terms
of average, daily population than those that did
not have data on chronic disease prevalence
(mean ADP 14,103 vs. 23,076). At the same time,
these States had a larger mean annual intake
(11,264 vs. 7,945) and larger mean annual
releases (10,339 vs. 7,510).
Although these 19 States claimed to have data on
the prevalence of chronic diseases in their prison
systems, when asked to report either the number
or percentage of inmates in their systems with

asthma, diabetes, hypertension, and heart disease,
not all of them could provide numbers or percentages for each condition. When the prevalence
of chronic diseases were expressed as rates per
1,000 inmates, rates varied as much as threefold.
The prevalence of asthma among 17 responding
States ranged from 2.5 percent (25/1000) to 7.2
percent (72/1000; mean: 4.8 percent); the prevalence of diabetes in 18 State systems ranged from
1.9 percent (19/1000) to 2.8 percent (28/1000;
mean 2.35 percent). The prevalence rates for
hypertension in 15 State systems reporting ranged
from 1.3 percent (13/1000) to 7.8 percent
(78/1000; mean 4.5 percent). The prevalence rates
for heart disease in 15 State systems reporting
ranged from 1.5 percent (15/1000) to 2.8 percent
(28/1000; mean 2.1 percent).
Table 3 shows the crude prevalence rates for
asthma, diabetes, hypertension, and heart disease
per 100 inmate population calculated from survey
forms completed by the States.10 For comparison
purposes, table 3 also shows rates calculated from
the National Health and Nutrition Examination
Survey (NHANES–III; 1988–94).11 NHANES–III
is a multistage probability sample of the noninstitutionalized U.S. population. Prevalence rates
also were calculated for a subsample of the
NHANES respondents selected to reflect low
socioeconomic status. The individuals in this
subsample had received food stamps, welfare
assistance, or other public assistance within the
previous year. This subsample represents a
population of approximately 66 million and
reflects the lowest quartile of socioeconomic
status in the United States.12

Table 3. Prevalence of Chronic Diseases in Prisons From the Survey of State Prison Facilities and
the U.S. Population Estimated From the National Health and Nutrition Examination Survey (NHANES–III)
Disease
Asthma

4.8b

7.7

8.4

Diabetes

2.3

5.3

7.3

Hypertension

4.5

23.1

28.5

3.4

5.3

Heart disease
2.1
Self-report data: “Have you ever been told that you have . . . ?”
b
All rates are per 100.
a

NHANES–III
(All U.S.)

NHANES–IIIa
(Lowest SES)

NIJ–NCCHC
State Prison Survey

6

The rates in table 3 are crude rates per 100
population. Comparing estimated prevalence
between the prison population and the general
population (i.e., NHANES) can be misleading
because of differences in the demographic
profiles and other characteristics that may make
one group more or less susceptible to disease
than another. For example, the prevalence of
hypertension increases with age. Thus, the crude
prevalence of hypertension is expected to be
lower in the prison population because it is
disproportionately younger than the general
population. Diabetes tends to be more prevalent
among women than men. Therefore, it could be
expected to be less prevalent in the prison
population than the general population because
of a lower percentage of women in the prison
population.

diseases are significantly undetected and underdiagnosed in prison health care systems or that
prison systems have poor quality data on the
prevalence of chronic disease in their populations.

The prevalence of asthma, diabetes, hypertension,
and heart disease in the prison population as
reported by the States responding to the survey
are low relative to the rates in the general U.S.
population. These lower prevalence rates are
unlikely to be “explained away” by age, race, or
gender differences in the respective populations.
In the case of hypertension, where more than 99
percent of inmates have blood pressures taken
upon entering the system, the estimate that 4.5
percent of the inmates are hypertensive is significantly lower than the rate of self-reported
hypertension in the general U.S. population.
Moreover, it is only one-fifth the rate of hypertension in a similar socioeconomic group in the
community, who are least likely to have their
blood pressures checked frequently. The survey
data raise the suspicion either that chronic

About two-thirds of the responding prison
systems reported systemwide protocols for
treating asthma. These 26 prison systems house
approximately 84 percent of inmates and account
for 78 percent of annual releases among responding States. Fewer than 70 percent of inmates
and annual releases are from prisons with systemwide protocols for treating heart disease. Despite
numerous guidelines for treating diabetes and
hypertension, only about 73 percent of inmates
and releases are from systems with protocols for
treating diabetes, and 80 percent of inmates and
77 percent of releases are from systems with
protocols for treating hypertension.

Treatment Protocols
The next section of the survey inquired about
systemwide clinical protocols or treatment guidelines for the management of the target chronic
diseases. Table 4 shows that the number of States
with systemwide treatment protocols varies.
Twenty States have protocols for treating heart
disease; 26 States have protocols for treating
asthma. States with systemwide protocols for
treating or managing diseases tended to be those
with the largest ADP and the most annual
releases.

The implications of this sporadic use of systemwide treatment protocols are unclear. On the one
hand, one could expect a higher quality of care to

Table 4. Systemwide Treatment Protocols for Chronic Diseases:
Average Daily Population and Mean Total Annual Releases
Average Daily Population

Total Annual Releases

Mean ADP

Mean TAR

N

%

N

%

Asthma (n = 26)

26,627

13,706

692,295

84.2

338,695

78.4

Diabetes (n = 24)

25,287

13,195

606,878

73.8

316,686

73.3

Hypertension (n = 25)

26,421

13,453

660,520

80.3

336,320

77.8

Heart disease (n = 20)

26,597

14,654

566,103

68.9

307,731

68.9

Disease

7
be provided when established treatment protocols
(such as that advocated for hypertension by the
JNC–VI or for diabetes by NIH or the American
Diabetes Association) are in place systemwide.
On the other hand, treatment guidelines that are
not adhered to may lead to poorer quality of care
than when accepted standards are followed in the
absence of systemwide treatment protocols.

Medication Use
The survey asked whether pharmacy data for the
prison system were computerized. Thirty-one
States responded that they had a computerized
pharmacy system. These systems have an ADP of
708,835 (86.2 percent of the ADP for the 41
responding States). Only 17 States, however,
indicated they could determine the number of
inmates taking selected medications. Even fewer
gave the number of inmates taking inhaled asthma
medications, insulin or oral hypoglycemic agents,
or antihypertension medicines. Fewer yet could
state the number of inmates taking medications
prescribed for heart disease (e.g., anti-ischemic
and antiarrhythmic agents). Table 5 presents the
available data on the number and percentage of
inmates in the States reporting this information
who are taking these medications.

Discharge Planning
Discharge planning facilitates an inmate’s
transition into the community. In the case of
health care, discharge planning means that
arrangements are made for inmates to have a
“point of care” to receive needed medical
attention for their condition when they are
released into the community. Sixteen States

indicated they had policies and procedures for
discharge planning for inmates with chronic
diseases. These State systems housed 60.8 percent of the total inmate population and released
278,548 inmates into the community in their most
recent accounting period. Twenty-nine States,
accounting for 84.2 percent of total annual
releases, indicated that inmates with chronic
medical conditions were given a supply of
medication when they were released. At least
35 percent of inmates (approximately 150,000)
are released each year without the benefits of a
system of discharge planning. More disturbing,
67,000 or more inmates with chronic medical
conditions are released each year without even a
supply of medication.

Recently Released Inmates
An important section of the survey queried
respondents about information they could provide
concerning inmates recently released from their
prison systems. Of the 41 States that responded,
30 indicated they could determine which inmates
had been released within the past 6 months. These
facilities released approximately 382,799 inmates
(88.6 percent of inmates released from all State
prisons) during the most recent period. Only 12
State systems indicated that they could provide
demographic data (e.g., age, race, and gender) on
their recently released inmates. These 12 systems
released 219,827 inmates in 1997 (50.1 percent of
those released by all State prisons). Moreover,
only 10 State systems, which released 94,531
inmates in 1997 (48.5 percent of those released by
all State prisons), said they could identify the age,
race, and gender of recently released inmates with
chronic diseases.

Table 5. Number and Percentage of Inmates Taking Selected Medications
Medication

# of Inmates

% ADP

Inhaled asthma medications

4,787

2.48

Insulin or oral hypoglemics

4,995

2.48

11,916

6.29

Anti-ischemic agents

2,782

1.85

Antiarrhythmic agents

1,162

0.61

Antihypertension agents

8

Table 6 lists these 10 State systems, the number of
inmates they released in 1996, and the number of
inmates reported to have asthma, diabetes, hypertension, and heart disease. Although these 10
States reported they could identify inmates with
chronic diseases released within the past 6
months, 3 States (North Dakota, Maryland and
Oklahoma) either could not or did not indicate the
prevalence of any of the target chronic diseases in
their current population of inmates. Three other
States (Illinois, Florida, and Utah) could provide
prevalence data on some, but not all, of the target
conditions.
The prevalence rates reported by Oregon and
Washington appear to be inconsistent. Both States
have an approximately equal number of annual
releases (5,608 vs. 5,545), yet Washington has
three or more times the number of inmates
diagnosed with asthma, diabetes, and hypertension and six times the number of inmates
diagnosed with heart disease.

Mental Health
The final section of the survey instrument
inquired about the prevalence of mental disorders
among inmates. Seventeen States with a total
ADP of 401,265 (48.8 percent of the ADP of all
responding State prisons), 170,263 annual intakes
(36.2 percent of annual intakes into State prisons
in responding States), and 161,554 annual
releases (37.4 percent of annual releases from
State prisons in responding States) reported that
they designate one or more facilities for housing
inmates receiving treatment for mental disorders.
Twenty-one State systems housing 544,926
inmates (66.3 percent of the ADP of all responding States), 306,385 admissions (65.6
percent of annual intakes into State prisons in
responding States), and 283,450 annual releases
(65.6 percent of annual releases from State
prisons in responding States) claimed they
maintained data on the number of inmates with
mental disorders by diagnoses. Fourteen systems

Table 6. States Reporting They Have Chronic Disease Data by
Demographic Characteristics of Recently Released Inmates
# of Inmates
State
Arkansas

Total Annual
Releases
4,977

Facilities

Asthma

Diabetes
Mellitus

18

315

146

Hypertension
642

Heart
Disease
128

Florida*

23,866

60

33,829

1,276

—

—

Illinois

25,124

32

2,962

729

—

—

3,845

8

172

114

271

58

12,000

26

—

—

—

—

520

7

—

—

—

—

Oklahoma

6,582

42

—

—

—

—

Oregon

5,608

12

156

115

284

94

Utah

1,464

2

250

123

318

—

Iowa
Maryland
North Dakota

Washington
5,545
12
570
391
1,259
* Computed from the percentage of inmates with the diagnosis and the average daily population of inmates.

577

9
with 268,741 inmates (32.7 percent of the ADP
of all responding States), 130,573 admissions
(27.8 percent of annual intakes into State prisons
in responding States), and 124,186 annual
releases (28.7 percent of annual releases from
State prisons in responding States) classify
diagnosed mental disorders according to the
DSM–IV criteria for Axes 1, 2, and 3.

Table 8 shows the number of States that could
identify inmates with mental conditions according
to demographic characteristics and the total ADP
of these State prison systems. Fourteen States
indicated that they could identify the age, race,
and gender of recently released inmates with
mental disorders, but only 12 States said they had
data on race and 13 said they had data on the
gender of the inmates. This incongruity raises
questions about the validity of the reported data.

Few States reported on the number of inmates
within their systems with selected mental
diagnoses. Table 7 presents the number of
responding prison systems and reported
prevalence rates for selected mental conditions.
All reported prevalence rates are low, ranging
from about 3 inmates per 1,000 with panic
disorder to 18 per 1,000 with schizophrenia.

When asked if they had treatment protocols or
guidelines for the management of inmates with
mental disorders, 15 States responded “yes” and
12 said “no”; the balance did not complete this
question. The total ADP of the 15 States with
treatment protocols is 317,511 (mean daily
population = 21,167), which is larger than the
ADP for those responding that they did not have
protocols for managing inmates with mental
disorders (mean = 13,104).

Information also was sought on the number of
inmates with mental disorders who had cooccurring alcohol dependency and other
substance dependency disorders. Only four
responses to these questions were received and
the accuracy of the data was highly suspect.

Table 7. Reported Rates of Selected Mental Disorders
Mental Disorder

# of States

Prevalence per 100 Inmates

Schizophrenia

7

1.81

Affective disorder

6

0.54

Psychotic disorder

6

0.36

Major depression

7

1.72

Bipolar disorder

7

0.67

Dysthymic disorder

8

0.41

Panic disorder

4

0.30

Post-traumatic stress disorder

6

0.33

Delusions, dementia, amnestic cognitive
disorder, and organic brain syndrome

5

0.80

Table 8. Number and Average Daily Population of States Able to Identify
Recently Released Inmates With Mental Disorders
Characteristics

# of States

Total ADP

Age

14

230,314

Gender

13

308,062

Race

12

271,262

Age/gender/race

14

454,084

10
Policies covering discharge planning for inmates
with mental disorders are in effect in 7 States with
a mean ADP of 24,368. These States house more
than 414,000 inmates and release a total of
185,337 inmates each year. Nine States that
release a total of 47,330 inmates each year
responded that they had no policies or procedures
for the discharge planning of inmates with mental
disorders. About one-half of the responding States
left this question blank.
Twenty-three States with total annual releases of
228,646 inmates provide medication to inmates
with mental disorders when they are released into
the community. Only three States responded that
it was not their policy to give inmates with mental
disorders a supply of medication on release.
States’ capability to identify inmates with mental
disorders after they are released into the community is limited. Fifteen States with 113,122 total
annual releases indicated they could identify
inmates with mental disorders released within the
past 3 months. Fourteen States with 108,381 total
annual releases could identify inmates with mental
disorders released within the past 6 months. Nine
States with 86,595 total annual releases could
identify inmates with mental disorders released
into the community within the past year.

Conclusions
State prison systems were surveyed to collect
information on the prevalence of selected chronic
medical conditions—asthma, diabetes, hypertension, and heart disease—and mental disorders in
the inmate population, and to learn their policies
and procedures for discharge planning and
providing medications to inmates when they are
released into the community. Information was
also sought on whether inmates with chronic
medical conditions or mental disorders who were
released into the community in the past 3, 6, and
12 months could be identified.
The responses received from 41 States were of
limited value. Ten States and the Federal Bureau
of Prisons did not respond to the survey despite
repeated requests from NCCHC and the study
organizers. In a study of sexually transmitted

diseases, the Centers for Disease Control and
Prevention (CDC) were able to obtain a better
response rate, but only by sending a CDC representative to the jails to assist correctional
personnel in collecting and recording the requested
data.13 In this survey, the 10 nonresponding States
house approximately 200,000 inmates, which is a
significant percentage of the prison population.
Moreover, several of the States that returned their
questionnaires provided little usable data. Either
questions were not answered or some answers that
were provided were clearly erroneous. Missing or
erroneous data, particularly in the section of the
questionnaire related to mental health, seriously
weaken the conclusions that can be reached.
Although the researchers did not learn much of
what they wanted to, much was learned about the
state of prison health. Many State prison systems
cannot report detailed, accurate data on the prevalence of medical problems or mental disorders
within their inmate populations. It would appear
that State systems have not integrated their inmate
databases. Administrative databases that contain
information on the demographic profile of the
inmate population are not “connected” to databases that contain medical data on diagnosed
conditions or medication usage from the pharmacy.
Concerns regarding confidentiality of inmates’
health conditions undoubtedly contribute to the
lack of linkage between these databases.

Notes
1. Bureau of Justice Statistics, Correctional
Populations in the United States, 1995, Washington,
DC: U.S. Department of Justice, Bureau of Justice
Statistics, 1997, NCJ 163916.
2. Estelle v. Gamble, 429 U.S. 97 (1976).
3. Bureau of Justice Statistics, Correctional
Populations in the United States, 1995 (see note 1).
4. Bureau of Justice Statistics, Correctional
Populations in the United States, 1996, Washington,
DC: U.S. Department of Justice, Bureau of Justice
Statistics, 1999, NCJ 170013.
5. Hammett, T.M., R. Widom, J. Epstein, M. Gross,
S. Sifre, and T. Enos, HIV/AIDS and STDs in Correctional Facilities: 1994 Update, Washington, DC: U.S.

11
Department of Justice, National Institute of Justice;
and U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention, National
Center for HIV, STD, and TB Prevention, 1995, NCJ
156832.
6. The Federal Bureau of Prisons did not respond to
the survey despite repeated requests. Further, for
simplicity, the District of Columbia is included as
a State.
7. Bureau of Justice Statistics, Correctional Populations in the United States, 1997, Washington, DC:
U.S. Department of Justice, Bureau of Justice
Statistics, 2000, NCJ 177613.
8. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus, “Report of the Expert
Committee on the Diagnosis and Classification of
Diabetes Mellitus,” Diabetes Care 20(7)(1997):
1183–97.
9. Joint National Committee on Prevention, Detection,
Evaluation, and Treatment of High Blood Pressure,
The Sixth Report of the Joint National Committee on
Prevention, Detection, Evaluation, and Treatment of
High Blood Pressure, Bethesda, MD: National

Institutes of Health, National Heart, Lung and Blood
Institute, 1998, NIH publication No. 98–4080.
10. Some States provided frequency counts, while
others responded in terms of percentages of inmates.
All frequency counts were converted to percentages
based upon the average daily population of the system.
11. National Center for Health Statistics, National
Health and Nutrition Examination Survey III
[NHANES–III], Washington, DC: U.S. Department
of Health and Human Services, Centers for Disease
Control and Prevention, 1997.
12. Hornung, C.A., R.B. Greifinger, and S. Gadre,
“A Projection Model of the Prevalence of Selected
Chronic Diseases in the Inmate Population,” paper
prepared for the National Commission on Correctional
Health Care, Chicago, Illinois, n.d. (Copy in this
volume.)
13. National Center for HIV, STD, and TB Prevention,
Division of STD Prevention, Sexually Transmitted
Disease Surveillance, 1998, Atlanta, GA: U.S. Department of Health and Human Services, Centers for
Disease Control and Prevention, September 1999.

13

The Burden of Infectious Disease
Among Inmates and Releasees From
Correctional Facilities
Theodore M. Hammett, Ph.D., Patricia Harmon, and William Rhodes, Ph.D., Abt Associates Inc.

Introduction
It is widely believed that infectious diseases—
particularly human immunodeficiency virus and
acquired immunodeficiency syndrome (HIV/
AIDS), sexually transmitted diseases (STDs),
hepatitis, and tuberculosis (TB)—are much more
prevalent among correctional inmates than in the
total population and that, therefore, a disproportionate share of the burden of infectious disease is
found among people who pass through correctional facilities. Largely because of the public
health implications of potential transmission of
disease from inmates to persons outside prison,
there is growing recognition of the importance of
improving prevention and treatment interventions
in correctional settings. A number of authors have
advocated strongly for taking better advantage of
this important “public health opportunity.”1
Prevention and treatment programs for infectious
disease in prisons and jails have improved in
recent years, but there continues to be a general
lack of public and political recognition of the
importance of correctional settings for health
interventions. Thus, the opportunity has yet to be
fully exploited.
There is a potentially important two-part strategy
for increasing the recognition of the public health
problem and opportunity represented by infectious
disease in correctional populations and for
improving the policy response. It is to develop
and disseminate (1) quantitative estimates of the
burden of infectious disease among inmates and
releasees and (2) quantitative analyses of the costs

and benefits of prevention, early identification,
and treatment of infectious disease among
inmates. Neither of these estimates or analyses
has been done systematically.
This paper addresses the first part of the strategy.
Comparisons of the prevalence of HIV disease in
correctional populations to that in the total
population have been done,2 but, to date, no one
has sought to estimate the number of persons with
infectious disease in all types of correctional
facilities, the numbers of inmates with infectious
disease who are being released to the community,
or the proportion of the burden of infectious
disease found among people who serve time in
correctional facilities.
This paper presents national estimates of inmates
and releasees with HIV infection and AIDS;
syphilis, gonorrhea, and chlamydia infection;
hepatitis B and C infection; and TB infection and
TB disease. These figures should be considered
rough estimates of the burden of infectious
disease in correctional populations. It is impossible to present precise statistics because of the lack
of systematic surveillance and the resulting paucity of observations on which prevalence estimates
for many of the conditions of interest must be
based. Moreover, as discussed in greater detail
below, the estimates presented in this paper
reflect some double counting between prison and
jail populations, inmates and releasees, and jail
releasees during a given year. The extent of this
duplication cannot be quantified precisely, but it
should be considered in using the estimates.

14

Prevalence and Incidence
Before proceeding to a discussion of data sources
and estimation methods and presentation of the
estimates, it is important to clarify the use of
several key epidemiologic terms in this paper.
The estimates and analyses presented here are
based on point prevalence or period prevalence
measures, meaning the percentage of a given
population with a condition either at a particular
point in time (e.g., at year-end) or over a period
of time (e.g., over a 1-year screening period).
Measures of prevalence should not be confused
with incidence rates, which are intended to
represent the risk of development of a condition
within a susceptible population, for example, in
terms of numbers of new cases per 1,000 or
100,000 individuals during 1 year. A susceptible
population generally means those without the
condition at the beginning of the period in which
incidence is being measured.3 Prevalence estimates
are easier to calculate than incidence rates based
on the available data for correctional populations,
and they are more policy relevant in this context.
In this paper, the estimates of inmates with AIDS,
HIV infection, and TB disease are based on point
prevalence data. The estimates of inmates infected
with syphilis, chlamydia, gonorrhea, TB, hepatitis
B, and hepatitis C are based on period prevalence
data. All estimates for releasees are also, in effect,
period prevalence estimates that reflect the number of persons with certain infections or diseases
who are released to the community during a given
year.

Estimates of Numbers of Inmates and
Releasees From Correctional Facilities
To estimate the burden of infectious disease
among persons passing through correctional
facilities, one must know the numbers of inmates
and persons being released. The U.S. Department
of Justice, Bureau of Justice Statistics (BJS),
gathers and publishes statistics on numbers of
prison and jail inmates and persons being released
from prisons. The statistics on prisoners come
from BJS’s National Prisoner Statistics.4 Statistics
on jail populations come from BJS’s Census of
Jails conducted every 5 years and, in each

intervening year, a sample-based Prison and Jail
Inmates at Midyear 1997.5 BJS’s midyear 1997
inmate population statistics and data on 1996
releases (the latest available) were used because
these reflect the situation closest to the date on
which correctional systems provided data on HIV
and AIDS to BJS’s Survey of Inmates in State and
Federal Correctional Facilities6 and on STDs and
TB to the NIJ/CDC Ninth National Survey of
HIV/AIDS, STDs, and TB in Correctional Facilities,7 on which many of the estimates are based.
This approach requires an estimate of the number
of unique individuals released from jails and
prisons during a specified year. Although BJS
data report the number of releases from jails and
prisons, they do not tell us the number of unique
individuals. It is common for someone to be
arrested and released more than once during a
given year. Therefore, BJS data must be adjusted
to provide an estimate of the number of releasees.
The National Institute of Justice (NIJ) provided
Drug Use Forecasting (DUF, since renamed the
Arrestee Drug Abuse Monitoring [ADAM]
program) data from five sites. These data reported
the number of times that an arrestee had been
booked during the year just before the arrest that
caused his or her inclusion in the DUF sample.
Data were based on self-reports. Reasoning that
arrests are generated by a Poisson process with
unmeasured heterogeneity, those data were used
to estimate that arrestees who admitted using
cocaine or heroin weekly were arrested about
0.38 times per year while at liberty. These estimates were for weekly drug users because they
are probably at greatest risk for the conditions of
interest for this analysis. This estimate suggests
that if A represents the number of arrests during a
given year, then A/1.38 estimates the number of
unique individuals who are arrested during the
year.
Applying the factor of 1.38 will probably underestimate unique releasees because many of those
at risk of arrest are not at liberty for the entire
year. Because they are sometimes incarcerated,
weekly drug users probably generate fewer than
0.38 arrests per year, so the estimate of the
number of unique individuals booked into and

15
released from local jails is probably too small. On
the other hand, people who are booked into and
released from jail cannot be distinguished from
those who are sentenced to jail. When the two
populations are added up, some minor double
counting results,8 because most people serving jail
terms must have been booked before being
convicted. Dividing by 1.38 does not overcome
that double counting. On balance, the convention
of dividing BJS’s figure for total number of jail
releases by 1.38 probably provides an estimate of
unique individuals that is close enough to reality
for present purposes. Relying on this logic, BJS’s
estimate of 10 million jail releases was divided by
1.38 to yield an estimate of 7,246,377 individuals
who were released from city and county jails
during 1996.
The estimates also rely on the number of individuals who are released from State and Federal
prisons, which BJS reports to have been 504,289
in 1996.9 Because people typically spend 1 year
or more in prison, the prison population is less
likely to overlap the jail population. There may
be some overlap because many people enter
prison following parole violations. These people
were probably arrested before being returned to
prison, so there is some degree of overlap between jail releasees and prison releasees. This
overlap is probably small, because persons
returned to prison following a parole revocation
typically serve long terms. A more troubling
problem is that parole authorities often use short
jail terms in lieu of longer prison terms as a
response to technical parole violations. Use of
jails for this purpose would certainly result in
double counting, but it appears that parole violations account for less than 3 percent of the jail
population, so the double counting cannot be
severe.10
A count of prison releasees includes some
duplicate counting because some prisoners are
released on parole, have their releases revoked,
and then are released again after serving the time
attributed to their revocation. Again, because
revocations usually result in lengthy prison stays,
double counting of prison releasees is negligible.
Therefore, BJS’s figure for prison releasees has
been used.

Overall Approach to Estimating the
Burden of Infectious Disease
To estimate the number of unique individuals
with condition D who pass through jails and
prisons, a formula was applied:
ND = 7,246,377 PJ + 504,289 PP
Where:
ND =
PJ =
PP =

the number of unique individuals with
condition D who pass through jails and
prisons
the proportion of people in jail with
condition D
the proportion of people in prison with
condition D

Much of the rest of this paper discusses how PJ
and PP were estimated.
Because of the paucity of data on which some
of the estimates are based, their precision is
questionable. The gross accuracy of the estimates
can be checked on the basis of the epidemiology
of the conditions under study. This method is
described below and used to evaluate the estimates presented later in the paper.
Assume that a total of TD people in the U.S.
population have condition D. Assume, furthermore, that condition D always results from
injection drug use and never from any other
cause. Finally, assume that injection drug users
(IDUs) have a 0.32 probability of being released
from jail or prison during any given year.11 Then,
ND/TD = 0.32
This is to say that 0.32 is the approximate upper
limit to the ratio of people with condition D who
are released from any jail or prison during a
specified year to all people in the U.S. population
with condition D.
If condition D sometimes results from injection
drug use but frequently results from behaviors

16
that do not put people at high risk of arrest, then
the equality does not hold, and instead:
ND/TD # 0.32.
Some concrete illustrations may help make the
case. Injection drug use appears to be the major
transmission factor for hepatitis C virus (HCV)
infection. The equality would apply, so one would
expect about 32 percent of all persons with HCV
infection to be released from jail or prison during
any given year.
In contrast, IDUs account for about 24 percent of
current AIDS cases.12 Thus, the ratio of ND/TD
would be somewhat greater than 0.32 × 0.24, or
0.08, because there are other important risk
factors for HIV infection, and persons with
histories of some of these risk behaviors are
overrepresented in correctional populations.
Using similar reasoning, those released from
prison should account for considerably less than
32 percent of the national burden of other
diseases that are transmitted primarily through
needle use.

HIV Infection and AIDS
Data sources and limitations
The best sources for statistics on the prevalence
of HIV disease in prison and jail populations are
the surveys conducted by BJS. Using its annual
Survey of State and Federal Correctional Facilities, BJS compiles statistics on numbers of
inmates with HIV infection and confirmed AIDS
at year-end. BJS first compiled and presented
these statistics for 1991.13 The series has been
continued annually since then.14 BJS also conducts
a Census of Jails every 5 years and an annual
sample-based Survey of Inmates in Local Jails,
from which it develops estimates of the number
of jail inmates with HIV infection and the number
and proportion of jail inmate deaths due to
HIV/AIDS.
The BJS surveys should provide fairly accurate
counts of State and Federal inmates with AIDS,
assuming that the correctional systems gather
and report the statistics accurately. Unfortunately,
BJS has no control over the accuracy of the
correctional systems’ reporting, and it is hard to

evaluate that reporting systematically for
adjustment or estimation purposes. The BJS
statistics have a major limitation with regard to
prevalence rates and numbers of inmates with
HIV infection in both State and Federal and city
and county systems. This limitation makes it
necessary to adjust BJS’s figures. BJS compiles
its statistics on HIV infection from State and
Federal prison systems that have different HIV
testing policies. Only 16 State correctional
systems had mandatory HIV testing of all new
inmates in 1997. Most prison systems have
voluntary or on-request HIV testing, the aggregate
results of which almost certainly underestimate
true HIV seroprevalence because some HIVinfected inmates will not accept voluntary
testing.15 The problem is even more pervasive
with regard to HIV prevalence among jail
inmates, because no major jail systems have
mandatory testing.

Estimates and estimation methods
A national point prevalence estimate of inmates
with confirmed AIDS and a period prevalence
estimate of releasees with confirmed AIDS are
presented in table 1, broken down by prison and
jail systems. These estimates combine men and
women. Regional estimates are provided for State
prison systems. The most recent BJS prevalence
percentage for State and Federal prison inmates
with AIDS was 0.5 percent at year-end 1996.
Several systems did not respond to the 1996 BJS
survey, so the national and regional prevalence
percentages were applied to the total inmate
populations at midyear 1997 to obtain the national
and regional estimates. It is estimated that more
than 6,000 State and Federal prison inmates had
AIDS in 1997. Because the national prevalence
of AIDS among State and Federal inmates has
remained steady at 0.5 percent since 1993,16 it
seems reasonable to apply the 1996 prevalence
percentage forward 1 year to obtain the AIDS
prevalence estimate for 1997. The national
prevalence estimate of 0.5 percent for State and
Federal inmates in 1996 was applied to the total
jail population in 1997 to develop a national
estimate of more than 2,800 jail inmates with
AIDS in 1997. The national estimate for prison
and jail inmates with AIDS in 1997 is more than
8,900, representing 4 percent of the almost

17
Table 1. National and Regional Estimates of Inmates and Releasees with AIDS
Est. % w/
AIDS, 1996a

Population,
1997b

0.5

1,218,256

Federal Bureau of
Prisons (FBOP)

0.4

States: Northeast
States: Midwest

Category
State/Federal
Prison Systemsd

States: South
States: West
City/County
Jail Systems

d

Est. Inmates
w/AIDS, 1997

Releasees,
1996c

Est. Releasees
w/AIDS, 1996

6,091

504,289

2,521

110,160

441

24,945

100

1.3

167,706

2,180

61,293

797

0.3

212,779

638

93,243

280

0.5

484,391

2,422

175,695

878

0.3

243,220

730

149,112

447

0.5

567,079

2,835

7,246,337e

36,232

Total
0.5
1,785,335
8,926
7,750,666
38,753
Bureau of Justice Statistics, Survey of State and Federal Correctional Facilities, 1996.
b
Gilliard, D.K., and A.J. Beck, Prison and Jail Inmates at Midyear 1997. Bureau of Justice Statistics Bulletin. Washington, DC:
U.S. Department of Justice, Bureau of Justice Statistics, January 1998, NCJ 167247.
c
Bureau of Justice Statistics, Correctional Populations in the United States, 1996. Washington, DC: U.S. Department of Justice,
Bureau of Justice Statistics, 1999, NCJ 170013.
d
Includes District of Columbia.
e
BJS estimate of 10,000,000 jail releasees divided by 1.38. See text for discussion of method.
a

229,000 people living with AIDS in the total U.S.
population at the end of 1997.17 The 0.5 percent
prevalence of AIDS among inmates is more than
five times the estimated prevalence of 0.09
percent in the total U.S. population.
To estimate the number of people with AIDS
released from State and Federal prison systems,
the same 0.5 percent prevalence was applied to
the total number of releasees from State and
Federal prisons in 1996, the most recent available
statistics. The national estimate is more than
2,500 State and Federal prison releasees with
AIDS in 1996. To estimate the number of people
with AIDS released from city and county jails, the
same 0.5 percent prevalence was applied to the
estimate of unduplicated jail releasees derived as
described above. It is estimated that more than
36,000 jail releasees had AIDS in 1996. The
estimated total of prison and jail releasees with
AIDS in 1996 is almost 39,000. Seventeen
percent of the estimated 229,000 persons living
with AIDS in the United States in 199618 passed
through a correctional facility that year. This ratio
is in line with the checking methodology outlined
above.

Estimating the number of inmates with HIV
infection was more complicated because of
variable testing policies. Because of the uncertainties involved, an estimated range based on
a range of possible point prevalence rates is
presented. These point prevalence estimates are
shown in table 2, again broken down by prisons
and jails but combined for men and women.
Numerous studies have shown that HIV seroprevalence rates for inmates tend to be higher
among women than among men. The estimates
reflect all HIV-infected inmates, including those
with AIDS.
The lower bound of the estimate is based on
applying BJS’s 2.3-percent national HIV
prevalence among State and Federal prison
inmates in 1996 to the national total of State and
Federal inmates, and BJS’s regional prevalence
rates to the regional totals of State inmates. The
same was done to obtain the lower bound of State
and Federal releasees with HIV infection.

18
Table 2. National and Regional Estimates of Inmates and Releasees with HIV Infection

Category
State/Federal
Prison Systemsa

Est. % HIV+,
1996 (Range)

Population,
1997

Est. HIV+
Inmates, 1997
(Range)

Releasees,
1996

Est. HIV+
Releasees,
1996 (Range)

2.3b–2.98

1,218,256

28,020–36,304d

504,289

11,599–15,028d

FBOP

1.0–1.5

110,160

1,102–1,652

24,945

249–374

States: Northeast

7.5–7.85

167,706

12,577–13,165

61,293

4,597–4,812

States: Midwest

1.0–1.26

212,779

2,128–2,681

93,243

932–1,175

1.9–2.93

484,391

9,203–14,193

175,695

3,338–5,148

0.8–1.88

243,220

1,946–4,573

149,112

1,193–2,803

1.2c–1.8

567,079

6,805–10,207

7,246,377

86,956–130,435

7,750,666

98,555–145,463

States: South
States: West
City/County
Jail Systems

a

Total
1,785,335
34,825–46,511
Includes District of Columbia.
b
Bureau of Justice Statistics, Survey of State and Federal Correctional Facilities, 1996.
c
Bureau of Justice Statistics, 1996 Survey of Inmates in Local Jails.
d
Regional estimates do not add to these totals due to rounding.
a

The upper bound was obtained by adjusting
upward the aggregate HIV seropositivity rates
reported to the BJS survey by the Federal prison
system, which does not mandatorily test at intake,
and by all but four of the States with voluntary
testing. All of these adjustments are shown in
table 3. The four voluntary testing States whose
BJS figures were not adjusted were New York
and Connecticut, whose reported seropositivity
rates were very close to those found in blinded
seroprevalence studies, and Oregon and Wisconsin, where comparative studies showed that seropositivity in voluntary testing was very similar to
seroprevalence in blinded intake studies.19
For the other States and the Federal Bureau of
Prisons, it was decided to increase the HIV
seropositivity rate reported to BJS by 50 percent
or by a specific adjustment factor for that system,
if available. The adjustment factor was based on
comparisons between seropositivity rates found in
voluntary testing versus blinded seroprevalence
studies. In high-prevalence States such as New
York, Maryland, and California, rates from
blinded studies were 2–3 times higher than in
voluntary testing. In States such as Oregon and
Wisconsin, by contrast, rates were similar. The
extent of the discrepancy depends on the system’s
policy in encouraging inmates to be tested voluntarily and the receptivity of the inmates to being

tested. Some inmates may be in denial or may
fear discrimination, mistreatment, or breach of
confidentiality. These conditions vary across
and within systems. Therefore, 50 percent was
considered a conservative upward adjustment for
States without available comparisons of voluntary
versus mandatory testing or blinded studies.
For the small number of systems that did not
report HIV seropositivity statistics to BJS, BJS’s
seropositivity rate for the State’s region was used
if the State had mandatory testing or the regional
rate was adjusted upward by 50 percent if the
State had voluntary testing. Applying the estimated national prevalence range of 2.3–2.98
percent, which is 8–10 times the prevalence in the
total U.S. population, it is estimated that between
28,000 and 36,000 State and Federal inmates had
HIV infection in 1997 (table 2).
Because no major jail systems have mandatory
HIV testing, the BJS prevalence estimate of 1.2
percent for jail inmates was used as the lower
bound. This rate was adjusted upward by 50
percent to 1.8 percent to obtain the upper bound.
This estimated national range is much lower than
rates found in studies of certain large jail systems,
notably New York City’s, but is still 4–6 times
the estimated prevalence of HIV infection in the
total U.S. population.

19
Table 3. Derivation of HIV Prevalence Estimates for State and Federal Prison Systems
Jurisdiction

HIV Testing
Policy

% HIV+
1996 (BJS)

% HIV+
(Adjusted)

Population
1997

Est. HIV+ Inmates
1997 (Range)

7.5

7.85

167,706

12,577–13,165i

voluntary

4.6

4.6a

15,608

718–718

Maine

voluntary

0.3

0.45

1,559

5–7

Massachusetts

voluntary

3.6

5.0b

11,907

429–595

New Hampshire

Northeast
Connecticut

mandatory

0.9

0.9

2,153

19–19

New Jersey

voluntary

3.0

4.5

27,766

833–1,249

New York

voluntary

13.6

13.6c

69,530

9,456–9,456

Pennsylvania

voluntary

1.9

2.85

34,703

659–989

Rhode Island

mandatory

3.9

3.9

3,293

128–128

Vermont

voluntary

0.3

0.45

1,187

1.0

1.26

212,779

2,128–2,681i

voluntary

1.6

2.4

40,425

647–970

voluntary

d

—

1.5

17,549

?–263

mandatory

0.4

0.4

6,636

27–27

Midwest
Illinois
Indiana
Iowa
Kansas
Michigan
Minnesota

4–5

voluntary

0.2

0.3

7,790

16–23

mandatory

1.2

1.2

43,784

525–525

voluntary

0.5

0.75

5,348

27–40

Missouri

mandatory

0.9

0.9

23,687

213–213

Nebraska

mandatory

0.5

0.5

3,431

17–17

North Dakota

mandatory

0.4

0.4

Ohio

voluntary

0.7

1.05

47,248

331–496

South Dakota

voluntary

0.2

0.3

2,177

4–7

Wisconsin

voluntary

South

e

739

3–3

0.7

0.7

13,965

98–98

1.9

2.93

474,652

9,018–13,907i

Alabama

mandatory

1.1

1.1

22,076

243–243

Arkansas

voluntary

0.9

1.35

9,539

86–129

Delaware

voluntary

—

2.85

5,313

?–151

Florida

voluntary

3.4

5.1

64,713

2,220–3,300

Georgia

mandatory

2.3

2.3

36,329

836–836

Kentucky

voluntary

0.5

0.75

13,858

69–104

Louisiana

voluntary

2.0

3.0

28,382

568–851

Maryland

voluntary

3.8

11.4f

22,415

852–2,555

mandatory

1.3

1.3

14,639

190–190

voluntary

2.0

3.0

32,334

647–970

Oklahoma

mandatory

0.7

0.7

19,931

140–140

South Carolina

voluntaryg

2.1

3.15

21,021

441–662

Tennessee

voluntary

1.0

1.5

15,827

158–237

Texas

voluntary

1.4

2.1

136,599

1,912–2,869

Virginia

voluntary

1.5

2.25

28,673

430–645

West Virginia

voluntary

0.3

0.45

3,003

9–14

Mississippi
North Carolina

20
Table 3. Derivation of HIV Prevalence Estimates for State and Federal Prison Systems (continued)
Jurisdiction

HIV Testing Policy

% HIV+
1996 (BJS)

West

% HIV+
(Adjusted)

Population
1997

Est. HIV+ Inmates
1997 (Range)
1,946–4,573i

0.8

1.88

243,220

0.3

0.45

3,741

Alaska

voluntary

11–17

Arizona

voluntary

0.9

1.35

23,176

209–313

California

voluntary

0.8

2.4h

153,010

1,224–3,672

Colorado

mandatory

0.9

0.9

12,840

116–116

Hawaii

voluntary

0.7

1.05

4,491

31–47

Idaho

mandatory

0.5

0.5

4,105

21–21

Montana

voluntary

0.4

0.6

2,295

9–14

Nevada

mandatory

1.6

1.6

8,617

138–138

voluntary

0.2

0.3

4,692

9–14

New Mexico
Oregon
Utah
Washington
Wyoming
FBOP

e

voluntary

0.5

0.5

7,899

39–39

mandatory

0.7

0.7

4,154

29–29
102–153

voluntary

0.8

1.2

12,732

mandatory

0.3

0.3

1,468

voluntary

1.0

1.5

110,160

2.3

2.98

Total

4–4
1,102–1,652

a

The rate reported to BJS in 1993 was close to that found in an anonymous mail intake study in the same year and to seroprevalence estimates for women. Therefore, the BJS figure was not adjusted. See Altice, F.L., F. Mostashari, P.A. Selwyn, P.J.
Checko, R. Singh, S. Tanguay, and E.A. Blanchette, “Predictors of HIV Infection Among Newly Sentenced Male Prisoners,”
Journal of AIDS and Human Retrovirology 18(5)(1998): 444–453; and Mostashari, F., E. Riley, P.A. Selwyn, and F.L. Altice,
“Acceptance and Adherence with Antiretroviral Therapy Among HIV-Infected Women in a Correctional Facility,” Journal of
AIDS and Human Retrovirology 18(4)(1998): 341–348.
b
Blinded serosurveys, Mass. Department of Public Health, 1997.
c
Close to blinded study results so not adjusted.
d
Did not report to BJS Survey.
e
Studies have shown voluntary and blinded studies yield similar HIV+ rates so not adjusted.
f
Results of voluntary testing in 1991 reported to BJS—2.5% HIV+ versus results of blinded study in 1991—8.5% HIV+. (See
Harlow, C.W. HIV in U.S. Prisons and Jails. Bureau of Justice Statistics Special Report. Washington, DC: U.S. Department of
Justice, Bureau of Justice Statistics, September 1993, NCJ 143292; and Ruiz, J.D., and J. Mikanda, “Seroprevalence of HIV,
Hepatitis B, Hepatitis C, and Risk Behaviors Among Inmates Entering the California Correctional System,” California
Department of Health Services, Office of AIDS, HIV/AIDS Epidemiology Office, March 1996). Thus, the BJS figure was
inflated by 3.
g
Mandatory testing began in 1998.
h
Result of voluntary testing in 1994 as reported to BJS—0.8% HIV+ versus results of blinded study of incoming inmates in
1994—2.5% HIV+. (See Brien, P.M. and A.J. Beck, HIV in Prisons 1994. Washington DC: U.S. Department of Justice, Bureau
of Justice Statistics, 1996, NCJ 158020; and Ruiz, J.D., and J. Mikanda, “Seroprevalence of HIV, Hepatitis B, Hepatitis C, and
Risk Behaviors Among Inmates Entering the California Correctional System,” California Department of Health Services, Office
of AIDS, HIV/AIDS Epidemiology Office, March 1996). Thus the BJS reported rate was inflated by 3.
i
State estimates do not add to these totals due to rounding.

The HIV prevalence estimate for jails was also
compared to an estimate obtained by a different
method. The percentage of inmates with selfreported injection drug use in the past 6 months
(8.8 percent) in the 25 jail systems that participated in DUF over the period 1989–98 was
multiplied by the estimated national HIV seroprevalence of 14 percent among IDUs based on
analysis of data from 96 metropolitan areas in the

United States.20 This procedure yielded an estimate of 1.2 percent seroprevalence among jail
inmates, identical to the BJS estimate of HIV
seroprevalence among jail inmates nationwide.
Applying the range of 1.2–1.8 percent seroprevalence
to the total number of jail inmates in 1997 yields
an estimate of 6,800–10,200 jail inmates with
HIV infection. The total estimate of almost 35,000

21
to more than 46,500 prison and jail inmates with
HIV infection in 1997 represents 5–6 percent of
all people living with HIV in the U.S. population.
Estimates of the numbers of prison and jail
releasees with HIV infection (table 2) were
obtained by applying the above prevalence ranges
to the same population and release figures used
for the AIDS estimates. This produced an
estimate of between 98,000 and 145,000 people
with HIV infection released from U.S. prisons and
jails in 1996, including those with AIDS. Based
on this range, it is estimated that between 13.1
and 19.3 percent of the roughly 750,000 people
estimated by the Centers for Disease Control and
Prevention (CDC) to be living with HIV infection
in the United States in 1996 passed through a
correctional facility that year. This range of
percentages is within the parameters based on the
checking methodology presented above.

Sexually Transmitted Diseases:
Syphilis, Gonorrhea, and Chlamydia
Data sources and limitations
The sources for development of national estimates
of the prevalence of STDs among correctional
inmates are limited. The CDC’s national STD
surveillance program does not flag cases
identified in correctional facilities. There are a
few system-specific studies of syphilis and
chlamydia prevalence.21 CDC has recently
initiated a system for monitoring prevalence of
syphilis, gonorrhea, and chlamydia among jail
inmates in the United States. Some early data are
available from this system.22
The 1994 and 1997 national surveys of HIV/
AIDS, STDs, and TB in correctional facilities that
were sponsored by the CDC and NIJ sought data
on STD screening policies and on the numbers of
inmates who were screened and tested positive for
syphilis, gonorrhea, and chlamydia during the 12
months before completion of the survey. The most
useful data are the results of mandatory and
routine screening, which are most representative
of the total inmate population. Much data is
missing, however, reflecting that many systems
do not have mandatory or routine screening and
that many of those that do screen (especially for

syphilis) could not or would not report the results
to the survey. The combination of statistics from
the NIJ/CDC survey and the CDC STD Prevalence Monitoring Program provided enough
observations with acceptable diversity of size
and geographic location to produce supportable
national estimates, as described below.
The data used to develop these prevalence
estimates represent positive rapid plasma reagin
(RPR) serologies for syphilis and positive tests
for infection with gonorrhea and chlamydia. A
number of qualifications must be noted, especially
for the syphilis estimates, the first set of which
indicates that the estimates based on such testing
data may be overstated. The national incidence
of syphilis has declined substantially since 1997;
the disease is now concentrated in areas of the
Southeast and some large cities outside that
region. The sentinel surveillance jurisdictions in
the CDC’s STD monitoring program are heavily
weighted toward those where syphilis remains
more prevalent. More generally, the testing data
on which estimates are based do not necessarily
reflect active disease or infectiousness. The data
reflect a combination of testing methodologies
that may have different sensitivities. Data
reported to the NIJ/CDC surveys probably do
not represent confirmed positivity, and thus
include some number of biological false positives
for syphilis (which are associated with drug use or
pregnancy). The data from the CDC’s STD prevalence monitoring program are more likely to be
based on confirmed positivity. Nevertheless, even
confirmed RPR positivity does not indicate
syphilis disease stage or infectiousness. Some
proportion of confirmed positive results are in
individuals with old, already treated infection. In
addition, some percentage of inmates who test
positive for STDs will be treated successfully
during their incarceration. As a result, using
estimates of STD positivity among incoming
inmates to produce estimates of the number of
offenders released with STDs may artificially
inflate estimates of STDs among releasees.
On the other hand, intake jail testing usually does
not occur until an individual has been in jail for at
least 72 hours and, in some jurisdictions, at least
14 days. A large proportion of jail inmates are

22
probably released on bail or otherwise before
receiving any intake screening. Sex workers and
others likely to be at highest risk for STDs may
be disproportionately represented among those
released without having been screened. These
circumstances would suggest that statistics on jail
intake screening for STDs may understate the true
prevalence of STDs among people passing
through jails.
Another important consideration is that some
STDs such as gonorrhea and chlamydia are often
asymptomatic. Infected individuals may act as
carriers and vectors of disease without becoming
symptomatic or knowing of their own infection.

Estimates and estimation methods
As shown in table 4, it is estimated that between
46,000 and 76,000 prison and jail inmates and
between 202,000 and 332,000 releasees had
positive RPR serologies for syphilis in 1997. A
positive RPR serology is only a crude indication
of infection. It does not reflect disease stage or
infectiousness. For the reasons enumerated above,
these estimates may be overstated. The figures are
based on a range of 2.6–4.3 percent prevalence of
RPR positivity in prison and jail systems combined. Because of the regional differences in
syphilis incidence noted above, two weighted
average prevalence estimates were generated,
combining statistics for mandatory or routine
intake screening from the 1997 NIJ/CDC survey
and for routine intake screening from the CDC’s
STD Prevalence Monitoring Program for 1997.
The upper end is based on all observations
available, including jurisdictions in the South,
while the lower end excludes southern jurisdictions.

The observations used in both calculations are
shown in tables 5a and 5b. The average was
weighted by total inmate population in each
system. Although gender differences are
important in STD prevalence and course of
infection, it was impossible to calculate separate
estimates for men and women because many
systems only reported aggregated data.
For gonorrhea and chlamydia, weighted averages
were calculated that pooled State and Federal and
city and county systems. This yielded estimated
prevalence rates of 1.0 percent for gonorrhea and
2.4 percent for chlamydia. The period prevalence
estimates shown in tables 6 and 7 suggest that
almost 18,000 inmates and 77,000 releasees were
infected with gonorrhea, and almost 43,000
inmates and 186,000 releasees were infected with
chlamydia. These estimated prevalence rates were
derived by calculating weighted averages of
system-specific rates based on mandatory or
routine intake screening reported to the 1997
NIJ/CDC survey and the CDC’s STD Prevalence
Monitoring Program in 1997. All of these
observations are shown in tables 8 and 9.
Five jurisdictions reported gonorrhea prevalence
data for women only to the CDC Prevalence
Monitoring Program; seven jurisdictions reported
chlamydia prevalence data for women only. These
women-only rates were converted to overall rates
based on comparison of gender-specific data for
gonorrhea screening in San Francisco (1.7 percent
of men and 2.5 percent of women) and Cook
County (2.0 percent of men and 4.2 percent of
women). Based on these comparisons, female
gonorrhea prevalence rates were estimated to be
75 percent higher than male rates. The overall
prevalence estimate was then calculated based on
the gender distribution of jail inmates reported by
BJS in 1997—89 percent men and 11 percent
women.

Table 4. National Estimates of Inmates and Releasees with Positive RPR Serologies
Category

Est. %
RPR+

Population,
1997

Est. RPR+
Inmates, 1997

Releasees,
1996

Est. RPR+
Releasees, 1996

All systems

2.6–4.3

1,785,335

46,597–76,537

7,750,666

202,292–332,271

23
Table 5a. Derivation of RPR+ Prevalence Estimates (Southern Jurisdictions Excluded)
#
Tested

Jurisdictiona

#
Positive

%
Positive

Population,
1997

Weight

Weighted %
Positive

NIJ/CDC Survey (unless otherwise noted)
Idaho

2,540

3

0.1

4,105

0.020

0.001977

Illinois

22,722

246

1.1

40,425

0.195

0.214143

4,090

2

0.5

6,636

0.032

0.015979

Iowa
Kansas

6,540

65

7,790

0.038

0.037515

Massachusetts

9,956

530

5.3

1

11,907

0.057

0.303907

Missouri

14,716

73

0.5

23,687

0.114

0.057035

Nevada

3,384

20

0.6

8,617

0.041

0.024898

Oregon

6,769

34

0.5

7,899

0.038

0.019020

New Jersey

11,880

254

2.1

27,766

0.134

0.280798

Rhode Island

11,157

150

1.3

3,293

0.016

0.020616

West Virginia

1,850

16

0.9

3,003

0.014

0.013015

Wisconsin

5,551

56

1

13,965

0.067

0.067252

807

2

1,468

0.007

0.001414

Wyoming

0.2

Alameda, California

7,128

278

3.9

4,098

0.020

0.076966

Nassau, New York

10,500

276

2.6

1,739

0.008

0.021774

120,765

11,728

9.7

17,528

0.084

0.818777

21,441

2,322

10.8

5,563

0.027

0.289331

2.7

6,732

0.032

0.087533

301

8.4

2,243

0.011

0.090734

3,817

3.8

9,189

0.044

0.168156

207,653

1.000

New York City, New York
Philadelphia, Pennsylvania
Maricopa, Arizona

b

San Francisco, California
Chicago (Cook), Illinois
Total

d

c

3,594
100,981

Weighted Average
Prevalence Estimate
2.610839
a
Source is NIJ/CDC Survey unless otherwise noted.
b
CDC STD Prevalence Monitoring Program, 1997.
c
San Francisco Department of Public Health, STD Prevention and Control Section. September, 1998. STD Screening: San
Francisco County Jails, 1997.
d
Chicago Department of Public Health, STD/HIV Prevention Program, unpublished data.

24
Table 5b. Derivation of RPR+ Prevalence Estimates (Southern Jurisdictions Included)
#
#
%
Population,
Weighted %
Jurisdiction/Source
Tested
Positive
Positive
1997
Weight
Positive
NIJ/CDC Survey
Arkansas
699
72
10.3
9,539
0.020
0.030
Georgia
13,811
457
3.3
36,329
0.195
0.114
Idaho
2,540
3
0.1
4,105
0.032
0.013
Illinois
22,722
246
1.1
40,425
0.038
0.127
Iowa
4,090
2
0.5
6,636
0.057
0.021
Kansas
6,540
65
1
7,790
0.114
0.025
Massachusetts
9,956
530
5.3
11,907
0.041
0.037
Mississippi
6,718
914
13.6
14,639
0.038
0.046
Missouri
14,716
73
0.5
23,687
0.134
0.075
Nevada
3,384
20
0.6
8,617
0.016
0.027
Oregon
6,769
34
0.5
7,899
0.014
0.025
New Jersey
11,880
254
2.1
27,766
0.067
0.087
Rhode Island
11,157
150
1.3
3,293
0.007
0.010
West Virginia
1,850
16
0.9
3,003
0.020
0.009
Wisconsin
5,551
56
1
13,965
0.008
0.044
Wyoming
807
2
0.2
1,468
0.084
0.005
Alameda, California
7,128
278
3.9
4,098
0.027
0.013
Washington, D.C.
10,568
1,634
15.5
6,873
0.032
0.022
Palm Beach, Florida
12,607
1,200
9.5
2,283
0.011
0.007
Pinellas, Florida
10,938
192
1.8
2,296
0.044
0.007
Dekalb, Georgia
1,682
72
4.3
2,491
0.008
Prince George’s, Maryland
5,028
275
5.5
1,297
0.004
Nassau, New York
10,500
276
2.6
1,739
0.005
New York City, New York
120,765
11,728
9.7
17,528
0.055
Philadelphia, Pennsylvania
21,441
2,322
10.8
5,563
0.018
CDC STD Prevalence
Monitoring Program
Jefferson, Alabama
1.8
1,310
0.004
0.007421
Maricopa, Arizona
2.7
6,732
0.021
0.057205
San Francisco, Californiaa
3,594
301
8.4
2,243
0.007
0.059297
Orange, Florida
10.4
3,411
0.011
0.111645
Fulton, Georgia
3.6
3,982
0.013
0.045116
Cook (Chicago), Illinoisb
100,981
3,817
3.8
9,189
0.029
0.109895
Orleans, Louisiana
6.3
6,537
0.021
0.129612
Baltimore, Maryland
6.1
3,598
0.011
0.069074
Hinds, Mississippi
10.1
789
0.002
0.025080
Columbia, South Carolina
5.7
923
0.003
0.016558
Shelby, Tennessee
12.4
5,568
0.018
0.217293
Harris, Texas
6.7
8,224
0.026
0.173414
Total
317,742
1.000
Weighted Average
Prevalence Estimate
4.287272
a
San Francisco Department of Public Health, STD Prevention and Control Section. September 1998. STD Screening: San
Francisco County Jails, 1997.
b
Chicago Department of Public Health, STD/HIV Prevention Program, unpublished data.

25
Table 6. National Estimates of Inmates and Releasees with Gonorrhea Infection

Category

Est. % w/
Gonorrhea
Infection

Population,
1997

Est. Gonorrhea+
Inmates, 1997

Releasees,
1996

Est. Gonorrhea+
Releasees, 1996

1.0

1,785,335

17,853

7,750,666

77,507

All systems

Table 7. National Estimates of Inmates and Releases with Chlamydia Infection

Category

Est. % w/
Chlamydia
Infection

Population,
1997

Est. Chlamydia+
Inmates, 1997

Releasees,
1996

Est. Chlamydia+
Releasees, 1996

2.4

1,785,335

42,848

7,750,666

186,016

All systems

Table 8. Derivation of Gonorrhea Prevalence Estimates
Jurisdiction

Year

Idaho
Wisconsin
Wyoming
CDC STD Prevalence
Monitoring Program

% Positive

Population,
1997

150

2

1.3

4,105

2,500

11

0.4

13,965

807

1

0.1

1,468

1997
a

Connecticut
Washington, D.C.
Cook, Illinois

#
Positive

1996–97

NIJ/CDC Survey

San Francisco, California

#
Tested

b

Shawnee, Kansas

4,309

2.0

2,243

—

—

1.7

15,608

—

—

1.1

6,873

2,475

2.3

9,189

—

0.4

275

108,941
—

82

New York City, New York

—

—

1.4

17,528

Columbia, South Carolina

—

—

4.6

923

Shelby, Tennessee

—

—

0.8

5,568

Weighted Average
Prevalence Estimate
1.0
a
San Francisco Department of Public Health, STD Prevention and Control Section. September 1998. STD Screening: San
Francisco County Jails, 1997.
b
Chicago Department of Public Health, STD/HIV Prevention Program, unpublished data.

26
Table 9. Derivation of Chlamydia Prevalence Estimates
Jurisdiction
NIJ/CDC Survey

Year

#
Tested

#
Positive

%
Positive

Population,
1997

1996–97

Iowa

777

24

3.1

6,636

North Dakota

503

8

1.6

739

5,106

317

6.2

2,243

CDC STD Prevalence
Monitoring Program

1997

San Francisco, California*
Connecticut

—

—

2.8

15,608

Hawaii

—

—

2.3

4,491

Cook, Illinois

—

—

3.6

9,189

Shawnee, Kansas

—

—

1.4

275

New York City, New York

—

—

2.7

17,528

Multnomah, Oregon

—

—

3.6

1,467

King, Washington

—

—

1.8

2,412

Weighted Average
Prevalence Estimate
2.4
* San Francisco Department of Public Health, STD Prevention and Control Section. September 1998. STD Screening: San
Francisco County Jails, 1997.

For chlamydia, San Francisco was the only
jurisdiction for which gender-specific prevalence
data were available. Because the data showed
virtually identical rates for both sexes—6.2
percent among men and 6.1 percent among
women—the chlamydia prevalence rate among
women was used as the overall prevalence rate.
There are no reliable estimates of the prevalence
of syphilis, gonorrhea, or chlamydia infection in
the total U.S. population. The only prevalence
statistics available are for demonstrably unrepresentative population segments, such as
people requesting testing in STD or family
planning clinics. Therefore, it is not possible to
estimate the percentage of the total burden of
these sexually transmitted infections that occurs
among correctional populations.

Hepatitis B and C
Data sources and limitations
Data to develop national prevalence estimates of
hepatitis B (HBV) and C (HCV) virus infection
among correctional inmates are sparse. There is
no national surveillance or systematically

collected national data on hepatitis among
inmates. The only direct data are from a few
system-specific studies. The only two recent
studies of HBV prevalence among inmates were
done in the California State prison system23 and
the New York State prison system from 1987 to
1997.24 An important issue for the epidemiology
of HBV is that different markers have different
meanings: reactivity to HBV surface antigen
(HBsAg) indicates that a person is currently or
chronically infected and possibly infectious,
while reactivity to HBV core antibody (anti-HBc)
and nonreactivity to HBsAg indicates that a
person was infected at some unknown time in the
past but is no longer infectious.
More correctional systems have conducted
seroprevalence studies of HCV. Data are
available from the States of California,25
Connecticut,26 Maryland,27 Rhode Island,28
and Washington.29

Estimates and estimation methods
An indirect method of estimation for HCV was
used, given the paucity of direct prevalence data.
HCV is thought to be transmitted primarily

27
through sharing drug injection equipment,
although tattooing and body piercing may also be
implicated. Sexual transmission of HCV is
considered quite rare. According to the CDC,
HCV prevalence among injection drug users is
approximately 72–86 percent.30 Available data
suggest that about 24 percent of State prison
inmates nationwide have histories of injection
drug use.31 A crude estimate of HCV seroprevalence among inmates can be obtained by
multiplying these two percentages, yielding a
range from 17 to 21 percent. This is substantially
lower than the 30–41 percent found in the systemspecific studies cited above: California—41
percent among male and female intakes;32
Connecticut—32 percent among females;33
Maryland—38 percent among men and women;34
Rhode Island—33 percent among male and
female inmates seeking culinary work assignments;35 and Washington—30–40 percent among
men and women.36 Therefore the upper bound of
national prevalence estimates was increased to
40 percent. Using this range of prevalence rates
yields estimates of between 303,000 and 714,000
HCV-infected inmates and between 1.3 and 3.1
million HCV-infected releasees. This estimate of
releasees with HCV suggests that an extremely
high 29.3–68.9 percent of the estimated 4.5
million HCV-infected people in the U.S. population37 served time in a correctional facility. The
lower end of this ratio (29.3 percent) is within the
32 percent limit produced by the checking methodology presented earlier, but the upper end (68.9
percent) is more than double that limit.

Therefore, the range of prevalence rates was
adjusted to produce ratios of correctional cases to
total cases that fall within the 32 percent limit,
even though this range is below the percentages
found in all available system-specific studies.
Table 10 presents national period prevalence
estimates that 17.0–18.6 percent of prison and jail
inmates and releasees were infected with HCV in
1996 and 1997, representing 303,000–332,000
inmates and 1.3–1.4 million releasees. Using the
above method, it was not possible to provide
separate estimates for prison and jail systems. The
17.0–18.6 percent prevalence range is between 9
and 10 times the estimated HCV prevalence of 1.8
percent in the U.S. population.38
The estimate of 1.3–1.4 million releasees with
HCV suggests that an extremely high 29–32
percent of all persons with HCV infection passed
through a correctional facility in 1996.
Given the extreme paucity of data on HBV
prevalence and the different measures involved
and reported, estimating national seroprevalence
for this condition is perilous. The indirect
estimation method used for HCV is not appropriate to HBV because HBV is commonly
transmitted both sexually and parenterally.
Table 11 presents a period prevalence estimate
that 2 percent of inmates and releasees, representing
more than 35,000 inmates and 155,000 releasees,
are positive for the HBV surface antigen (HBsAg)
indicating current or chronic HBV infection and
possible infectiousness. This estimate is based on

Table 10. National Estimates of Inmates and Releasees with Hepatitis C (HCV) Infection

Category

Est. % w/ HCV
Infection*
(Range)

All systems
17–18.6
* Defined as HCV antibody positive.

Population,
1997

Est. Anti-HCV+
Inmates, 1997
(Range)

Releasees,
1996

Est. Anti-HCV+
Releasees, 1996
(Range)

1,785,335

303,507–332,072

7,750,666

1,317,613–1,441,624

Table 11. National Estimates of Inmates and Releasees with Current or Chronic Hepatitis B Infection
Category

Est. % w/
HBsAg*

All systems
2
* Hepatitis B surface antigen.

Population,
1997

Est. HBsAg+
Inmates, 1997

Releasees,
1996

Est. HBsAg+
Releasees, 1996

1,785,335

35,707

7,750,666

155,013

28
the 2 State studies in California (1994) and New
York (1987–97), which yielded similar results:
2.2 percent in California39 and 1.8 percent in New
York.40 Time series data from New York indicate
that the HBsAg seroprevalence among incoming
inmates remained virtually flat between 1987 and
1997.41 The proposed national estimate is 2
percent, which is 5 times the national prevalence
estimate of 0.4-percent positivity to HBsAg.42 The
estimate of 155,000 releasees with HCV infection
indicates that 12.4–15.5 percent of the national
burden of chronic or current HBV infection
(1–1.25 million persons)43 in 1996 occurred in
individuals who passed through a correctional
facility that year. This ratio falls within the limit
derived from the checking method described
above.

Tuberculosis Infection and Disease
Data sources and limitations
The primary source for prevalence estimates of
TB infection and disease among inmates is the
1997 NIJ/CDC survey. The survey sought data
on the number of inmates screened by purified
protein derivative (PPD) and the number who
tested positive during the 12 months before the
survey was completed, yielding a period
prevalence estimate. In addition, the survey
sought data on the number of inmates under
treatment for active TB disease at the time the
survey was completed, yielding a point prevalence estimate. Response rates were good for
active TB disease—69 percent of State and
Federal systems and 88 percent of city and county
systems. They were lower but still probably
adequate for TB infection (PPD screening)—
47 percent of State and Federal systems and 61
percent of city and county systems.

An additional source of information on the prevalence of TB infection and disease is the CDC TB
surveillance data. Since 1994, the CDC surveillance case report for TB disease has included
a space to indicate whether the patient was a
resident of a correctional facility at the time of
diagnosis. The CDC surveillance data can be used
to calculate period prevalence of TB disease in
correctional settings as well as in the total
population.

Estimates and estimation methodology
Prevalence estimates for TB disease and TB
infection were calculated from the 1997 NIJ/CDC
survey results using the same method applied to
syphilis. Weighted average prevalence estimates
were calculated on the basis of the inmate
populations of the reporting systems. Table 12
presents point prevalence estimates that 0.04
percent of State and Federal prison inmates and
0.17 percent of city and county jail inmates—a
total of more than 1,400 inmates in all systems—
were under treatment for TB disease in 1997.
These prevalence rates are between 4 times (for
State and Federal prison inmates) and 17 times
(for city and county jail inmates) the rate of 0.01
percent found in the total U.S. population based
on CDC surveillance data for 1996.44 Applying
the estimated prevalence among inmates to releasees indicates that 200 persons were released
from State and Federal prisons with active TB in
1996, while more than 12,000 persons with active
TB were released from city and county jails that
year.
This suggests that 35 percent of the approximately 34,000 persons with active TB disease in

Table 12. National Estimates of Inmates and Releasees with Tuberculosis Disease
Category
State/Federal prison systems
City/county jail systems
Total

Est. %
with TB
Disease
0.04
0.17

Population,
1997
1,218,256
567,079
1,785,335

Est. Inmates
w/TB
Disease, 1997
487
964
1,451

Releasees,
1996
504,289
7,246,377
7,750,666

Est. Releasees
w/TB Disease,
1996
202
12,319
12,521

29
the United States in 1996 passed through a
correctional facility that year.
The prevalence of TB disease in the total U.S.
population in 1996 was estimated by using data
from the CDC’s TB registry and TB surveillance
reports. The TB registry reports, which provided
data on numbers of prevalent cases of TB disease,
were discontinued after 1994. After 1994, only
incidence data on TB disease are available.
Therefore, ratios of prevalence to incidence were
calculated for 1992, 1993, and 1994. The prevalence of TB disease during a given year was taken
to be the sum of cases at the start of the year and
cases added during the year. The incidence figure
was taken from the CDC’s TB surveillance
reports.45 The average ratio of 0.627 for the 3
years was applied to the 1996 incidence figure of
21,337 to obtain an estimated prevalence of TB
disease in that year of 34,030.
Table 13 shows the data from the prison and jail
systems reporting to the 1997 NIJ/CDC survey
that were used to calculate the TB disease prevalence estimates. According to the CDC surveillance
data, 790 TB cases were diagnosed among correctional inmates in 1996, a figure very close to the
768 inmates reported to the 1997 NIJ/CDC survey
as under treatment for active TB disease.
Tables 14 and 15 present the period prevalence
estimates and underlying NIJ/CDC survey data
for TB infection. It is estimated that 7.4 percent of
State and Federal inmates and 7.3 percent of city
and county inmates were PPD positive in 1997—
more than 90,000 prison inmates and more than
41,000 jail inmates. Applying these prevalence
percentages to releasees results in an estimate that

more than 37,000 people with TB infection were
released from State and Federal prisons in 1996,
and almost 529,000 TB-infected people were
released from city and county jails in that year.
There are no estimates of the prevalence of PPD
positivity in the total U.S. population, so it is not
possible to calculate the percentage of the national
burden of TB infection that is attributable to
correctional facilities.

Conclusion
The estimates presented in this paper, as
summarized in table 16, demonstrate that the
burden of infectious disease among correctional
inmates and releasees in the United States is
heavy. Available comparative statistics show that
the prevalence of AIDS, HIV infection, HCV, and
TB disease are many times higher in correctional
populations than in the total U.S. population, and
that a disproportionate share of the burden of
infectious disease is found among people who
serve time in correctional facilities. During 1996,
about 3 percent of the U.S. population passed
through a correctional facility. By contrast,
between 12 and 35 percent of the burden of key
infectious diseases was found in this relatively
small segment of the population.
The policy implication of these findings is clear.
Correctional facilities are critical settings in which
to provide interventions for the prevention and
treatment of infectious diseases. Such interventions
stand to benefit not only the inmates and their
families and partners, but also the public health of
the communities to which the vast majority of
inmates return.

30
Table 13. Derivation of TB Disease Prevalence Estimates, NIJ/CDC Survey
Jurisdiction
State/Federal prison systems
Alaska

Year

Inmates Under
Treatment for TB

% w/TB
Disease

Population, 1997

2

0.05

3,741

1996–97

Arizona

5

0.02

23,176

Arkansas

5

0.05

9,539

Connecticut

1

0.006

15,608

Delaware

0

—

5,313

Georgia

17

0.05

36,329

Hawaii

0

—

4,491

Idaho

2

0.05

4,105

Iowa

0

—

6,636

Kentucky

0

—

13,858

Louisiana

6

0.02

28,382

Massachusetts

1

0.008

11,907

Mississippi

0

—

14,639

Missouri

2

0.008

23,687

Nevada

1

0.01

8,617

New Hampshire

0

—

2,153

New Jersey

19

0.07

27,766

New Mexico

0

—

4,692

142

0.2

69,530

New York
North Carolina

8

0.02

32,334

Oklahoma

6

0.03

19,931

Oregon

0

—

7,899

Pennsylvania

0

—

34,703

Rhode Island

2

0.07

3,293

Tennessee

4

0.03

15,827

Texas

74

0.05

136,599

Utah

0

—

4,154

Vermont

0

—

1,187

Virginia

0

—

28,673

West Virginia

6

0.2

3,003

Wisconsin

1

0.007

13,965

16

0.01

110,160

Federal Bureau of Prisons
Weighted Average
Prevalence Estimate

0.04

31
Table 13 (continued)
Inmates Under
Treatment for TB

% w/TB
Disease

Population, 1997

Maricopa, Arizona

0

—

6,732

Alameda, California

3

0.07

4,098

Contra Costa, California

2

0.13

1,574

Jurisdiction

Year

Fresno, California

2

0.09

2,107

Orange, California

4

0.07

5,368

Los Angeles, California

31

0.14

21,962

Riverside, California

20

0.79

2,528

San Bernardino, California

2

0.05

4,156

San Francisco, California

1

0.04

2,243

Santa Clara, California

1

0.02

4,588

Denver, Colorado

0

—

1,760

Washington, DC

0

—

6,873

Broward, Florida

0

—

4,125

Dade, Florida

0

—

7,320

Duval, Florida

4

0.16

2,507

Hillsborough, Florida

0

—

3,155

Orange, Florida

6

0.18

3,411

Palm Beach, Florida

2

0.09

2,283

Pinellas, Florida

0

—

2,296

Dekalb, Georgia

5

0.2

2,491

Cook, Illinois

9

0.1

9,189

Prince Georges, Maryland

0

—

1,297

Wayne, Michigan

0

—

2,708

Essex, New Jersey

1

0.05

2,025

Passaic, New Jersey

3

0.15

1,942

Nassau, New York

0

—

1,739

63

0.36

17,528

Cuyahoga, Ohio

0

—

1,705

Franklin, Ohio

2

0.13

1,501

Philadelphia, Pennsylvania

70

1.26

5,563

Shelby, Tennessee

New York City, New York

26

0.47

5,568

Bexar, Texas

3

0.08

3,683

Tarrant, Texas

1

0.03

3,366

Travis, Texas

0

—

2,132

King, Washington

0

—

2,349

Weighted Average
Prevalence Estimate

0.17

32
Table 14. National Estimates of Inmates and Releasees with TB Infection*
Est. PPD+
Releasees,
1996

Est. % PPD+

Population,
1997

Est. PPD+
Inmates

Releasees,
1996

State/Federal prison
systems

7.4

1,218,256

90,151

504,289

37,317

City/County
jail systems

7.3

567,079

41,397

7,246,377

528,986

1,785,335

131,548

7,750,666

566,303

Category

Total
* Defined as positive PPD skin test.

Table 15. Derivation of TB Infection Prevalence Estimates
#
Tested

#
PPD+

Connecticut

21,660

856

3.9

Delaware

45,944

324

0.7

5,313

Georgia

15,407

1,089

7.1

36,329

Hawaii

5,447

211

3.9

4,491

Idaho

3,832

76

2.0

4,105

Iowa

8,275

145

1.8

6,636

Jurisdiction
State/Federal prison systems

Kansas

Year

% PPD+

Population,
1997

1996–97
15,608

8,069

1,283

15.9

7,790

Maryland

23,095

283

1.2

22,415

Massachusetts

15,525

506

3.3

11,907

Mississippi

10,942

442

4.0

14,639

Missouri

27,238

592

2.2

23,687

Nebraska

1,750

65

3.7

3,431

Nevada

12,617

380

3.0

8,617

New Jersey

10,154

386

3.8

27,766

New Yorka

11,366

2,546

22.4

69,530

North Carolina

17,031

836

4.9

32,334

Oklahoma

12,300

227

1.8

19,931

Oregon

11,428

323

2.8

7,899

Rhode Island

13,000

190

1.4

3,293

Utah

3,537

213

6.0

4,154

Virginia

9,974

489

4.9

28,673

West Virginia

1,850

12

0.6

3,003

11,463

156

1.4

13,965

696

13

1.9

1,468

Wisconsin
Wyoming
Weighted Average
Prevalence Estimate

7.4

33

Table 15 (continued)
Number
Tested

Number
PPD+

% PPD+

38,510

4,447

11.5

4,098

6,100

405

6.6

1,574

22,749

1,935

8.5

5,368

Riverside, California

8,494

377

4.4

2,528

Washington, D.C

4,716

304

6.4

6,873

Dade, Florida

9,157

1,188

13.0

7,320

Hillsborough, Florida

52,728

2,063

3.9

3,155

Orange, Florida

12,263

289

2.4

3,411

Palm Beach, Florida

Jurisdiction

Year

City/County jail systems

Population,
1997

1996–97

Alameda, California
Contra Costa, California
Orange, California

12,613

691

5.5

2,283

Pinellas, Florida

5,400

274

5.1

2,296

Dekalb, Georgia

16,094

1,318

8.2

2,491

Cook, Illinois

22,673

954

4.2

9,189

Prince Georges, Maryland

15,365

983

6.4

1,297

Wayne, Michigan

15,562

1,042

6.7

2,708

1,786

171

9.6

2,113

16,000

960

6.0

2,025

76,516

8,806

11.5

17,528

1,316

79

6.0

1,705

Clark, Nevada
Essex, New Jersey
New York City, New York

a

Cuyahoga, Ohio
Franklin, Ohio

3,948

57

1.4

1,501

20,230

793

3.9

5,563

4,573

131

2.9

5,568

Bexar, Texas

41,475

796

1.9

3,683

Tarrant, Texas

15,870

657

4.1

3,366

Travis, Texas

13,800

1,500

10.9

2,132

King, Washington

1,923

224

11.6

2,349

Durham, North Carolinab

1,009

89

8.8

477

Philadelphia, Pennsylvania
Shelby, Tennessee

Weighted Average
Prevalence Estimate
a
Mikl et al. 1998 (blinded intake studies, 1987–97).
b
Jones 1998.

7.3

34

Table 16. Burden of Infectious Disease Among Inmates and Releasees

Est. Prevalence
Among Inmates, %

Total # in U.S.
Population w/
Condition, 1996

Prisons

Jails

Est. # of
Inmates w/
Condition, 1997

0.5a

0.5a

8,900

39,000

229,000b

17.0

2.3–2.98c

1.2–1.8d

35,000–47,000

98,000–145,000

750,000e

13.1–19.3

Positive RPR
Serology (Syphilis)

2.6–4.3

2.6–4.3

46,000–76,000

202,000–332,000

N/A

—

Chlamydia Infection

2.4

2.4

43,000

186,000

N/A

—

GC Infection

1.0

1.0

18,000

77,000

N/A

—

HBV (HBsAg+)

2.0

2.0

36,000

155,000

1,000,000–
1,250,000f

12.4–15.5

17–18.6g

17–18.6g

303,000–332,000

1,300,000–1,400,000

4,500,000h

28.9–32.0

Condition
AIDS
HIV Infection

HCV (anti-HCV+)
TB Disease
TB Infection (PPD+)
a

Est. # of
Releasees w/
Condition, 1996

Releasees w/
Condition as
% of Total in
U.S.
Population
w/Condition,
1996

i

j

k

0.04

0.17

1,400

12,000

34,000

35.3

7.4

7.3

131,000

566,000

N/A

—

>5 times prevalence in U.S. population (0.09%).
b
Centers for Disease Control and Prevention, HIV/AIDS Surveillance Report, 1997.
c
8–10 times prevalence in U.S. population (0.3%).
d
4–6 times prevalence in U.S. population (0.3%).
e
CDC estimate, based on midpoint of 1993 estimate (Rosenberg 1995).
f
CDC, Morbidity and Mortality Weekly Report, November 22, 1991.
g
9–10 times prevalence in U.S. population (1.8%)
h
Based on prevalence estimate in McQuillan et al (1997).
i
4 times prevalence in U.S. population (0.01%).
j
17 times prevalence in U.S. population (0.01%).
k
Estimated from Centers for Disease Control and Prevention, TB Registry Reports, 1992–94. See text for discussion.

35

Notes

Prevention, 1999, NCJ 176344.

1. Glaser, J.B., and R.B. Greifinger, “Correctional
Health Care: A Public Health Opportunity,” Annals of
Internal Medicine 118(2)(1993): 139–145; Polonsky,
S., S. Kerr, B. Harris, J. Gaiter, R.R. Fichtner, and
M.G. Kennedy, “HIV Prevention in Prisons and Jails:
Obstacles and Opportunities,” Public Health Reports
109(5)(1994): 615–625; Gaiter, J., and L. Doll,
“Improving HIV/AIDS Prevention in Prisons is Good
Public Health Policy” (editorial), American Journal of
Public Health 86(9)(1996): 1201–1203; Hammett,
T.M., J. Gaiter, and C. Crawford, “Reaching Seriously
At-Risk Populations: Health Interventions in Criminal
Justice Settings,” Health Education and Behavior
25(1)(1998): 99–120.

8. About 322,000 sentenced inmates were in jail on the
day of BJS’s 1997 annual jail survey (Gilliard, D.K.,
and A.J. Beck, Prison and Jail Inmates at Midyear
1997 [see note 4]). If sentenced inmates could serve
about X months on average in jail, then one could
estimate that roughly 322,000 x 12/X unique sentenced
inmates are released during the year. Unfortunately,
estimates of the average jail term served by sentenced
inmates are not readily available. If the average jail
term is 3 months, then roughly 1,288,000 unique
sentenced inmates are released from jail every year.
Not all of these could have been arrested during that
same year. About 322,000 must have begun their jail
terms before the year started, reducing the potential
overlap to 966,000. But many sentenced jail inmates
must also have been arrested before the year started,
because there is often a considerable delay between
arrest and conviction. If this delay averages 3 months,
then the overlap should be reduced by 322,000, leaving
a potential overlap of 644,000. Provided this estimate
is not grossly wrong, it suggests that the overlap is a
small part of the roughly 10 million jail releases
estimated by BJS to have occurred during 1996.

2. Centers for Disease Control and Prevention,
“HIV/AIDS Education and Prevention Programs
for Adults in Prisons and Jails and Juveniles in
Confinement Facilities—United States, 1994,”
Morbidity and Mortality Weekly Report 45(13)(1996):
268–271; Maruschak, L., HIV in Prisons and Jails,
1995, Bureau of Justice Statistics Bulletin, Washington, DC: U.S. Department of Justice, Bureau of Justice
Statistics, August 1995, NCJ 164260.
3. Lilienfeld, A.M., and D.E. Lilienfeld, Foundations
of Epidemiology 2d. ed., New York: Oxford University
Press, 1980.
4. Gilliard, D.K., and A.J. Beck, Prison and Jail
Inmates at Midyear 1997, Bureau of Justice Statistics
Bulletin, Washington, DC: U.S. Department of Justice,
Bureau of Justice Statistics, January 1998, NCJ
167247; Bureau of Justice Statistics, Correctional
Populations in the United States, 1997, Washington,
DC: U.S. Department of Justice, Bureau of Justice
Statistics, 2000, NCJ 177613.
5. Gilliard, D.K., and A.J. Beck, Prison and Jail
Inmates at Midyear 1997 (see note 4).
6. Bureau of Justice Statistics, Correctional Populations in the United States, 1996, Washington, DC:
U.S. Department of Justice, Bureau of Justice
Statistics, November 2000, NCJ 177613.
7. Hammett, T.M., P. Harmon, and L. Maruschak,
1996–1997 Update: HIV/AIDS, STDs, and TB in
Correctional Facilities, Issues and Practices in
Criminal Justice, Washington, DC: U.S. Department of
Justice, National Institute of Justice and Bureau of
Justice Statistics; and Centers for Disease Control and
Prevention, National Institute for HIV, STD, and TB

9. Bureau of Justice Statistics, Correctional Populations in the United States, 1996, Washington, DC: U.S.
Department of Justice, Bureau of Justice Statistics,
1999, NCJ 170013.
10. Maguire, K., and A.L. Pastore, eds., Sourcebook
of Criminal Justice Statistics, 1997, Washington, DC:
U.S. Department of Justice, Bureau of Justice Statistics,
1998, NCJ 171147, table 6.30.
11. This analysis assumes that arrests of injection drug
users are generated by a Poisson process with parameter 0.38 that is invariant across IDUs. This implies
that an IDU has a probability of 0.316 of being arrested
at least once during a given year. Therefore, in a steady
state, 0.316 is the approximate probability that an IDU
will be released from jail or prison during that year.
12. Centers for Disease Control and Prevention,
HIV/AIDS Surveillance Report, 1997 9(2)(1997):
1–43.
13. Harlow, C.W., HIV in U.S. Prisons and Jails,
Bureau of Justice Statistics Special Report, Washington, DC: U.S. Department of Justice, Bureau of
Justice Statistics, September 1993, NCJ 143292.

36
14. Maruschak, L., HIV in Prisons and Jails, 1995
(see note 2); Hammett, T.M., P. Harmon, and L.
Maruschak, 1996–1997 Update: HIV/AIDS, STDs,
and TB in Correctional Facilities (see note 7).
15. Maruschak, L., HIV in Prisons and Jails, 1995
(see note 2).
16. Ibid.
17. Centers for Disease Control and Prevention,
HIV/AIDS Surveillance Report, 1997 (see note 12).
18. Ibid.
19. Hoxie, N.J., J.M. Vergeront, H.R. Frisby, J.R.
Pfister, R. Golubjatnikov, and J.P. Davis, “HIV
Seroprevalence and the Acceptance of Voluntary HIV
Testing Among Newly Incarcerated Male Prison
Inmates in Wisconsin,” American Journal of Public
Health 80(9)(1990): 1129–1131; Andrus, J., D.W.
Fleming, C. Knox, R.O. McAllister, M.R. Skeels, R.E.
Conrad, J.M. Horan, and L.R. Foster, “HIV Testing
in Prisoners: Is Mandatory Testing Mandatory?”
American Journal of Public Health 79(7): 840–842.
20. Holmberg, S.D., “The Estimated Prevalence and
Incidence of HIV in 96 Large U.S. Metropolitan
Areas,” American Journal of Public Health
86(5)(1996): 642–654.
21. See, for example, Blank, S., D.D. McDonnell, S.R.
Rubin, J.J. Neal, M.W. Brome, M.B. Masterson, and
J.R. Greenspan, “New Approaches to Syphilis Control:
Finding Opportunities for Syphilis Treatment and
Congenital Syphilis Prevention in a Women’s
Correctional Setting,” Sexually Transmitted Diseases
24(4)(1997): 218–226; Mikl, J., A. Dzierbicki, P.F.
Smith, R. Greifinger, L. Wright, and D.L. Morse,
“Trends in HIV Infection Rates Among New York
State (NYS) Prison Inmates, 1987–97,” poster abstract
no. 23516 presented at 12th World AIDS Congress,
June 30, 1998, Geneva, Switzerland; Holmes, M.D.,
S.M. Safyer, N.A. Bicknell, S.H. Vermund, P.A.
Hanff, and R.S. Phillips, “Chlamydial Cervical
Infection in Jailed Women,” American Journal of
Public Health 83(4)(1993): 551–555.
22. Mertz, K.J., S. Blank, J.G. Courtney, S. Dick, I.
Dyer, M.P. Wilson, S. Danos, R. Voigt, K. Hutchins,
W.C. Levine, et al., “A System for Monitoring STD
Prevalence Among Persons Admitted to Jails and
Juvenile Detention Facilities in the United States”
(abstract); Centers for Disease Control and Prevention,
Reported Tuberculosis in the United States, 1996,

Atlanta: Centers for Disease Control and Prevention,
1997.
23. Ruiz, J.D., and J. Mikanda, “Seroprevalence of
HIV, Hepatitis B, Hepatitis C, and Risk Behaviors
Among Inmates Entering the California Correctional
System,” California Department of Health Services,
Office of AIDS, HIV/AIDS Epidemiology Office,
March 1996.
24. Mikl, J., A. Dzierbicki, P.F. Smith, R. Greifinger,
L. Wright, and D.L. Morse, “Trends in HIV Infection
Rates Among New York State (NYS) Prison Inmates,
1987–97” (see note 21).
25. Ruiz, J.D., and J. Mikanda, “Seroprevalence of
HIV, Hepatitis B, Hepatitis C, and Risk Behaviors
Among Inmates Entering the California Correctional
System” (see note 23).
26. Fennie, K.P., P.A. Selwyn, and F.L. Altice,
“Hepatitis C Virus Seroprevalence and Seroincidence
in a Cohort of HIV+ and HIV- Female Inmates,” poster
abstract Tu.C.2655 presented at the XI International
Conference on AIDS, July 9, 1996, Vancouver, British
Columbia.
27. Vlahov, D., K.E. Nelson, T.C. Quinn, and N.
Kendig, “Prevalence and Incidence of Hepatitis C
Virus Among Male Prison Inmates in Maryland,”
European Journal of Epidemiology 9(5)(1993):
566–569.
28. Spaulding, A., C. Greene, K. Davidson, B.S.
Schneiderman, and J. Rich, “Hepatitis C in State
Correctional Facilities,” Preventive Medicine
28(1)(1999): 92–100.
29. Schueler, L., presentation at a Symposium on
Current Strategies for the Treatment and Prevention of
HIV in Corrections sponsored by Brown University
AIDS Program and Yale University HIV in Prisons
Program, October 24, 1998, New York.
30. Centers for Disease Control and Prevention,
“Recommendations for Prevention and Control of
Hepatitis C Virus (HCV) Infection and HCV-Related
Chronic Disease,” Morbidity and Mortality Weekly
Report 47(RR–19)(1998): 1–39.
31. National Center on Addiction and Statistics,
Behind Bars: Substance Abuse and America’s Prison
Population, New York: National Center on Addiction
and Substance Abuse, 1998: 182.

37
32. Ruiz, J.D., and J. Mikanda, “Seroprevalence of
HIV, Hepatitis B, Hepatitis C, and Risk Behaviors
Among Inmates Entering the California Correctional
System” (see note 23).

39. Ruiz, J.D., and J. Mikanda, “Seroprevalence of
HIV, Hepatitis B, Hepatitis C, and Risk Behaviors
Among Inmates Entering the California Correctional
System” (see note 23).

33. Fennie, K.P., P.A. Selwyn, and F.L. Altice,
“Hepatitis C Virus Seroprevalence and Seroincidence
in a Cohort of HIV+ and HIV- Female Inmates” (see
note 26).

40. Mikl, J., A. Dzierbicki, P.F. Smith, R. Greifinger,
L. Wright, and D.L. Morse, “Trends in HIV Infection
Rates Among New York State (NYS) Prison Inmates,
1987–97” (see note 21).

34. Vlahov, D., K.E. Nelson, T.C. Quinn, and N.
Kendig, “Prevalence and Incidence of Hepatitis C
Virus Among Male Prison Inmates in Maryland”
(see note 27).

41. Jaromir Mikl, New York State Department of
Health, personal communication, November 1998.

35. Spaulding A., C. Greene, K. Davidson, B.S.
Schneiderman, and J. Rich, “Hepatitis C in State
Correctional Facilities” (see note 28).
36. Schueler, L., presentation at a Symposium on
Current Strategies for the Treatment and Prevention
of HIV in Corrections (see note 29).
37. Based on the prevalence estimate in McQuillan,
G.M., M.J. Alter, L.A. Moyer, S.B. Lambert, and H.S.
Margolis, “A Population Based Serologic Survey of
Hepatitis C Virus Infection in the U.S.,” in Viral
Hepatitis and Liver Disease, M. Rizzetto, R.H. Purcell,
G.L. Gerin, and G. Verne, eds., Turin: Edizioni
Minerva Medica, 1997: 267–270.
38. McQuillan, G.M., M.J. Alter, L.A. Moyer, S.B.
Lambert, and H.S. Margolis, “A Population Based
Serologic Survey of Hepatitis C Virus Infection in
the U.S.” (See note 37).

42. Patrick Coleman, Centers for Disease Control and
Prevention, personal communication, December 3,
1998.
43. Centers for Disease Control, “Hepatitis B Virus: A
Comprehensive Strategy for Eliminating Transmission
in the United States Through Universal Childhood
Vaccination: Recommendations of the Immunization
Practices Advisory Committee (ACIP),” Morbidity and
Mortality Weekly Report 40(RR–13)(1991): 1–25.
44. Centers for Disease Control and Prevention,
“HIV/AIDS Education and Prevention Programs for
Adults in Prisons and Jails and Juveniles in Confinement Facilities—United States, 1994,” Morbidity and
Mortality Weekly Report 45(13)(1996): 268–271.
45. Centers for Disease Control and Prevention,
Reported Tuberculosis in the United States, 1992–1994,
Atlanta: Author, 1993–1995.

39

A Projection Model of the Prevalence
of Selected Chronic Diseases in
the Inmate Population

Carlton A. Hornung, Ph.D., M.P.H., Department of Medicine, Center for Health Services and Policy
Research, University of Louisville School of Medicine; Robert B. Greifinger, M.D., National Commission
on Correctional Health Care; and Soniya Gadre, M.P.H., Department of Medicine, Center for Health
Services and Policy Research, University of Louisville School of Medicine

Introduction
Little is known about the prevalence of chronic
diseases in the inmate population or the potential
impact on the community when inmates with
chronic diseases are released. To address these
unknowns, the National Institute of Justice (NIJ)
commissioned a study to investigate the health
status of soon-to-be-released inmates and awarded
a grant to the National Commission on Correctional
Health Care (NCCHC). The project’s steering
committee1 named an expert panel on chronic
disease and, working with that panel, targeted
four chronic diseases for study: asthma, diabetes,
hypertension, and heart disease.
Inmates with chronic medical conditions such
as those targeted for study in this project do not
represent the same kind of threat to the health
status of the general community when they are
released as do inmates with communicable
diseases such as hepatitis, tuberculosis (TB), and
human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS). Nonetheless,
inmates with chronic disease have a significant
effect on the correctional health care system, and
it is reasonable to expect that they will affect the
health care system in the general community
when they are released. Persons who delay or do
not receive needed ambulatory care are at
increased risk of becoming more seriously ill and
requiring hospitalization. Thus, undertreated
chronically ill inmates affect the community
during incarceration and following release

through increased demand for acute care and
costly tertiary services.2
Providing quality health care services to inmates
with chronic diseases can place a significant
strain on the correctional health care system in
terms of both the manpower required to provide
needed services and the costs of treatment.
Avoidable hospitalizations have been defined as
those that could potentially be avoided in the
presence of appropriate and timely ambulatory
care. The organizational and budgetary stresses
on the prison health system created by chronic
disease conditions within the inmate population
are expected to increase as the inmate population
ages. No less important are the consequences for
the health care system in the community when
inmates are released after receiving poor quality
care within the prison system. The inmate whose
diabetes or hypertension is poorly managed while
incarcerated is, when released back into the
community, more likely to use costly health care
services (e.g., dialysis for renal failure or
emergency room visits for glucose control or
stroke).
The steering committee and the expert panel on
chronic disease sought to determine the prevalence
of asthma, diabetes, hypertension, and heart
disease in the inmate population and the burden of
these conditions on both the correctional health
care system and the health care system in the
community. Measuring the impact of chronic
disease among soon-to-be-released inmates
requires either accurate data on the prevalence of

40
disease among inmates or projections of disease
prevalence derived from other comparable
populations.
Because accurate data on the prevalence of
diseases in the inmate population do not exist, an
alternative method for estimating the burden of
disease and the prevalence of the target conditions
in the correctional population must be employed.
One method is to use information on the prevalence
of the condition or disease in a known population
and apply these age-, gender-, and race-specific
disease prevalence rates to the target population.
This projection model yields estimates of the
expected number of prisoners with that disease.

The National Health and Nutrition
Examination Survey (NHANES)
The National Health and Nutrition Examination
Survey (NHANES) is one of the major health
surveys conducted by the National Center for
Health Statistics (NCHS).3 The survey was first
conducted between 1971 and 1974 (NHANES–I),
redone in 1976–78 (NHANES–II), done in the
Hispanic population in 1982–84 (Hispanic
NHANES) and conducted most recently between
1988 and 1994 (NHANES–III). NHANES represents the seventh in a series of surveys done on
complex multistage samples designed to yield
national estimates of the nutrition and health
status of the civilian noninstitutionalized population
aged 2 months and older in the United States. The
most recent NHANES, NHANES–III, was chosen
as the reference population to calculate prevalence
rates for the four target chronic conditions. These
rates were then applied to the inmate population
to estimate the expected number of cases of each
condition within the prison system.
Estimates of the prevalence of asthma, diabetes,
hypertension and heart disease in the civilian
noninstitutionalized population were calculated
from the NHANES–III data. The principal data
from NHANES–III were taken from the Household

Adult Questionnaire, physical examinations
conducted at mobile examination centers, and
laboratory test results. These three data files were
merged and a weighted analysis was done using
SPSS/PC 7.5 statistical software.
The prevalence of each of the four chronic
diseases of interest—asthma, diabetes, hypertension, and coronary heart disease—was
examined by age, race and gender. Sampling
weights were used to estimate rates representative
of the U.S. population. The results obtained in the
analyses employing all noninstitutionalized
civilian cases are based upon a weighted sample
size of 187,644,316 cases. Age-adjusted genderand race-specific rates for the U.S. population
older than 17 were calculated and standardized to
the 1990 U.S. Census. These rates were then
applied to the 1995 State and Federal prison and
local jail population estimates provided by NIJ.
Estimates based on calculations involving all
NHANES–III cases provide the baseline
projections of disease in the system and are
referred to in this report as the baseline estimates.
Because the poor and economically disadvantaged
are disproportionately present in the prison and
jail population, prevalence rates also were
determined from NHANES–III for the lowest
quartile of socioeconomic status (SES) in the
United States. This subset analysis selected from
the population all individuals who were receiving public assistance in the form of welfare,
supplementary security income (SSI), or food
stamps. These filters reduced the weighted sample
size to 66,444,192 individuals who can be said to
reflect the lowest quartile of SES in the United
States. Estimates of disease prevalence in the
inmate population based upon calculations
involving the lowest quartile of SES constitute
a more realistic expectation of the prevalence
of disease among incarcerated individuals.
Projections of disease prevalence made from the
subsample analysis are called the low SES
estimates.

41

Asthma

These rates are based on self-reports of having
been diagnosed with asthma and current medical
treatment. Baseline race-specific rates shown in
table 1 show that Hispanics have the lowest
prevalence rate for asthma—about 6.1 cases per
100—while both whites and blacks have rates
of about 8 cases per hundred. In the low SES
estimates of prevalence (see table 2), whites have
the highest prevalence rate for asthma at 9.1/100,
followed by blacks at 8.8/100, with Hispanics
showing the lowest rate among racial-ethnic
groups at 6/100.

Asthma is a chronic inflammatory disease of the
airways that affects between 14 and 15 million
individuals, of whom about 4.8 million are
children.4 As pointed out in the Expert Panel
Report 2: Guidelines for the Diagnosis and
Management of Asthma,5 asthma results in about
100 million days of restricted activity, 470,000
hospitalizations, and 5,000 deaths annually.
Tables 1 and 2 give the prevalence rates for
asthma estimated from the NHANES–III data for
the baseline and low SES models, respectively.

Table 1. Baseline Asthma Prevalence Rates in the United States (per 100)
White 8.0
Age

Male 7.6

Black 8.0

Female 8.3

Male 7.3

Hispanic 6.1

Female 8.5

Male 6.2

Female 6.1

#19

6.3

10.4

9.8

14.5

20–29

8.5

7.4

9.2

5.3

2.5

4.0

30–39

7.1

9.4

6.0

7.9

11.0

3.3

40–49

0.9

9.1

5.5

11.0

7.8

7.3

50–59

6.6

8.7

8.4

9.0

3.3

9.5

60+

6.9

7.1

5.9

8.8

8.5

10.3

4.3

9.0

Table 2. Low SES Asthma Prevalence Rates in the United States (per 100)
White 9.1
Age

Male 9.2

Black 8.8

Female 8.9

Male 8.1

Hispanic 6.0

Female 9.3

Male 5.7

Female 6.1

#19

10.0

12.9

11.2

14.4

5.3

10.2

20–29

10.1

9.1

10.8

5.7

1.7

3.2

30–39

9.0

11.3

7.4

9.2

13.3

3.8

40–49

11.2

15.0

5.7

14.3

5.7

5.4

50–59

14.9

5.6

5.6

9.5

5.6

5.3

6.6

7.0

6.8

8.8

4.4

13.5

60+

42
Applying the baseline and low SES age-, race-,
and gender-specific rates presented in tables 1 and
2 to the demographic profile of the State prison
population yields the expected number of cases of
asthma under the two prevalence models (see
tables 3 and 4). Given the race, gender and age
composition of the State prison systems, the
baseline model predicts higher rates of asthma
among white inmates (7.9/100) than among black
(7.6/100) and Hispanic (6/100) inmates. The low
SES model predicts even higher prevalence rates
of asthma for both white (10.1/100) and black
(8.8/100) inmates but not Hispanic (6/100)
inmates.
The overall rate of asthma in prisons projected by
the baseline model is 7.2 cases per 100 inmates.
The low SES estimate is 20 percent higher than
the baseline model and predicts about 15,000

more cases in the prison systems. The increased
number of cases is concentrated among white
males (7,576 cases) and black males (5,555 cases).
Tables 5 and 6 present the predicted number of
cases of asthma in the inmate population in State
prisons, Federal prisons and local jails. The
baseline model predicts a total of 118,461 cases
of asthma in the incarcerated population (see table
5). The low SES model predicts about 20 percent
more cases of asthma among inmates. In both
models, approximately 63 percent of the cases are
predicted to be in State prisons, and another 31
percent are predicted to be in local jails. Almost
93 percent of the cases are predicted to occur
among males; black and white males account for
the vast majority of the cases. Fewer than 10
percent of the asthma cases among inmates are
predicted to be women.

Table 3. Expected Number of Cases of Asthma in State Prisons: Baseline Estimates (per 100)
White 7.9
Age
#19

Male 7.9

Black 7.6

Female 8.6

Male 7.6

Hispanic 6.0

Female 8.3

Male 6.1

Female 4.4

497

48

2,247

51

252

6

20–29

11,196

656

17,807

667

1,929

147

30–39

8,475

855

9,550

980

6,017

120

40–49

4,854

297

2,740

337

1,422

99

50–59

1,336

88

741

55

183

23

639

20

364

16

111

4

26,997

1,964

33,449

2,106

9,914

399

60+
Total

Table 4. Expected Number of Cases of Asthma in State Prisons: Low SES Estimates (per 100)
White 10.1
Age
#19

Male 10.1

Black 8.8

Female 10.7

Male 8.9

Hispanic 6.0

Female 8.3

Male 6.2

Female 3.9

789

59

2,568

50

311

6

20–29

13,304

807

20,904

717

1,312

118

30–39

10,744

1,028

11,778

1,141

7,001

138

40–49

6,109

489

2,840

438

1,039

73

50–59

3,016

57

494

58

310

13

611

19

420

16

57

5

34,573

2,459

39,004

2,420

10,030

353

60+
Total

43
Table 5. Expected Number of Cases of Asthma in Correctional Settings: Baseline Estimates
Sex and Race

National

All
Incarcerated

State
Prisons

Federal
Prisons

Local Jails

White male

5,617,797

43,109

26,998

2,693

13,419

White female

6,685,466

3,848

1,963

166

1,718

697,645

49,735

33,448

1,858

14,428

Black male
Black female

967,783

4,166

2,105

189

1,871

Hispanic male

463,360

16,704

9,913

1,772

5,019

Hispanic female

439,955

899

398

98

403

14,872,006

118,461

74,825

6,776

36,858

7.2

7.2

Total
Rate

7.8

7.1

7.1

Table 6. Expected Number of Cases of Asthma in Correctional Settings: Low SES Estimates
Sex and Race

National

All
Incarcerated

State
Prisons

Federal
Prisons

Local Jails

White male

7,344,857

55,590

34,572

3,642

17,377

White female

7,826,035

4,831

2,459

210

2,162

768,833

57,846

39,003

2,110

16,734

1,078,199

4,793

2,420

220

2,153

Hispanic male

448,718

16,878

10,030

1,781

5,067

Hispanic female

416,326

800

353

84

364

17,882,968

140,738

88,837

8,047

43,857

Black male
Black female

Total
Rate

9.4

8.5

Diabetes Mellitus
Diabetes is a chronic condition that contributes
significantly to morbidity and mortality. Diabetes
is a leading cause of renal failure and the need for
dialysis and a major risk factor for cardiovascular
disease and blindness.6
Data to determine the prevalence of diabetes were
taken from the NHANES–III Laboratory Data
File. Blood and urine specimens were collected
on examinees aged 1 year or older at the mobile
examination center by certified phlebotomists or
medical technicians. Examinees aged 12 and older
were instructed to fast for 10–16 hours if their
medical examination was scheduled for the
morning or for at least 6 hours if their examination
was scheduled for the afternoon. An oral glucose

8.6

8.5

8.5

tolerance test was given to examinees aged
40–74 who did not report current insulin therapy.
The fasting specimens and the 2-hour glucose
levels were determined in accordance with the
expert committees’ rules for the identification,
diagnosis and classification of diabetes mellitus.
Individuals with a normal fasting glucose of less
than 110 mg/dL are considered not to have
diabetes. Those with fasting glucose values
greater than 126 mg/dL are considered to have
diabetes. Individuals with glucose levels between
110 and 126 mg/dL are defined as having
impaired fasting glucose.
Before the publication of new diagnostic
guidelines in 1997,7 a fasting blood glucose of
140 mg/dL or higher was the cutoff point for
defining diabetes. The new guidelines lowered

44
that threshold to 126 mg/dL. Nevertheless, the
researchers first analyzed the prevalence of
diabetes in the NHANES–III data to predict the
number and distribution of cases among inmates
according to the 140 mg/dL criteria. Subsequent
analysis explored the prevalence and predicted
number of “new” cases among inmates whose
fasting glucose is between 126 and 139 mg/dL.
Finally, the prevalence of impaired fasting
glucose, defined by the new diagnostic criteria as
110–125 mg/dL, was analyzed. The results of
the glucose tolerance test given to a sample of
examinees aged 40–74 were not analyzed because
this age group is small in the incarcerated
population.

blacks, particularly black females older than 60,
approximately 20 percent of whom have diabetes.
The prevalence of diabetes is known to be highest
in lower SES groups as reflected in table 8. In the
low SES groups, the prevalence rates for diabetes
are also highest among blacks and females and
they increase with age.
The increase in prevalence of diabetes with age
implies that the prison population, because it is
younger than the general population, will have
lower rates of diabetes than in the general
population. Table 9 shows the number of cases
of diabetes by race, gender, and age that are
expected in the State prison population based
upon the prevalence in the U.S. population
according to the >140 mg/dL standard. These
baseline rates predict that approximately 21,000
State prison inmates will be found to have diabetes. Predicted cases are concentrated among
black male inmates (10,570; 50.3 percent) with
about 7,400 (35 percent) occurring among whites.

The NHANES–III data in table 7 shows that the
prevalence of diabetes according to the former
diagnostic criteria of a fasting serum glucose
equal to or greater than 140 mg/dL is highest
among blacks and females, and increases with
age for both males and females and for all races.
The highest rates of diabetes are found among

Table 7. Baseline Diabetes Prevalence Rates in the United States (per 100) (serum glucose >140mg/dL)
White 4.8
Age

Male 4.7

Black 6.4

Female 4.8

Male 5.5

Hispanic 4.4

Female 7.2

Male 3.3

Female 5.5

#19

0.0

1.2

0.6

0.0

0.4

0.2

20–29

0.4

0.0

1.3

0.8

0.1

0.4

30–39

1.8

1.7

1.9

2.3

0.6

2.3

40–49

3.0

3.5

5.5

6.7

3.9

7.0

50–59

9.9

5.3

13.0

14.5

6.7

12.7

11.5

11.9

16.3

22.4

18.6

18.8

60+

Table 8. Low SES Diabetes Prevalence Rates in the United States (per 100) (serum glucose >140 mg/dL)
White 7.1
Age

Male 6.4

Black 8.0

Female 7.5

Male 6.3

Hispanic 5.1

Female 9.3

Male 3.5

Female 6.5

#19

0.0

0.0

1.0

0.0

0.7

0.3

20–29

0.7

0.0

2.3

1.2

0.2

0.3

30–39

2.2

2.3

1.7

3.5

0.7

3.6

40–49

7.0

7.5

6.9

9.0

2.9

8.7

50–59

12.0

9.6

13.3

16.8

9.5

14.3

60+

12.0

13.6

16.1

24.2

18.8

20.6

45

Table 9. Expected Number of Cases of Diabetes in the State Prison Population: Baseline Estimates
(serum glucose >140 mg/dL)
White 2.1
Age
#19

Male 2.2
0

Black 2.4

Female 1.6

Male 2.4

Hispanic 1.2

Female 2.5

6

138

0

Male 1.1

Female 2.6

23

0

20–29

527

0

2,516

101

77

15

30–39

2,149

155

3,024

285

328

83

40–49

1,636

114

2,740

205

711

95

50–59

2,004

54

1,146

89

371

31

60+

1,065

33

1,006

39

242

7

Total

7,381

362

10,570

719

1,752

231

Table 10 presents the predicted number of cases
based upon estimates obtained from the lowest
quartile of SES. These higher prevalence rates
predict a total of more than 27,600 cases of
diabetes among State prison inmates, which is
about 30 percent higher than the baseline
estimates. The number of white male inmates
predicted to have diabetes increases by 47 percent
to almost 11,000 (10,906). This total is nearly as
many as the predicted number of black male
inmates with diabetes (12,992). These increases
reflect differences in the age distribution of men
in State prisons between blacks and whites. A
disproportionate number of older men in State
prisons are white.
Tables 11 and 12 show the expected number of
cases of diabetes (fasting serum glucose $140
mg/dL) in State and Federal prisons and local
jails using the baseline and low SES models. The
gender- and race-specific age-adjusted rates based
on the baseline model are 2.0/100 for State
prisons, 3.0/100 for Federal prisons, and 1.8/100
for local jails. Table 11 shows that under this model,
an estimated 32,984 diabetics are incarcerated:
about 21,000 in State prisons, 2,800 in Federal
prisons, and more than 9,000 in local jails.
Table 12 shows the higher estimates of the
prevalence of diabetes among inmates obtained
from the lowest quartile of SES. The total number of
diabetics predicted in this model is 43,557. State
prisons are predicted to house more than 27,000
diabetics (2.7 per 100). Federal prisons are

predicted to have the highest prevalence (3.8 per
100), with about 3,640 diabetic inmates. Local jails
are predicted to have the lowest prevalence (2.4 per
100), with some diabetic 12,305 inmates.
The difference in predicted prevalence rates across
Federal, State, and local institutions reflects differences in the age distributions of inmates in these
facilities.
The newest guidelines for diagnosing and treating
diabetes, published in 1997, lowered the level of
fasting serum glucose for the clinical diagnosis of
diabetes from 140 to 126 mg/dL and defined serum
glucose values between 110 and 125 mg/dL as
impaired fasting glucose. Using the laboratory test
data for the sample of NHANES cases that were
given fasting serum glucose tests, the prevalence
rates were calculated by gender, race, and age
using all tested cases and those in the lowest
quartile of SES. These estimates of undiagnosed
diabetes were then applied to the inmate population. Table 13 reports the predicted number of
additional cases of diabetes using the baseline
model and the lower threshold serum glucose
level. Table 14 reports the predicted number of
additional cases using the low SES model and the
lower threshold serum glucose level.
The baseline model and the new guidelines for
diagnosing diabetes (126 mg/dL) together project
22,233 more diabetics in the inmate population
in addition to the 32,984 projected with the baseline model and the older 140 mg/dL diagnostic

46
Table 10. Expected Number of Cases of Diabetes in the State Prison Population:
Low SES Estimates (serum glucose >140mg/dL)
White 3.1
Age

Male 3.2

#19

Black 3.0

Female 2.6

Male 3.0

Hispanic 1.2

Female 3.5

Male 1.1

Female 3.3

0

0

229

0

41

0

20–29

922

0

4,452

151

154

11

30–39

2,626

209

2,706

434

328

130

40–49

3,818

245

3,438

276

529

118

50–59

2,429

97

1,173

103

526

35

60+

1,111

38

994

43

245

7

10,906

589

12,992

1,007

1,823

301

Total

Table 11. Expected Number of Cases of Diabetes in State Prisons, Federal Prisons, and Local Jails:
Baseline Estimates (serum glucose >140 mg/dL)
State
Prisons

Federal
Prisons

11,683

7,381

1,231

3,073

3,860,357

704

361

44

299

Black male

518,147

15,628

10,570

833

4,225

Black female

855,714

1,380

720

81

580

Hispanic male

230,393

3,099

1,753

559

787

Hispanic female

393,971

490

230

77

183

Total

9,291,426

32,984

21,015

2,825

9,147

Rate

4.9

Sex and Race

National

White male

3,432,634

White female

All
Incarcerated

2.1

2.0

Local Jails

3.0

1.8

Table 12. Expected Number of Cases of Diabetes in State Prison, Federal Prison and Local Jails:
Low SES Estimates (serum glucose >140 mg/dL)
State
Prisons

Federal
Prisons

17,410

10,906

1,811

4,695

5,214,549

1,139

588

74

477

563,277

19,236

12,991

983

5,262

1,006,612

1,943

1,006

109

828

Hispanic male

243,549

3,193

1,823

567

804

Hispanic female

463,221

636

301

96

239

11,825,107

43,557

27,615

3,640

12,305

Sex and Race

National

White male

4,333,899

White female
Black male
Black female

Total
Rate

6.2

All
Incarcerated

2.8

2.7

2.8

Local Jails

2.4

47
Table 13. Expected Number of Additional Cases of Diabetes:
Baseline Estimates (fasting serum glucose 126–139 mg/dL)
State
Prisons

Federal
Prisons

6,402

4,037

728

1,637

1,721,532

310

162

21

128

Black male

229,548

8,952

6,002

482

2,467

Black female

482,871

1,192

606

64

522

Hispanic male

227,554

5,008

2,889

759

1,359

Hispanic female

303,596

369

172

66

131

Total

5,150,841

22,233

13,868

2,120

6,244

Rate

2.7

1.4

1.3

2.2

1.2

Sex and Race

National

White male

2,185,740

White female

All
Incarcerated

Local Jails

Table 14. Expected Number of Additional Cases of Diabetes: Low SES Estimates
(fasting serum glucose 126–139 mg/dL)
Sex and Race

National

White male

2,635,929

White female

All
Incarcerated
7,163

State
Prisons

Federal
Prisons

4,535

828

Local Jails
1,801

2,644,042

350

183

24

142

Black male

448,861

14,946

10,200

765

3,981

Black female

806,081

1,630

845

89

696

Hispanic male

276,447

5,678

3,281

885

1,511

Hispanic female

477,591

623

295

103

226

Total

7,288,951

30,390

19,339

2,694

8,357

Rate

3.8

2.0

1.9

2.8

1.6

criterion (see table 13). The new criterion for
diagnosing diabetes increases the projected
prevalence among inmates by 67 percent to a total
of 55,217 (3.5/100) cases among all inmates. The
increased prevalence is largest among inmates of
Federal prisons, where more than 5 percent of
inmates are projected to be diabetic.

level of serum glucose from $140 to $126 mg/dL
for the clinical diagnosis of diabetes, but they also
included the category of “impaired fasting glucose,”
which is defined as a fasting serum glucose from
110 to 125 mg/dL. Tables 15 and 16 show the
number of inmates with impaired fasting glucose
projected by the baseline and low SES models.

The increase in the prevalence of diabetes is
even greater using the new diagnostic standard
and the low SES model (see table 14). Nearly 70
percent more diabetics are projected in the inmate
population, giving a projected total of 73,947
(4.8/100). Most of the additional cases are predicted
to occur among males and black inmates with the
greatest increase in prevalence in Federal prisons.
The 1997 diagnostic criteria not only lowered the

Unlike with diabetes, there is little difference in
the number of inmates with impaired fasting
glucose projected by the baseline and low SES
models. Both models predict between 78,000
(5.0/100) and 80,000 (5.2/100) inmates to have
impaired fasting glucose, with about 60 percent of
the cases being in State prisons, 12 percent in
Federal prisons, and 28 percent in local jails.

48
Table 15. Expected Number of Cases of Impaired Fasting Glucose:
Baseline Estimates (fasting serum glucose 110–125 mg/dL)
Sex and Race

National

All
Incarcerated

State
Prisons

Federal
Prisons

Local Jails

White male

6,755,874

33,152

20,784

2,953

9,423

White female

4,267,485

661

344

43

274

Black male

614,312

24,400

16,736

1,165

6,499

Black female

714,564

1,841

939

99

803

1,067,648

17,471

10,341

2,268

4,862

Hispanic male
Hispanic female
Total
Rate

369,594

483

231

71

181

13,789,477

78,008

49,375

6,599

22,042

5.0

4.8

6.9

4.3

7.3

Table 16. Expected Number of Cases of Impaired Fasting Glucose:
Low SES Estimates (fasting serum glucose 110–125 mg/dL)
Sex and Race

National

All
Incarcerated

21,067

Federal
Prisons
2,940

Local Jails

White male

6,700,284

White female

4,239,662

678

353

45

280

615,687

26,619

18,213

1,266

7,140

Black male

33,560

State
Prisons

9,560

Black female

716,207

1,892

964

100

828

Hispanic male

608,166

16,641

9,852

2,145

4,645

Hispanic female

345,101

483

230

68

185

13,225,107

79,873

50,679

6,564

22,638

5.2

4.9

6.9

Total
Rate

7.0

Table 17 summarizes the results obtained from
the Low SES model. The pre-1997 definition of
clinical diabetes (fasting serum glucose $140
mg/dL) predicts about 43,500 cases of diabetes in
the inmate population, while the new diagnostic
criteria (fasting serum glucose $126 mg/dL)
predicts about 30,000 more cases. When those
predicted to have impaired fasting glucose are
added, more than 150,000 inmates are projected
to have abnormal glucose metabolism.

Hypertension
The large decline in cardiovascular disease
mortality rate that began in the late 1960s,
particularly the decline in stroke mortality, is
largely due to better diagnosis and treatment of
hypertension.8 Nevertheless, hypertension remains

4.4

a significant health problem and a leading cause
of heart disease, stroke, and renal failure. Hypertension and its consequences disproportionately
affect blacks and individuals of low socioeconomic status. Accordingly, even with adjustments for age, the prevalence of hypertension is
expected to be a significant health problem among
the incarcerated population.
The NHANES–III Adult Interview asked
respondents if they were ever told they had high
blood pressure. In addition, interviewers were
trained to take and record multiple blood pressure
measurements. Hypertension projections were
compiled from self-reports of a history of high
blood pressure and blood pressure measurements
taken according to protocols recommended by the
American Heart Association. Hypertension was

49
Table 17. Expected Number of Inmates with Abnormal Glucose Metabolism: Low SES Estimate
Serum Glucose (mg/dL)

All Incarcerated

State Prisons

Federal Prisons

Local Jails

$140

43,557

27,615

3,640

126–139

30,390

19,339

2,694

8,357

110–125

79,873

50,679

6,564

22,638

153,820

97,633

12,898

43,300

Total

defined according to JNC–VI criteria ($140
mmHg systolic and/or >90 mmHg diastolic) using
the mean systolic and mean diastolic pressures
from multiple readings from the adult household
survey and/or the physical examination.9 Also
included among those defined as hypertensive
were patients who reported a diagnosis of
hypertension in the adult household interview.

12,305

Tables 20 and 21 show the number of inmates
projected to have hypertension based on the
baseline and low SES estimates of the prevalence
of hypertension in the U.S. population. The
projected race- and gender-specific rates among
inmates are relatively low, reflecting the younger
age distribution of the incarcerated population.
Although 24.6 percent of whites in the general
population have hypertension (see table 18), the
rate among white inmates in State prisons
projected by the baseline model is only 16.1
percent (see table 20). The prevalence rates for
hypertension for blacks and Hispanics in the
general U.S. population are 30.2 percent and 18.0
percent (see table 18); the projected rates among
the incarcerated population for these groups are
18.6 percent for blacks and 11.1 percent for
Hispanics (see table 20).

Table 18 gives gender-, race-, and age-specific
rates of hypertension for the U.S. population.
More than 30 percent of the black population is
hypertensive compared to about 25 percent of
whites and 18 percent of Hispanics. The rates
are higher for females and increase with age,
particularly after age 30. More than one-half of
blacks older than 50 are hypertensive. Table 19
shows the gender-, race-, and age-specific
prevalence rates for hypertension in the lowest
SES quartile of the U.S. population. In the lowest
quartile of SES, hypertension rates for blacks are
nearly 30 percent higher than for whites.

Table 21 gives prevalence rates for hypertension
derived from the lowest quartile of SES in the
U.S. population and applied to State prisons.

Table 18. Baseline Hypertension Rates in the United States (per 100)
White 24.6
Age

Male 23.7

Black 30.2

Female 25.5

Male 27.5

Hispanic 18.0

Female 32.3

Male 16.7

Female 19.3

#19

7.3

5.1

2.5

5.5

1.9

2.7

20–29

8.8

12.0

12.8

10.5

5.0

9.0

30–39

15.3

11.2

19.9

21.5

13.9

13.7

40–49

26.2

18.5

32.8

40.8

17.9

24.0

50–59

36.2

34.3

53.2

55.9

44.4

26.8

60+

41.0

50.6

55.8

66.8

36.1

51.2

50
Table 19. Low SES Hypertension Prevalence Rates in the United States (per 100)
White 31.8
Age
#19

Male 26.9

Black 32.9

Female 35.3

Male 27.5

Hispanic 20.0

Female 36.8

Male 18.9

Female 21.0

10.0

4.0

2.1

9.6

2.9

3.1

20–29

9.6

17.5

12.6

11.4

6.7

9.6

30–39

19.3

18.7

16.9

21.6

17.0

15.8

40–49

27.9

33.1

37.0

56.2

15.2

24.0

50–59

48.3

37.7

50.6

64.3

51.6

27.3

60+

40.7

53.5

55.1

74.2

42.2

57.3

Table 20. Expected Number of Hypertensives in the State Prison Population: Baseline Estimates
White 16.1
Age
#19

Male 16.3

Black 18.6

Female 13.9

Male 18.5

Hispanic 11.1

Female 19.6

Male 10.9

Female 13.8

576

23

573

19

111

2

20–29

11,591

1,064

24,775

1,321

3,858

332

30–39

18,264

1,019

31,673

2,667

7,603

496

40–49

14,290

604

16,341

1,250

3,264

325

50–59

7,327

347

4,691

343

2,458

65

60+

3,797

140

3,444

118

470

18

55,845

3,197

81,497

5,718

17,764

1,238

Total

Table 21. Expected Number of Hypertensives in the State Prison Population: Low SES Estimates
White 19.2
Age
#19

Male 19.0

Black 17.7

Female 21.2

Male 17.7

Hispanic 14.0

Female 17.8

Male 14.0

789

18

482

24

20–29

12,645

1,551

24,388

1,585

5,170

354

30–39

23,039

1,701

26,899

1,602

11,213

572

40–49

15,217

1,080

18,434

1,489

2,826

325

50–59

9,775

381

4,462

391

2,856

66

60+

3,769

148

3,401

118

550

21

65,234

4,879

78,066

5,209

22,785

1,340

Total

Although the low SES projected rates of
hypertension for whites and Hispanics in State
prisons increase by about 3 percent from the
baseline model, the rate for blacks in State prisons
actually decreases by nearly 1 percent, from 18.6
to 17.7 percent. These differences are related to
the age distributions of whites, blacks, and

170

Female 14.9
2

Hispanics in the State prison population (blacks in
State prisons tend to be younger than whites and
Hispanics). The baseline model predicts that more
than 165,000 inmates with hypertension are in
State prisons. The number of inmates projected by
the low SES model is about 7 percent higher—
177,513 hypertensive inmates.

51
Tables 22 and 23 show the number of hypertensive
inmates that are predicted in State prisons,
Federal prisons, and local jails. The baseline
projection model (table 22) predicts that State
prisons, Federal prisons, and local jails together
house more than one-quarter of a million inmates
with hypertension. In spite of the large number,
the rate of hypertension among inmates is predicted to be about 66 percent of the rate for the
general population. This relatively low rate is a
consequence of the disproportionate share of
young persons, in whom hypertension rates are
lowest, in the prison population. The lowest rates
are predicted for local jails (14.7/100), followed
by State prisons (16.0/100), with the highest rate
predicted to occur in Federal prisons (19.2/100),
which house the oldest inmates.
The low SES model projects more than 283,000
inmates with hypertension. Although this is 9
percent higher than the baseline model projections
(n = 259,170), there are no striking differences
between the two models. The prevalence of

hypertension is still predicted to be highest among
Federal prison inmates (21.6/100) and lowest
among local jail inmates (16.1/100). Regardless
of which projection model is used and in spite
of the finding that the projected prevalence of
hypertension among inmates is lower than in the
general population (as a result of differences in
age composition), hypertension is a significant
problem among inmates. At least one-quarter of a
million inmates are predicted to have hypertension.
Both the baseline and low SES projection models
may understate the prevalence of elevated blood
pressure and hypertension because neither model
takes into account the effects of incarceration on
stress and the body’s reaction to it, which is likely
to elevate blood pressure. Hypertension is
projected to be a significant problem in the
incarcerated population in terms of the number of
inmates affected and the demand and need for
health services, particularly if the sequelae of
hypertension, including heart disease, stroke, and
renal failure, are to be in the prison and in the
community when inmates are released.

Table 22. Expected Number of Hypertensives in the Incarcerated Population: Baseline Estimates
Sex and Race

National

All
Incarcerated

Federal
Prisons

55,845

7,521

Local Jails

White male

17,298,916

White female

20,511,964

6,170

3,196

306

2,669

2,598,315

120,003

81,498

5,742

32,764

Black male

89,428

State
Prisons

26,602

Black female

3,741,008

11,107

5,717

564

4,825

Hispanic male

1,132,968

29,825

17,764

3,858

8,202

Hispanic female

1,383,541

2,637

1,237

318

1,082

Total

46,666,712

259,170

165,257

18,309

76,144

Rate

24.5

16.7

16.0

19.2

14.7

Table 23. Expected Number of Hypertensives in the Incarcerated Population: Low SES Estimates
National

All
Incarcerated

White male

19,476,236

White female

25,437,936
2,548,491

Sex and Race

Black male

State
Prisons

Federal
Prisons

104,836

65,235

8,813

9,438

4,879

461

4,098

115,207

78,064

5,615

31,528

Local Jails
30,788

Black female

4,125,784

12,866

5,208

653

5,593

Hispanic male

1,368,835

37,911

22,788

4,621

10,505

Hispanic female

1,495,490

2,847

1,339

339

1,169

Total

54,452,772

283,105

177,513

20,502

83,681

Rate

28.6

18.3

17.2

21.6

16.1

52

Heart Disease
Heart disease, particularly coronary artery disease
or ischemic heart disease, is the leading cause of
death in the United States. Although the rate of
death from heart disease has declined since 1968
due to advances in diagnosis and treatment and,
most importantly, changes in behavior including
reduced smoking, less fat and cholesterol in the
daily diet, and an increase in the percentage of the
population who engage in routine exercise, heart
disease continues to account for approximately
50 percent of the deaths in the United States each
year. Rates of heart disease are higher in blacks
than whites and in men than women, and they
increase with age. Consequently, as the number of
inmates older than 50 increases, heart disease in
the inmate population will become increasingly
prevalent.

administered by an interviewer, includes nine
questions about pain or discomfort in the chest
including when pain occurs (i.e., when hurrying
or walking up hill); how long it lasts; how and
when it is relieved, and in what part of the chest,
neck, and arms it is located. Scoring algorithms
enable the pain to be classified as angina (i.e., due
to myocardial ischemia) or not, to be graded for
severity, and to be classified associated or not
associated with possible myocardial infarction.
In studies of the ability of the Rose Questionnaire
to differentiate between patients with coronary
artery disease and those without, the sensitivity
was found to be 81 percent and the specificity
was found to be 97 percent.11 In other words, the
Rose Questionnaire correctly identified 81
percent of patients with documented coronary
artery disease and 97 percent of those without
coronary artery disease.

The NHANES–III interview included the Rose
Questionnaire, which was developed more than
30 years ago to distinguish between cardiac and
noncardiac chest pain.10 The questionnaire,

Tables 24 and 25 show the prevalence rates for
coronary artery disease calculated from the Rose
Questionnaire using the baseline and low SES
models. Rates are higher among blacks than

Table 24. Baseline Heart Disease Prevalence Rates in the United States (per 100)
White 6.1

Black 6.6

Hispanic 5.2

Age

Male 6.3

Female 5.8

Male 5.4

Female 7.6

Male 4.2

Female 6.2

#19

0.0

2.5

1.1

4.1

1.4

1.9

20–29

1.0

2.6

3.3

3.9

2.4

3.9

30–39

1.7

2.3

2.4

5.0

4.2

5.8

40–49

4.4

4.9

4.1

6.7

4.1

6.9

50–59

8.3

4.9

9.1

13.3

5.0

6.9

18.3

12.7

15.3

15.3

12.6

14.3

60+

Table 25. Low SES Heart Disease Prevalence Rates in the United States (per 100)
White 10.3
Age

Male 10.8

Black 8.6

Female 9.9

Male 7.6

Hispanic 6.1

Female 9.3

Male 5.1

Female 7.0

#19

0.0

2.9

1.3

5.1

2.6

1.2

20–29

2.5

2.9

4.6

3.4

3.2

2.7

30–39

2.7

5.8

3.2

6.4

2.1

10.4

40–49

11.0

12.1

6.7

8.2

6.0

5.3

50–59

12.5

7.6

16.3

17.3

7.4

11.8

60+

21.9

15.7

16.6

17.7

16.9

13.9

53
among whites and Hispanics, and, except among
whites, are higher among females than males.
The higher rates observed among both black and
Hispanic females relative to males of the same
age in those racial and ethnic groups reflect
false positives arising from the difficulty of
identifying coronary artery disease in females
by history of chest pain alone without exercise
stress testing and the “gold standard” of
coronary angiography. Although the predictions
from the Rose Questionnaire overstate the
prevalence of coronary artery disease in
females, the overall impact on the number of
prison inmates with coronary artery disease is
small owing to the relatively small number of
women in the prison population.

disease. Nearly one-half (45 percent) of the
heart disease is predicted to occur among black
males, but less than 20 percent is predicted to be
in inmates aged 50 or older.
Table 27 shows the expected number of cases of
heart disease among inmates in State prisons
predicted by the Rose Questionnaire according
to the low SES model. The number of cases of
heart disease among State prison inmates using
the low SES model projections (46,187) is
nearly 50 percent higher than under the baseline
model, but the distribution across race, age, and
gender does not change.
Tables 28 and 29 give the expected number of
cases of coronary heart disease among all
incarcerated individuals using the baseline and
low SES models. The baseline model projects a
total of 49,230 cases of coronary heart disease
in the incarcerated population, with just more
than one-half of those cases occurring in State

Table 26 shows the expected number of cases of
heart disease in the State prison population
according to the baseline model using the Rose
Questionnaire. More than 31,000 inmates in
State prisons are predicted to have heart

Table 26. Expected Number of Cases of Heart Disease in State Prisons: Baseline Estimates
White 6.1
Age
#19

Male 2.7

Black 3.3

Female 3.0

Male 3.2

Hispanic 3.4

Female 4.9

Male 3.3

Female 5.1

0

11

252

14

82

1

20–29

1,317

231

6,387

491

1,852

144

30–39

2,029

209

3,820

620

2,297

210

40–49

2,400

160

2,043

205

748

80

50–59

1,680

50

802

82

277

17

60+

1,695

35

944

27

164

5

Total

9,121

696

14,248

1,439

5,420

457

Table 27. Expected Number of Cases of Heart Disease in State Prisons: Low SES Model Estimates
White 5.0
Age
#19

Male 5.0

Black 4.6

Female 5.7

Male 4.6

Hispanic 3.5

Female 5.6

Male 3.4

Female 6.5

0

13

298

18

152

1

20–29

3,293

257

8,903

428

2,469

100

30–39

3,223

528

5,093

794

1,149

377

40–49

6,000

395

3,338

251

1,094

72

50–59

2,530

77

1,437

106

410

29

60+
Total

2,028

43

1,025

31

220

5

17,074

1,313

20,094

1,628

5,494

584

54
Table 28. Estimated Number of Cases of Heart Disease in the Incarcerated Population:
Baseline Estimates
State
Prisons

Federal
Prisons

14,289

9,121

1,439

3,729

4,729,728

1,354

696

66

592

Black male

509,605

20,780

14,249

930

5,601

Black female

881,048

2,771

1,439

135

1,197

Hispanic male

311,225

9,063

5,420

978

2,665

Hispanic female

444,128

973

457

107

410

Total

11,479,714

49,230

31,382

3,655

14,194

Rate

6.03

2.5

3.8

2.7

Sex and Race

National

White male

4,603,980

White female

All
Incarcerated

3.2

Local Jails

Table 29. Expected Number of Cases of Heart Disease in the Incarcerated Population:
Low SES Estimates
Sex and Race

National

All
Incarcerated

State
Prisons

Federal
Prisons

Local Jails

White male

6,802,573

26,978

17,074

2,577

7,328

White female

7,230,465

2,563

1,313

133

1,117

691,860

29,488

20,095

1,373

8,020

Black male
Black female

1,040,499

3,167

1,628

156

1,382

Hispanic male

501,800

9,364

5,494

858

2,837

Hispanic female

523,364

1,056

582

138

492

Total

16,790,561

72,616

46,186

5,235

21,176

Rate

8.8

4.7

4.5

5.5

prisons (see table 28). Although the greatest
number of cases is predicted to be in State
prisons, the highest predicted rate of coronary
heart disease is in Federal prisons (3.8 cases per
100 inmates). Given a sensitivity of 0.87 and a
13-percent false negative rate for the Rose
Questionnaire, the adjusted number of cases
from the baseline model is about 56,600.
The low SES model projects 72,616 inmates
with coronary heart disease in the incarcerated
population (see table 29). Adding the false
negatives from the Rose Questionnaire raises this
estimate to about 83,500. The estimate of the
relative prevalence of coronary heart disease
among black and white males generated by the
low SES model differs significantly from that
generated by the baseline model. The baseline
model predicts about three cases of heart disease
among black male inmates for every two cases

4.1

among white male inmates. In contrast, the low
SES model predicts about a 1:1 ratio of cases for
black and white male inmates with virtually no
change in the projected number of cases of
coronary heart disease in Hispanic male inmates.

Conclusion
Statistical estimation and projection models are
only as good as their underlying assumptions and
the data that are used as input. Two models have
been applied here with differing assumptions
concerning the demographics and social characteristics of the incarcerated population. In the
baseline model, race- and gender-specific ageadjusted disease prevalence rates in the inmate
population were projected from prevalence rates
calculated from the NHANES–III survey of the
noninstitutionalized civilian U.S. population of
the United States. These projections constitute a

55
baseline estimate of disease prevalence. They
predict the number of cases of disease in the
inmate population if that population is comparable
to the noninstitutionalized population.
Clearly, the institutionalized and noninstitutionalized
populations differ in gender and race composition
and the distribution of behaviors, attitudes, and
other risk factors associated with the distribution
of disease in the human population. In an effort
to account for at least some of the differences
between the institutionalized and noninstitutionalized populations, a subsample of the
NHANES–III data was analyzed involving
persons currently on welfare or other public
assistance. This group represents approximately
66 million Americans and approximates the
lowest quartile of socioeconomic status in the
U.S. population. Because disease prevalence,
particularly asthma, diabetes, hypertension, and
heart disease, is greater among lower SES
individuals, the projections of disease prevalence
obtained from this subsample probably more
accurately reflect the real health status of the inmate
population. Nonetheless, key variables related to
disease prevalence (i.e., educational status, health
behaviors) are not included in the model, which
affects the resulting prevalence estimates.
The prevalence estimates may also be biased by
differences in definitions of disease. Self-reported
asthma rates measured as the response to a single
question posed by an interviewer in the context of a
national health survey such as NHANES are likely
to be considerably higher than clinically diagnosed
asthma rates recorded in patients’ medical records.
Accordingly, the estimates of asthma prevalence and
the expected number of cases projected by the
baseline and low SES models can be compared to
clinically diagnosed prevalence rates of asthma in
the incarcerated population only with caution.
Inmates with a history of asthma before
incarceration may not be recorded as having asthma
in the prison system unless and until they have an
attack that comes to the attention of prison health
care workers. Mild intermittent and mild persistent
asthmatics would not necessarily be detected in a
medical record review. Consequently, estimates of
prevalence of asthma in the incarcerated population
are likely to understate the true prevalence of asthma

and be quite a bit smaller than the estimates from
self-reports as made here.
The same caveats do not apply to the estimates
of prevalence and projected number of cases of
diabetes and hypertension. The prevalence estimates
for these conditions were taken from laboratory
measurements according to established measurement guidelines. The analysis of diabetes was
compared to figures reported by the National
Institutes of Health that were based upon the
NHANES–III data. The estimates of prevalence
rates conformed to those reported by the NIH
authors, validating the measurement of diabetes and
impaired fasting glucose. No comparable analysis
exists for the prevalence of hypertension.
Prevalence rates were calculated according to
established diagnostic criteria using the medical
examination record and the mean systolic and mean
diastolic values from multiple measurements of
blood pressure. Consequently, the estimated
prevalence rates and projected number of cases of
impaired glucose metabolism and hypertension in
the incarcerated population are based upon valid
measurement and methodology. These estimates and
projections may differ from the actual prevalence
and number of cases in the incarcerated population
to the extent that the assumptions underlying the
baseline and low SES models are flawed.
Rates of coronary heart disease calculated from
responses to the Rose Questionnaire apply only to
the prevalence of ischemic heart disease (e.g.,
coronary artery disease). They do not capture other
forms of heart disease (e.g., valvular disease,
congestive heart failure). The Rose Questionnaire
has a known sensitivity of 0.81 and a known
specificity of 0.97. That is, the questionnaire will
detect 81 percent of cases with ischemic heart
disease, and will correctly classify as negative
97 percent of cases without disease. Although
only 81 percent of individuals with coronary
artery disease test positive on the Rose Questionnaire, its sensitivity is likely higher than
that achieved with one or two questions about a
previous diagnosis of heart disease in an inmate
intake assessment. At least some cases defined as
positive on the Rose Questionnaire are preclinical
and would not be detected in a history and physical
examination in the prison setting.

56
Although the Rose Questionnaire will detect more
true cases of heart disease than self-reports of a
physician diagnosis, projections of the number of
cases of heart disease in the incarcerated population
are not without peril. The Rose Questionnaire is
sensitive to ischemic heart disease (ICD 410–414.9)
and does not adequately identify other forms of
cardiac disease. Most important, it is particularly
difficult to identify coronary artery disease in
women based on a history of chest pain alone.
Several studies have shown that chest pain has a
poor positive predictive value for diagnosing
ischemic heart disease in women. Similarly, many
elderly patients experience the pain associated
with myocardial ischemia differently than
younger patients. Elderly patients experiencing
myocardial ischemia often report pain indicative
of gastroesophageal reflux disease or pain in the
middle of their back, as opposed to the more
common report among younger patients of
substernal pain radiating into the neck, jaw, and
left arm.
The Rose Questionnaire may not detect forms of
cardiac disease other than myocardial ischemia,
and it may overstate coronary disease prevalence
among women inmates and understate coronary
heart disease prevalence among older inmates.
Its application in the NHANES–III data to the
incarcerated population, however, provides the first
estimates of the prevalence of coronary heart
disease among inmates.

Notes
1. The Steering Committee consisted of Edward
Harrison, National Commission on Correctional Health
Care; R. Scott Chavez, M.P.A., National Commission
on Correctional Health Care; Robert B. Greifinger,
M.D., Principal Investigator; B. Jaye Anno, Ph.D.,
Carlton A. Hornung, Ph.D., M.P.H., University of
Louisville School of Medicine; John Miles, M.P.A.,
Centers for Disease Control and Prevention; Cheryl
Crawford, M.P.A., J.D., National Institute of Justice;
Andrew Goldberg, M.A., National Institute of Justice;
Marilyn Moses, M.S., National Institute of Justice; and
Laura Winterfield, Ph.D., National Institute of Justice.
2. McDonald, D.C., Managing Prison Health Care
and Costs, Issues and Practices, Washington, DC: U.S.
Department of Justice, National Institute of Justice,
1995, NCJ 152768.

3. National Center for Health Statistics, National
Health and Nutrition Examination Survey III.
1988–1994 [NHANES–III], Washington, DC: U.S.
Department of Health and Human Services, Centers for
Disease Control and Prevention, 1996.
4. Adams, P.F., and M.A. Marano, “Current Estimates
From the National Health Interview Survey, 1994,”
Vital Health Statistics 10(1995): 94.
5. National Asthma Education and Prevention
Program, Expert Panel Report 2: Guidelines for the
Diagnosis and Management of Asthma, Bethesda, MD:
National Institutes of Health, National Heart, Lung,
and Blood Institute, 1997, NIH pub 97–4051.
6. Harris, M.I., K.M. Flegal, C.C. Cowie, M.S.
Eberhardt, D.E. Goldstein, R.R. Little, H.M.
Wiedmeyer, and D.D. Byrd-Holt, “Prevalence of
Diabetes, Impaired Fasting Glucose, and Impaired
Glucose Tolerance in U.S. Adults: The Third
National Health and Nutrition Examination Survey,
1988–1994,” Diabetes Care 21(4)(1998): 518–524.
7. The Expert Committee on the Diagnosis and
Classification of Diabetes Mellitus, “Report of the
Expert Committee on the Diagnosis and Classification
of Diabetes Mellitus,” Diabetes Care 20(7)(1997):
1183–1197.
8. National Center for Health Statistics, Health, United
States, 1996, Hyattsville, MD: U.S. Public Health
Service, 1997.
9. Joint National Committee on Prevention, Detection,
Evaluation and Treatment of Low Blood Pressure, The
Sixth Report of the Joint National Committee on
Prevention, Detection, Evaluation and Treatment of
Low Blood Pressure, Bethesda, Maryland: National
Institutes of Health, National Heart, Lung, and Blood
Institute, 1997, NIH pub 98–4080.
10. Rose, G.A., and H. Blackburn, Cardiovascular
Survey Methods, Geneva: World Health Organization,
1968.
11. Heyden, S., A.G. Bartel, E. Tabesh, J.C. Cassel,
H.A. Tyroler, J.C. Cornoni, and C.G. Hames, “Angina
Pectoris and the Rose Questionnaire,” Archives of
Internal Medicine 128 (6)(1971): 961–964.

57

Prevalence Estimates of Psychiatric
Disorders in Correctional Settings

Bonita M. Veysey, Ph.D., and Gisela Bichler-Robertson, M.A., Rutgers University School of Criminal
Justice

Overview
The true prevalence and incidence of psychiatric
disorders in criminal justice populations have
been difficult to estimate. There have been several
significant barriers to gathering data for these
estimations. First and foremost, well-designed and
rigorous epidemiological studies are costly and
labor intensive. Correctional facilities are currently overwhelmed by the numbers of inmates
being processed through the system. This pressure makes it difficult, if not impossible, for
researchers to gain entry and administrative
support for large studies of incarcerated
populations. Each point of the criminal justice
system presents different difficulties in determining rates of disorder. Jail psychiatry, for
example, is concerned with identifying and
treating acute episodes. Because jails have
constant, high-volume turnover, prevalence
studies of a single-point-in-time census are
impossible. Further, the projected utilization of
jail services must be estimated on the need of a
large percentage of individuals who may remain

for less than 48 hours. Basing prevalence and
utilization estimates on a longer term group does
not necessarily reflect the actual need for care for
this population. Epidemiological studies of jail
populations, therefore, should be made on
admissions (i.e., bookings). Only one such study
has been conducted to date.1 All other estimates
of mental illnesses in jails have been based on
persons using or requiring mental health services
who were already identified by jail personnel.
The study by Teplin, Abram, and McClelland2
was conducted in the Cook County (Chicago),
Illinois jail and represents the best estimates to
date (see table 1). Analyses were conducted on
males and females separately, but have been
weighted to represent the racial/ethnic composition of the jail.3 As table 1 shows, the rates of
disorders differ substantially among men and
women. These data reveal that acute symptoms
of serious mental illnesses requiring treatment
are present in about 6 percent of males4 and 15
percent of females5 at booking.

Table 1. Estimated 6-Month and Lifetime Diagnosis (Cook County)
Current Illness
Diagnosis
Schizophrenia

Female

Lifetime Illness

Male

Female

Male

1.8

3.0

2.5

3.8

13.7

3.4

16.9

5.1

Bipolar manic

2.2

1.2

2.6

2.2

Dysthymia

6.5

—

9.6

8.5

22.3

—

33.5

—

Major depression

Post-traumatic stress

Anxiety/other
3.5
11.6
4.0
21.0
Source: Teplin, L.A., “Psychiatric and Substance Abuse Disorders Among Male Urban Jail Detainees,” American Journal of
Public Health 84(2)(1994): 290–293; Teplin, L.A., K.M. Abram, and G.M. McClelland, “Prevalence of Psychiatric Disorders
Among Incarcerated Women: 1. Pretrial Jail Detainees,” Archives of General Psychiatry 53(8)(1996): 505–512.

58
Prison facilities present fewer problems in
gathering data and estimating the need for
services. First, prisons have relatively stable
populations. Therefore, it is possible to conduct a
census-based study. Most prisons do not have the
onsite capacity to provide psychiatric inpatient
hospitalization. Ninety-two percent of State
prisons do not provide inpatient care within the
facility, and 2.3 percent of the inmate population
is in inpatient or residential care at any given
time.6 The challenge for research, therefore, is to
account for the individuals who are currently
offsite due to an inpatient stay.
Like estimates of mental illness in jails, most
estimates of mental illnesses in prisons are based
on those utilizing services. These studies typically
estimate that between 6 and 15 percent of the
prison population has a serious and persistent
mental illness. Recent epidemiological studies of
specific disorders indicate, however, that 22.5
percent of a male prison population exhibited
symptoms of major depression.7 Among opiatedependent males, anxiety disorders were found in
32 percent of the population and affective
disorders were found among 25 percent of the
population.8 Jordan and colleagues conducted a
study of female prisoners and found statistics
similar to the Teplin, Abram, and McClelland
1996 study.9
The Epidemiological Catchment Area study10
conducted during the early 1980s estimated the
prevalence of mental disorders in the American
public. In addition to the large community sample, the study also contained samples from
institutionalized populations, including prison
inmates. This study revealed that the 1-year
prevalence rate of serious mental illnesses was
as follows: 5 percent exhibited symptoms of
schizophrenia, 6 percent suffered from bipolar
disorder, and 9 percent from unipolar
depression.11
To date, no estimates have been made regarding
the prevalence of mental illness in community
corrections populations. One study of State
probation and parole authorities estimated that the
percentage of probationers with mental illnesses

varied from 3 to 23 percent (with a mean of 6
percent) across States that maintained records,
and that the percentage of parolees with mental
illnesses varied from 1 to 11 percent (with a mean
of 5 percent) across these same States.12 This
study is not comparable to the others noted above
and does not estimate the true prevalence of
mental disorders in these community corrections
populations. No scientifically rigorous prevalence
study has been conducted to date on this population.
This is primarily because community corrections
departments have no obligation to provide mental
health services or access to those services. Therefore, these departments need not know the psychiatric status of persons under their supervision.

National Comorbidity Survey
To remain consistent with the methodology
employed by the other monographs in this report,
a national community-based epidemiological
study was used to estimate psychiatric disorders
in correctional settings.
Taking advantage of the wealth of secondary data
available for social science research, this study
used the U.S. National Comorbidity Survey
(NCS)13 to generate estimated prevalence rates
for various diagnoses among the incarcerated
population. The NCS was mandated by Congress
to provide information about the prevalence and
risk factors of substance abuse and psychiatric
disorders among the general population. This
landmark survey is the first nationally representative psychiatric epidemiologic survey based on
a community sample.
Using a comprehensive diagnostic interview,
trained interviewers who were not clinicians
collected histories of psychiatric symptoms
and use of substances from noninstitutionalized
individuals, many of whom had not been previously diagnosed. The detailed questions combined multiple items based on the American
Psychiatric Association’s Diagnostic and
Statistical Manual (DSM–III–R) with questions
that allow for comparisons with the International
Classification of Diseases (ICD–10). The resulting national sample of 8,098 persons aged 15 to

59
54 was selected from the 48 coterminous States.
General findings suggest that lifetime and recent
psychiatric morbidity are more prevalent than
previously thought. The survey revealed that 48
percent of the sample had at least 1 psychiatric
disorder at some time in their life and 29 percent
had evidence of a disorder within the past year.14

Methodology
Seven diagnoses were examined: psychotic
disorder, major depression, bipolar mania,
dysthymia, post-traumatic stress disorder,
anxiety,15 and antisocial personality disorder. The
prevalence of each of the seven diagnoses was
weighted by age, race, and gender in a manner
similar to that used by Hornung, Greifinger, and
Gadre.16 Using the community-based sample,
three rates (the community sample, the poverty
sample, and the poverty and substance abuse
sample) were estimated for lifetime prevalence
and 6-month prevalence for each diagnosis. Thus,
six tables were created for each diagnosis and
stratified by race and ethnicity, sex, and age
group. (Appendix A displays these tables.) First,
prevalence rates for the entire sample created a
baseline model (n = 7,828).17 Because the lowest
socioeconomic strata of society represent a
disproportionate amount of the incarcerated
population and because poverty and mental
disorder appear to be correlated, a subsample of
respondents with a reported income below the
poverty line was used to create a second set of
prevalence rates (n = 977).18 This second model
is expected to produce superior estimates of
psychiatric diagnosis among inmate populations,
for it provides a closer approximation of the
sociodemographic profile of inmates. A notable
exception is the greater percentage of white-collar
offenders, who are typically from a higher
socioeconomic stratum incarcerated in Federal
institutions. This second set is identified as
“Distressed Rate I.”
Finally, a third set of rates were computed based
on the fact that a majority of arrestees test positive in urine screens for illicit substance use.19
Approximately 65 percent have evidence of at
least 1 substance at the time of arrest. This
statistic does not include those who abused

alcohol, were under the influence of alcohol at the
time of arrest, or were drug addicted but not
recent users. Since the vast majority of jail and
prison inmates abuse substances, a subsample
(n = 247) of those in poverty with a comorbid
substance use disorder were used to estimate rates
of mental illnesses among an extremely distressed
population (Distressed Rate II).
Appendix B displays the cell frequencies for the
three samples. Because small sample sizes can
create unstable estimates, all cells with fewer than
10 cases (shaded areas) are calculated from the
prior table weighted by the marginal rates for race
and sex. Empty cells in the community sample are
assigned a value of 0.1.
From the 39 tables in appendix A, rates were
weighted by the 1995 age, gender, and race
distributions in Federal and State prisons, local
jails, and community corrections populations
consistent with those used by previous researchers.20 Instead of creating point estimates, the
expected prevalence of cases should be taken as
the range of values between two models. Because
jails must focus on acute psychiatric conditions,
jail estimates are based on the 6-month prevalence
rates of each disorder (except antisocial personality disorder) and range from the rates for the
poverty sample (Distressed Rate I) to the rates
for the poverty and substance abuse sample
(Distressed Rate II). State prison rates utilize the
same samples (Distressed Rates I and II), but are
based on lifetime occurrence. Because Federal
prisoners tend to be more economically advantaged, lifetime prevalence rates use the
Community and Distressed Rate I samples.
These same parameters are used for community
corrections populations.

Demographic Characteristics of
Offender Populations
The demographic characteristics of offender
populations vary only moderately across the five
categories of correctional settings listed here
(see table 2).21 Males are disproportionately
represented in all correctional populations,
varying from a high of 94 percent in State prisons

60
to a low of 79 percent under probation supervision.
The racial and ethnic distributions in correctional
populations reflect an overrepresentation of
persons of color. This degree of overrepresentation
differs depending on the setting. More than onehalf of probationers are white, but the proportion
of white inmates incarcerated in correctional
facilities is notably lower. The ethnic and racial
distribution is fairly consistent across facility
type, with at least 60 percent of inmates in each
facility classified as nonwhite. Jails and State
prisons have similar racial and ethnic
distributions. Federal prisons, however, have a
substantially greater proportion of Hispanic
inmates than the other types of correctional
settings.
The age distribution of the inmate populations
varies somewhat across types of correctional
facilities. In general, jails and State prisons have
similar age distributions, except for the larger
percentage of jail detainees under the age of 19.

Federal prisoners are typically older than those
held in other types of facilities. Federal prisons
had the largest proportion of middle-aged and
older inmates. Thirty-eight percent of Federal
inmates are more than 40 years old compared with
17 percent for jails and 18 percent for State
prisons.

Prevalence Estimates of Psychiatric
Morbidity in the General Population
Table 3 shows the prevalence of psychiatric
morbidity in the general U.S. population. Lifetime
occurrence of disorders vary from low-rate disorders, such as schizophrenia (0.8 percent) and
bipolar disorder (1.5 percent) to disorders that
occur at a relatively high rate, such as anxiety
disorders (25 percent), major depression (18
percent), and antisocial personality or conduct
disorder (15 percent). Recent episodes of psychiatric disorders have similar patterns across
diagnostic categories, but at about half the rate
of lifetime prevalence.

Table 2. Characteristics of Inmate Populations, 1995
State/Local
Probation

Local
Jails

State
Prisons

Federal
Prisons

Parole

2,620,560
507,044
1,026,882
100,250
648,921
Number
Gender
% Male
79.1
89.8
93.7
92.8
90.0
% Female
20.9
10.2
6.3
7.2
10.0
Ethnicity
% White
58.3
40.1
33.3
29.9
48.6*
% Black
27.9
43.5
46.5
37.8
42.8
% Hispanic
11.3
14.7
17.0
27.3
—
% Other
2.4
1.7
3.2
5.0
8.6
n/a
n/a
Age
% # 19
10.6
3.7
0.3
% 20–29
39.6
42.7
25.2
% 30–39
34.1
35.5
37.0
% 40–49
13.2
12.9
24.7
% 50+
3.5
5.3
12.8
* Racial distributions in the parole population do not break out persons of Hispanic heritage. These individuals are represented
within the racial categories of white, black and other. Therefore, direct comparisons with other correctional populations are not
possible.
Source: Maguire, K., and A.L. Pastore, eds., Sourcebook of Criminal Justice Statistics, 1996. Washington, DC: U.S. Department
of Justice, Bureau of Justice Statistics, 1997, NCJ 165361.

61
Table 3. Six-Month and Lifetime Prevalence of Diagnoses
Disorder

6-Month Estimates

Lifetime Estimates

Schizophrenia/psychosis

0.4

0.8

Major depression

8.4

18.1

Bipolar (manic)

1.0

1.5

Dysthymia

2.0

7.1

Post-traumatic stress

3.4

7.2

Anxiety
Antisocial personality

Gender
As the rates of psychiatric disorder vary across
diagnostic categories, they also vary by sex, race,
and age. Statistically significant differences
between men and women are evident in both
6-month and lifetime prevalence rates of several
psychiatric disorders (see table 4). Women have
higher rates of major depression, dysthymia, posttraumatic stress disorder, and anxiety disorders.
Men are diagnosed with antisocial personality
disorder (or conduct disorder during childhood)
at nearly three times the rate of women.

Age
Six-month and lifetime prevalence rates of
diagnostic categories vary across the lifespan (see
table 5). In these data, 6-month rates of major
depression and anxiety disorders are significantly
higher among the youngest age category (age 19
and younger) and decrease with age. Six-month
rates of post-traumatic stress disorder are highest
in the 20- to 29-year-old range and decrease
thereafter with age. Significant age differences
also exist in the lifetime occurrence of psychiatric

14.6

24.6

—

14.8

disorders. The prevalence of major depression
and dysthymia increase with age, but the lifetime
rates of anxiety disorders and antisocial personality
or conduct disorders decrease with age.

Race and ethnicity
Table 6 presents 6-month and lifetime prevalence rates of psychiatric disorders by racial and
ethnic category. The NCS data include race and
ethnicity data separately. These data also include
a four-category race and ethnicity variable coded
into “white—non-Hispanic,” “black—nonHispanic,” “Hispanic,” and “other.” Because
the correctional weights break out only white,
black, and Hispanic, the category of “other”
was dropped from these analyses.
Overall, a smaller percentage of black respondents than white or Hispanic respondents met the
criteria for any mental disorder, except schizophrenia. Two diagnostic categories revealed
significant racial and ethnic differences in 6month rates. Blacks and Hispanics had higher
rates of schizophrenia than whites, and Hispanics

Table 4. Six-Month and Lifetime Prevalence Rates of Diagnoses by Gender
6-Month Rate
Disorder

Lifetime Rate

Male

Female

sig

Male

Schizophrenia/psychosis

0.3

0.4

ns

0.8

Female
0.8

sig
ns

Major depression

5.9

10.6

.000

13.5

22.0

.000

Bipolar (manic)

1.1

0.9

ns

1.6

1.5

ns

Dysthymia

1.6

2.4

.010

5.8

8.2

.001

Post-traumatic stress

2.2

4.6

.000

4.8

9.6

.000

10.6

18.2

.000

20.0

28.7

.000

—

—

—

22.5

7.7

.000

Anxiety
Antisocial personality

62
Table 5. Six-Month and Lifetime Prevalence Rates of Diagnoses by Age
6-Month Rate

Lifetime Rate

Disorder

#19

20–
29

30–
39

40–
49

50+

sig

#19

20–
29

30–
39

40–
49

50+

sig

Schizophrenia

0.4

0.5

0.1

0.6

0.4

ns

0.6

1.1

0.6

1.1

0.6

ns

10.5

8.4

8.6

7.9

5.9

.022

14.0

17.0

19.1

19.7

17.1

.000

Bipolar (manic)

1.2

1.1

1.0

1.1

0.6

ns

1.2

1.6

1.7

1.7

0.9

ns

Dysthymia

1.7

1.4

2.2

2.4

2.3

ns

3.8

4.7

7.5

9.5

10.7

.025

Post-traumatic stress

3.0

4.4

3.5

2.7

2.9

.032

5.4

7.7

7.6

7.9

5.6

ns

Anxiety

20.4

15.5

14.1

12.4

12.3

.000

27.2

24.9

25.6

23.0

20.9

.001

Antisocial personality

—

—

—

—

—

—

19.5

17.5

15.2

11.1

8.1

.000

Major depression

Table 6. Six-Month and Lifetime Prevalence Rates of Diagnoses by Race/Ethnicity*
6-Month Rate
Disorder

White

Black

Schizophrenia

0.3

0.7

Major depression

8.2

7.8

Lifetime Rate

Hispanic

sig

White

Black

Hispanic

sig

0.7

.032

0.7

1.2

1.0

ns

11.1

.025

19.0

12.8

17.7

.000

Bipolar (manic)

1.1

0.6

1.0

ns

1.7

0.8

1.6

ns

Dysthymia

2.0

2.2

2.3

ns

7.5

5.1

6.7

.025

Post-traumatic stress

3.5

3.6

2.7

ns

7.3

6.6

7.5

ns

14.7

12.8

16.0

ns

25.3

19.8

25.6

.001

—

—

14.4

13.5

20.1

.000

Anxiety

Antisocial personality
—
—
* Persons of other racial/ethnic groups are not reported here.

had higher rates of major depression than whites
and blacks. Whites had the highest lifetime rates
of major depression and dysthymia, and Hispanics
had the highest rates of antisocial personality
disorder (including childhood conduct disorder).
Rates of anxiety disorders were similar for whites
and Hispanics and significantly lower for blacks.

Level of distress
Not surprisingly, rates of psychiatric disorders
vary directly by level of distress. In comparison
to the general community sample, holding constant the demographic distribution of the sample,
persons living in poverty have higher rates of all
disorders (see table 7). Persons living in poverty
who meet the criteria for substance abuse or
dependence have higher 6-month and lifetime
rates of all disorders than either the general
community or the poverty sample.

In summary, the rates of psychiatric disorders
vary from rare to relatively common. Schizophrenia
and bipolar disorder are relatively rare, but other
diagnoses, such as anxiety and major depression,
affect approximately two of every five Americans
over the course of their lives. Diagnoses also vary
across age, gender, and racial and ethnic categories
and across levels of distress. Because correctional
populations also differ by these factors and the
average length of confinement of offenders,
correctional rates must be weighted. The following section presents the synthetic estimates of
psychiatric disorders for each of the correctional
settings.

Estimated Rates of Psychiatric
Diagnoses in Correctional Populations
As noted earlier, rates were estimated by selecting
either the 6-month (i.e., jail) or the lifetime (i.e.,
State and Federal prisons and community corrections) rates and the lower and higher brackets

63
for the range of estimates based on the theoretically appropriate population samples. Community Sample-Distressed Rate I estimates were
applied to Federal prisons and community corrections and Distressed Rate I-Distressed Rate II
estimates were applied to jails and State prisons.
Finally, these estimates were weighted by the
1995 age, gender, and race distributions in each
setting. The projected number of individuals
estimated to have a diagnosable psychiatric
disorder cannot simply be added up to derive a
total of persons in need of care. Comorbidity of
disorders cannot be disentangled in the current
analyses.

into the first category. Other conditions may
cause significant distress to inmates and may or
may not be identified or treated. Antisocial
personality disorder is especially troubling to
administrators, but, because of its intractibility, is
usually not the focus of treatment.
Table 8 shows estimates of the number and
prevalence of psychiatric disorders among jail
inmates. On any given day, approximately 1
percent of offenders booked into U.S. jails are
estimated to have schizophrenia or other
psychotic disorder; 2–3 percent are estimated to
have bipolar disorder (manic episode); and 8–15
percent are estimated to exhibit symptoms of
major depression. Further, 3–4 percent are
predicted to have dysthymia. Fourteen to 20
percent are estimated to have some type of
anxiety disorder, excluding post-traumatic stress
disorder, which is estimated independently at 4–8
percent. Finally, 26–46 percent of jail inmates are
estimated to have antisocial personality disorder.

Jail
In correctional facilities, serious and persistent
psychiatric disorders that are often treated by
medication are distinguished from those
considered less serious. Schizophrenia, bipolar
disorders, and major (unipolar) depression fall

Table 7. Six-Month and Lifetime Prevalence Rates of Diagnoses by Level of Distress
6-Month Rate
Disorder

Comm

Distrs I

Lifetime Rate
Distrs II

Comm

Distrs I

Distrs II

Schizophrenia

0.4

0.9

0.8

0.8

1.6

1.6

Major depression

8.4

11.6

20.6

18.1

20.1

33.6

Bipolar (manic)

1.0

1.5

3.6

1.7

2.0

5.3

Dysthymia

2.0

3.5

7.3

7.1

8.5

15.8

Post-traumatic stress

3.4

6.7

10.5

7.2

11.0

18.2

14.6

18.5

28.3

24.6

28.9

41.3

—

—

—

14.8

20.7

45.3

Anxiety
Antisocial personality

Table 8. Jail Estimates (n = 500,483)
Disorder
Schizophrenia/psychotic
Major depression
Bipolar (manic)

Distressed Rate I (6-month)

Distressed Rate II (6-month)

Number

Number

Percent

Percent

4,955

1.0

5,589

1.1

39,690

7.9

76,229

15.2

7,755

1.5

12,920

2.6

Dysthymia

13,644

2.7

21,040

4.2

Post-traumatic stress

19,770

4.0

41,509

8.3

Anxiety

70,613

14.1

100,098

20.0

131,501

26.3

231,115

46.2

Antisocial personality

64

State prisons
Prisons, like the general community, must have
the capacity to provide both acute and long-term
care to persons with psychiatric disorders.
Therefore, as table 9 shows, State prison estimates are based on lifetime prevalence rates and
are substantially higher than jail rates. On any
given day, 2–4 percent of State prison inmates
are estimated to have schizophrenia or other
psychotic disorder, 2–4 percent to have bipolar
disorder (manic episode), and 13–18 percent to
have major depression.
A substantial percent of inmates exhibit symptoms of other disorders as well, including 8–13
percent with dysthymia, 6–12 percent with an
anxiety disorder, and 22–30 percent with posttraumatic stress disorder. As in jails, 26–45
percent of inmates are predicted to have antisocial
personality disorder.

Federal prisons
Federal inmates are estimated to have lower rates
of psychiatric disorders than State inmates across
all diagnostic categories. Table 10 shows estimates of the number and prevalence of psychiatric disorders among Federal prison inmates.
One to 3 percent are estimated to have schizophrenia or another psychotic disorder, 2–3 percent
to have bipolar disorder (manic episode), and
14–16 percent to exhibit symptoms of major
depression. Seven to 12 percent are predicted to
have dysthymia, 18–23 percent are estimated to
have an anxiety disorder, and 5–7 percent to have

post-traumatic stress disorder. Antisocial personality disorder is predicted to be fairly low at a
rate of 21–28 percent.

Community corrections
Community corrections have been weighted by
sex and race marginals. Because age distributions
are unknown, rates of disorders are assumed to be
evenly distributed across sex and race categories.
Table 11 shows the estimates of the number and
prevalence of psychiatric disorders among
offenders in community corrections.
One to 2 percent of offenders in community
corrections are estimated to have schizophrenia
or another psychotic disorder, 1–2 percent to
have bipolar disorder (manic episode), and
15–19 percent to have major depression. In
addition, 7–12 percent are predicted to have
dysthymia, 22–27 percent are estimated to have
an anxiety disorder, and 6–9 percent to have
post-traumatic stress disorder. As with Federal
inmates, antisocial personality disorder is
predicted to be fairly low at a rate of 17–26
percent.

Summary
The predicted rates of psychiatric disorders across
correctional settings are synthetic estimates based
on a complex theoretical and empirical weighting
scheme. The estimates are similar to those found
in single-site correctional facility epidemiological
studies and have the added advantage of being
based on a nationally representative sample.

Table 9. State Prison Estimates (n = 1,010,228)
Disorder
Schizophrenia/psychotic

Distressed Rate I (lifetime)

Distressed Rate II (lifetime)

Number

Number

Percent

Percent

22,994

2.3

39,262

3.9

132,619

13.1

188,259

18.6

Bipolar (manic)

21,468

2.1

43,708

4.3

Dysthymia

85,018

8.4

135,121

13.4

Post-traumatic stress

62,388

6.2

118,071

11.7

Anxiety

222,147

22.0

303,936

30.1

Antisocial personality

262,349

26.0

449,107

44.5

Major depression

65
Table 10. Federal Prison Estimates (n = 91,506)
Community Rate (lifetime)
Disorder
Schizophrenia/psychotic

Number

Percent

Distressed Rate I (lifetime)
Number

Percent

763

0.8

2,326

2.5

12,378

13.5

14,363

15.7

Bipolar (manic)

1,393

1.5

2,475

2.7

Dysthymia

6,253

6.8

10,652

11.6

Post-traumatic stress

4,466

4.9

6,257

6.8

Major depression

Anxiety

16,638

18.2

21,079

23.0

Antisocial personality

19,493

21.3

25,781

28.2

Table 11. Community Corrections Estimates (n = 3,269,481)
Community Rate (lifetime)
Disorder

Distressed Rate I (lifetime)

Number

Percent

Number

Percent

26,194

0.8

70,156

2.1

497,424

15.2

631,443

19.3

44,304

1.4

79,360

2.4

Dysthymia

218,614

6.7

381,350

11.7

Post-traumatic stress

192,128

5.9

303,884

9.3

Schizophrenia/psychotic
Major depression
Bipolar (manic)

Anxiety

731,708

22.4

885,761

27.1

Antisocial personality

542,672

16.6

834,855

25.5

These findings suggest that a minimum of 8
percent of short-term jail detainees have psychiatric conditions requiring medical intervention,
with a substantial additional percentage who will
experience significant distress due to psychiatric
conditions. State and Federal prisons have a
minimum of 13 percent who will require psychiatric care for an acute episode of a serious mental
illness at some time during their incarceration.
Although community corrections incur no duty to

provide psychiatric care, it is important for
administrators to know that a significant
percentage of persons under community
supervision have serious mental illnesses and may
require ongoing or acute care during their
community sentence. Psychiatric illnesses are not
as rare as was once thought. Acknowledging the
prevalence of these disorders in corrections is
only the first step toward providing appropriate
comprehensive care.

66

Notes

11. Ibid.

1. Teplin, L.A., “Psychiatric and Substance Abuse
Disorders Among Male Urban Jail Detainees,”
American Journal of Public Health 84(2)(1994):
290–293.

12. Boone, H.N., “Mental Illness in Probation and
Parole Populations: Results from a National Survey,”
Perspectives (Fall 1995): 32–39.

2. Teplin, L.A., K.M. Abram, and G.M. McClelland,
“Prevalence of Psychiatric Disorders Among Incarcerated Women: 1. Pretrial Jail Detainees,” Archives of
General Psychiatry 53(8)(1996): 505–512.
3. Teplin, L.A., “Psychiatric and Substance Abuse
Disorders Among Male Urban Jail Detainees” (see
note 1); Teplin, L.A., K.M. Abram, and G.M.
McClelland, “Prevalence of Psychiatric Disorders
Among Incarcerated Women: 1. Pretrial Jail
Detainees” (see note 2).
4. Teplin, L.A., “Psychiatric and Substance Abuse
Disorders Among Male Urban Jail Detainees” (see
note 1).
5. Teplin, L.A., K.M. Abram, and G.M. McClelland,
“Prevalence of Psychiatric Disorders Among Incarcerated Women: 1. Pretrial Jail Detainees” (see note 2).
6. Manderscheid, R.W., and M.A. Sonnenschein, eds.,
Mental Health, United States, 1992, Rockville, MD:
U.S. Department of Health and Human Services,
Substance Abuse and Mental Health Services
Administration, 1992, DHHS (SMA) 92–1942.
7. Eyestone, L.L., and R.J. Howell, “An Epidemiological Study of Attention-Deficit Hyperactivity
Disorder and Major Depression in a Male Prison
Population,” Bulletin of the American Academy of
Psychiatry and the Law 22(1994): 181–193.
8. Kokkevi, A., and C. Stefanis, “Drug Abuse and
Psychiatric Comorbidity,” Comprehensive Psychiatry
36(5)(1995): 329–337.
9. Jordan, B.K., W.E. Schlenger, J.A. Fairbank, and
J.M. Caddell, “Prevalence of Psychiatric Disorders
Among Incarcerated Women: II. Convicted Felons
Entering Prison,” Archives of General Psychiatry
53(6)(1996): 513–519; Teplin, L.A., “Psychiatric and
Substance Abuse Disorders Among Male Urban Jail
Detainees” (see note 1).
10. Robins, L.N., and D.A. Regier, eds., Psychiatric
Disorders in America: The Epidemiological
Catchment Area Study, New York: Free Press, 1991.

13. Kessler, R.C., “The National Comorbidity Survey,”
International Review of Psychiatry 6(1994): 365–376.
14. Ibid.
15. Five anxiety variables from the original study were
combined to form a comprehensive anxiety category.
Respondents were coded with a value of 1 if they had a
diagnosis for one of the following disorders: agoraphobia, generalized anxiety, simple phobia, social
phobia, or panic disorder. The variable was not additive. This process was repeated for both the 6-month
and lifetime estimates.
16. Hornung, C., R. Greifinger, and S. Gadre, “A
Projection Model of the Prevalence of Selected
Chronic Diseases in the Inmate Population,” paper
prepared the National Commission on Correctional
Health Care, Chicago, Illinois, n.d. (Copy in this
volume.)
17. This total differs from the total sample size
reported above because there were missing cases for
some of the variables; 3.3 percent of the cases were
missing (n = 270).
18. Because of missing values, this subsample lost 49
or 4.8 percent of the cases.
19. National Institute of Justice, Drug Use Forecasting: 1994 Annual Report on Adult and Juvenile
Arrestees, Washington, DC: U.S. Department of
Justice, National Institute of Justice, 1995, NCJ
157644.
20. Hornung, C., R. Greifinger, and S. Gadre, “A
Projection Model of the Prevalence of Selected
Chronic Diseases in the Inmate Population” (see
note 16).
21. Maguire, K., and A.L. Pastore, eds., Sourcebook of
Criminal Justice Statistics, 1996, Washington, DC:
U.S. Department of Justice, Bureau of Justice
Statistics, 1997, NCJ 165361.

67

Appendix A
Table A–1. Lifetime Prevalence of Psychotic Disorder in the General Population (n = 7,828)
Psychotic Disorder (lifetime)=0.8
White=0.7
Age

Black=1.2

Hispanic=1.0

Male=0.8

Female=0.7

Male=0.7

Female=1.5

Male=0.8

Female=1.1

#19

0.4

0.4

0.1

1.8

0.1

3.4

20–29

1.4

0.6

1.0

1.7

0.9

0.9

30–39

0.4

0.6

0.8

0.1

1.9

0.8

40–49

0.9

1.0

1.0

3.1

0.1

0.1

50+

0.4

0.6

0.1

2.2

0.1

0.1

Table A–2. Lifetime Prevalence of Psychotic Disorder Among Those in Poverty (n = 977)
Psychotic Disorder (lifetime)=1.6
White=1.3
Age

Male=2.9

Black=2.7

Female=0.3

Male=1.6

Hispanic=1.1

Female=3.4

Male=.8

Female=1.1

#19

0.4

0.4

0.1

4.2

0.1

3.4

20–29

4.6

0.6

1.0

3.9

4.3

0.9

30–39

0.4

1.2

0.8

0.1

6.7

0.8

40–49

6.9

1.0

2.3

9.5

0.1

0.1

50+

0.4

0.6

0.2

5.0

0.1

0.1

Table A–3. Lifetime Prevalence of Psychotic Disorder Among Persons with Poverty and Substance Abuse (n = 247)
Psychotic Disorder (lifetime)=1.6
White=1.6
Age

Male=3.6

Black=2.7

Female=0.4

Male=1.6

Hispanic=2.9

Female=3.4

Male=2.3

Female=3.2

#19

0.4

0.4

0.1

4.2

0.3

9.9

20–29

6.7

0.6

1.0

3.9

12.5

2.6

30–39

0.4

1.2

0.8

0.1

19.4

2.3

40–49

6.9

1.2

2.3

9.5

0.3

0.3

50+

0.5

0.7

0.2

5.7

0.3

0.3

68
Table A–4. Six-Month Prevalence of Psychotic Disorder in the General Population (n = 7,828)
Psychotic Disorder (6-month)=0.4
White=0.3
Age

Black=0.7

Hispanic=0.7

Male=0.3

Female=0.2

Male=0.2

Female=1.0

Male=0.3

Female=1.1

#19

0.4

0.1

0.1

0.1

0.1

3.4

20–29

0.5

0.2

1.0

1.1

0.1

0.9

30–39

0.1

0.1

0.1

0.1

1.0

0.8

40–49

0.4

0.4

0.1

2.3

0.1

0.1

50+

0.4

0.3

0.1

2.2

0.1

0.1

Table A–5. Six-Month Prevalence of Psychotic Disorder in Those in Poverty (n = 977)
Psychotic Disorder (6-month)=0.9
White=0.7
Age

Black=2.0

Hispanic=0.7

Male=0.7

Female=0.5

Male=0.6

Female=2.9

Male=0.3

Female=1.1

#19

0.4

0.1

0.1

0.1

0.1

3.4

20–29

3.4

0.2

1.0

2.6

0.1

0.9

30–39

0.1

0.1

0.1

0.1

1.0

0.8

40–49

3.4

0.4

0.3

9.5

0.1

0.1

50+

0.4

0.3

0.3

6.3

0.1

0.1

Table A–6. Six-Month Prevalence of Psychotic Disorder by Age for Those with Poverty and Substance Abuse (n = 247)
Psychotic Disorder (6-month)=0.8
White=1.1
Age

Black=2.0

Hispanic=0.7

Male=1.1

Female=0.8

Male=0.6

Female=2.9

Male=0.3

Female=1.1

#19

0.4

0.1

0.1

0.1

0.1

3.4

20–29

4.4

0.2

1.0

2.6

0.1

0.9

30–39

0.1

0.1

0.1

0.1

1.0

0.8

40–49

3.4

0.6

0.3

9.5

0.1

0.1

50+

0.6

0.5

0.3

6.3

0.1

0.1

69
Table A–7. Lifetime Prevalence of Major Depression by Age in the General Population (n = 7,828)
Major Depression (lifetime)=18.1
White=19.0
Age

Male=14.2

#19

Black=12.8

Female=23.4

Male=8.7

Hispanic=17.7

Female=15.8

Male=13.3

Female=22.1

9.4

21.9

3.1

3.6

9.7

22.4

20–29

14.0

22.7

5.9

15.1

6.6

19.0

30–39

15.5

23.3

13.5

20.5

20.2

19.5

40–49

16.5

25.0

10.2

14.0

17.7

28.8

8.7

23.0

3.2

20.0

11.1

41.2

50+

Table A–8. Lifetime Prevalence of Major Depression in Those in Poverty (n = 977)
Major Depression (lifetime)=20.1
White=25.0
Age

Male=21.0

Black=9.8

Female=27.4

Male=6.4

Hispanic=20.0

Female=11.2

Male=9.6

Female=27.1

#19

22.7

17.9

4.5

8.3

7.4

26.1

20–29

16.1

33.1

4.2

9.1

4.3

17.9

30–39

18.8

26.5

11.1

14.9

20.0

27.6

40–49

41.4

26.5

7.5

9.5

12.7

50.0

7.7

20.8

2.4

14.2

8.0

50.7

50+

Table A–9. Lifetime Prevalence of Major Depression in Those with Poverty and Substance Abuse (n = 247)
Major Depression (lifetime)=33.6
White=34.6
Age

Black=13.3

Hispanic=45.7

Male=28.1

Female=41.9

Male=6.7

Female=20.0

Male=31.3

Female=57.9

#19

53.3

27.3

4.7

14.9

24.1

55.9

20–29

17.8

42.9

4.4

16.3

14.0

38.3

30–39

25.0

47.1

11.7

26.7

65.2

59.1

40–49

50.0

40.5

7.9

17.0

41.4

99.0

50+

10.3

31.8

2.5

25.4

26.1

99.0

70
Table A–10. Six-Month Prevalence of Major Depression in the General Population (n = 7,828)
Major Depression (6-month)=8.4
White=8.2
Age

Black=7.8
Male=4.7

Hispanic=11.1

Male=5.9

Female=10.4

Female=10.1

Male=7.7

Female=14.3

#19

6.8

16.2

3.1

1.8

9.7

17.2

20–29

6.4

10.8

4.0

10.1

3.8

12.1

30–39

6.0

9.6

7.5

14.8

10.6

15.6

40–49

6.0

9.8

4.1

7.8

8.1

13.5

50+

2.6

8.2

0.1

8.9

5.6

11.8

Table A–11. Six-Month Prevalence of Major Depression in Those in Poverty (n = 977)
Major Depression (6-month)=11.6
White=13.1
Age
#19

Male=14.0

Black=6.6

Female=13.1

Male=3.8

Hispanic=13.9

Female=7.9

Male=5.5

Female=19.6

18.2

10.7

4.5

4.2

7.4

26.1

20–29

8.0

15.8

4.2

5.2

3.8

10.3

30–39

12.5

15.7

5.6

10.6

6.7

24.1

40–49

17.2

14.7

3.3

9.5

5.8

28.6

2.6

4.2

0.1

6.9

4.0

16.2

50+

Table A–12. Six-Month Prevalence of Major Depression in Those with Poverty and Substance Abuse (n = 247)
Major Depression (6-month)=20.6
White=18.7
Age

Male=19.8

Black=13.3

Hispanic=37.1

Female=17.4

Male=6.7

Female=20.0

Male=18.8

Female=52.6

#19

53.3

10.7

7.9

10.6

25.3

69.9

20–29

11.1

16.3

7.4

13.2

13.0

10.3

30–39

18.8

29.4

9.9

26.8

22.9

64.6

40–49

21.4

19.6

5.8

24.0

19.8

76.6

3.7

5.6

0.2

17.5

13.7

43.4

50+

71
Table A–13. Lifetime Prevalence of Bipolar Disorder in the General Population (n = 7,828)
Bipolar Disorder (lifetime)=1.5
White=1.7
Age

Male=1.8

Black=0.8

Female=1.6

Male=0.9

Hispanic=1.6

Female=0.7

Male=1.7

Female=1.6

#19

0.1

1.9

0.1

0.1

2.8

5.2

20–29

1.9

1.8

1.0

1.7

0.1

0.9

30–39

2.0

1.6

0.8

0.1

2.9

1.6

40–49

2.1

1.5

2.0

0.8

1.6

0.1

50+

1.7

0.6

0.1

0.1

0.1

0.1

Table A–14. Lifetime Prevalence of Bipolar Disorder in Those in Poverty (n = 977)
Bipolar Disorder (lifetime)=2.0
White=2.2
Age

Black=0.8

Hispanic=3.3

Male=2.4

Female=2.1

Male=0.9

Female=0.7

Male=2.7

Female=3.7

#19

0.1

1.8

0.1

0.1

3.7

8.7

20–29

3.4

2.2

1.0

2.6

0.1

0.9

30–39

3.1

2.4

0.8

0.1

6.7

6.9

40–49

2.1

2.9

2.0

0.8

2.5

0.1

50+

7.7

0.6

0.1

0.1

0.2

0.2

Table A–15. Lifetime Prevalence of Bipolar Disorder in Those with Poverty and Substance Abuse (n = 247)
Bipolar Disorder (lifetime)=5.3
White=3.8
Age

Male=2.1

Black=0.8

Female=5.8

Hispanic=17.1

Male=0.9

Female=0.7

Male=12.5

Female=21.1

#19

0.1

1.8

0.1

0.1

17.1

49.6

20–29

3.4

4.1

1.0

2.6

0.5

5.1

30–39

6.3

11.8

0.8

0.1

31.0

39.3

40–49

2.1

8.0

2.0

0.8

11.6

0.6

50+

6.8

1.7

0.1

0.1

0.9

1.1

72
Table A–16. Six-Month Prevalence of Bipolar Disorder in the General Population (n = 7,828)
Bipolar Disorder (6-month)=1.0
White=1.1
Age

Male=1.3

Black=0.6

Female=1.0

Male=0.9

Hispanic=1.0

Female=0.3

Male=0.6

Female=1.3

#19

0.1

1.9

0.1

0.1

2.8

5.2

20–29

1.4

1.1

1.0

1.1

0.1

0.9

30–39

1.5

0.9

0.8

0.1

0.1

0.8

40–49

1.5

0.8

2.0

0.1

0.1

0.1

50+

0.9

0.6

0.1

0.1

0.1

0.1

Table A–17. Six-Month Prevalence of Bipolar Disorder in Those in Poverty (n = 977)
Bipolar Disorder (6-month)=1.5
White=1.8
Age

Black=0.4

Hispanic=2.2

Male=2.4

Female=1.5

Male=0.6

Female=0.2

Male=1.4

Female=2.8

#19

0.1

1.8

0.1

0.1

3.7

8.7

20–29

3.4

1.4

1.0

1.3

0.1

0.9

30–39

3.1

1.2

0.8

0.1

0.1

3.4

40–49

1.5

2.9

1.3

0.1

0.2

0.1

50+

7.7

0.6

0.1

0.1

0.2

0.2

Table A–18. Six-Month Prevalence of Bipolar Disorder in Those with Poverty and Substance Abuse (n = 247)
Bipolar Disorder (6-month)=3.6
White=2.7
Age

Male=2.1

Black=0.4

Female=3.5

Male=0.6

Hispanic=11.4

Female=0.2

Male=6.3

Female=15.8

#19

0.1

1.8

0.1

0.1

16.7

49.1

20–29

3.4

2.0

1.0

1.3

0.5

5.1

30–39

6.3

5.9

0.8

0.1

0.5

19.2

40–49

1.5

6.8

2.0

0.1

0.9

0.6

50+

6.8

1.4

0.1

0.1

0.9

1.1

73
Table A–19. Lifetime Prevalence of Dysthymia in the General Population (n = 7,828)
Dysthymia (lifetime)=7.1
White=7.5
Age

Male=5.9

Black=5.1

Female=8.9

Male=4.0

Hispanic=6.7

Female=6.0

Male=7.5

Female=5.9

#19

2.9

6.2

3.1

0.1

20–29

4.2

5.8

3.0

3.9

3.8

4.3

30–39

5.9

9.1

5.3

8.0

10.6

4.7

40–49

8.1

11.7

5.1

6.2

11.3

9.6

50+

8.7

12.5

0.1

13.3

16.7

17.6

2.8

5.2

Table A–20. Lifetime Prevalence of Dysthymia in Those in Poverty (n = 977)
Dysthymia (lifetime)=8.5
White=11.6
Age

Male=11.7

Black=2.3

Female=11.6

Male=1.3

Hispanic=7.8

Female=2.8

Male=8.2

Female=7.5

#19

4.5

7.1

4.5

0.1

3.7

8.7

20–29

6.9

7.9

3.0

2.6

4.3

2.6

30–39

15.6

15.7

5.3

2.1

13.3

6.9

40–49

31.0

23.5

1.7

4.8

12.3

14.3

50+

15.4

12.5

0.1

6.3

18.2

22.4

Table A–21. Lifetime Prevalence of Dysthymia in Those with Poverty and Substance Abuse (n = 247)
Dysthymia (lifetime)=15.8
White=17.6
Age

Black=3.3

Male=15.6

Female=19.8

13.3

18.2

6.4

20–29

8.9

12.2

30–39

18.8

40–49
50+

#19

Male=1.9

Hispanic=17.1

Female=4.0

Male=25.0

Female=10.5

0.1

11.3

12.2

4.3

3.7

13.1

3.6

23.5

7.6

3.0

40.6

9.7

35.7

40.2

2.4

6.9

37.5

20.0

20.5

21.4

0.1

9.0

55.5

31.4

74
Table A–22. Six-Month Prevalence of Dysthymia in the General Population (n = 7,828)
Dysthymia (6-month)=2.0
White=2.0
Age

Male=1.5

Black=2.2

Female=2.4

Male=1.6

Hispanic=2.3

Female=2.6

Male=2.8

Female=1.9

#19

1.4

1.9

1.6

0.1

2.8

3.4

20–29

0.8

1.9

0.1

2.2

0.9

2.6

30–39

1.6

2.6

3.0

4.0

3.8

0.8

40–49

2.2

2.7

2.0

0.8

3.2

1.9

50+

0.9

2.9

0.1

6.7

5.6

0.1

Table A–23. Six-Month Prevalence of Dysthymia in Those in Poverty (n = 977)
Dysthymia (6-month)=3.5
White=4.8
Age

Male=3.9

Black=1.2

Female=5.4

Male=0.9

Hispanic=2.8

Female=1.4

Male=2.7

Female=2.8

#19

2.3

1.8

1.6

0.1

3.7

8.7

20–29

2.3

4.3

0.1

1.3

0.9

2.6

30–39

1.6

7.2

3.0

2.1

3.8

0.8

40–49

13.8

11.8

1.1

0.8

3.1

7.1

7.7

4.2

0.1

3.6

5.4

1.5

50+

Table A–24. Six-Month Prevalence of Dysthymia in Those with Poverty and Substance Abuse (n = 247)
Dysthymia (6-month)=7.3
White=8.2
Age

Male=6.3

#19

6.7

20–29

4.4

30–39

1.6

40–49

14.3

50+

12.5

Black=1.2

Female=10.5
1.8

Male=0.9

Hispanic=8.6

Female=1.4

1.6

0.1

6.1

0.1

17.6

3.0

22.9
8.1

Male=6.3

Female=10.5

8.6

32.6

1.3

2.1

9.8

2.1

8.9

3.0

1.1

0.8

7.2

26.6

0.1

3.6

12.6

5.6

75
Table A–25. Lifetime Prevalence of Post-Traumatic Stress Disorder in the General Population (n = 7,828)
Post-Traumatic Stress Disorder (lifetime)=7.2
White=7.3
Age

Male=4.9

Black=6.6

Female=9.6

Male=3.7

Hispanic=7.5

Female=8.7

Male=3.9

Female=11.1

#19

1.8

10.4

1.6

3.6

2.8

6.9

20–29

4.6

10.0

1.0

12.3

4.7

10.3

30–39

5.6

9.2

5.3

10.2

1.9

14.1

40–49

5.6

10.7

7.1

5.4

6.5

9.6

50+

4.4

6.7

0.1

4.4

5.6

11.8

Table A–26. Lifetime Prevalence of Post-Traumatic Stress Disorder in Those in Poverty (n = 977)
Post-Traumatic Stress Disorder (lifetime)=11.0
White=13.7
Age

Male=8.3

Black=6.3

Female=17.0

Male=2.6

Hispanic=9.4

Female=7.9

Male=2.7

Female=14.0

#19

4.5

14.3

1.6

4.2

2.8

8.7

20–29

8.0

19.4

1.0

9.1

4.3

10.3

30–39

12.5

16.9

5.6

10.6

1.9

20.7

40–49

13.8

14.7

5.0

4.8

4.5

14.3

4.4

12.5

0.1

4.0

3.9

14.9

50+

Table A–27. Lifetime Prevalence of Post-Traumatic Stress Disorder in Those with Poverty and Substance
Abuse (n = 247)
Post-Traumatic Stress Disorder (lifetime)=18.2
White=19.2
Age

Male=10.4

Black=13.3

Female=29.1

Male=6.7

Hispanic=17.1

Female=20.0

Male=12.5

Female=21.1

#19

6.7

9.1

4.1

10.6

12.9

13.1

20–29

8.9

28.6

2.6

23.0

19.9

15.5

30–39

12.5

35.3

14.4

26.8

8.8

31.1

40–49

21.4

25.1

12.9

12.1

20.8

21.5

5.5

21.4

0.3

10.1

18.0

22.4

50+

76
Table A–28. Six-Month Prevalence of Post-Traumatic Stress Disorder in the General Population (n = 7,828)
Post-Traumatic Stress Disorder (6-month)=3.4
White=3.5
Age

Male=2.1

Black=3.6

Female=4.7

Male=2.3

Hispanic=2.7

Female=4.5

Male=1.4

Female=4.0

#19

0.7

6.2

1.6

0.1

2.8

3.4

20–29

2.6

5.9

0.1

8.4

2.8

2.6

30–39

2.0

4.8

3.0

4.5

0.1

7.0

40–49

2.5

3.0

5.1

2.3

0.1

1.9

50+

1.7

4.4

0.1

0.1

0.1

0.1

Table A–29. Six-Month Prevalence of Post-Traumatic Stress Disorder in Those in Poverty (n = 977)
Post-Traumatic Stress Disorder (6-month)=6.7
White=8.9
Age

Male=3.9

Black=3.9

Female=11.9

Male=2.6

Hispanic=3.9

Female=4.5

Male=1.4

Female=5.6

#19

2.3

10.7

1.6

0.1

2.8

8.7

20–29

2.3

15.8

0.1

5.2

4.3

2.6

30–39

6.3

9.6

5.6

6.4

0.1

13.8

40–49

10.3

5.9

5.8

4.8

0.1

1.9

1.7

8.3

0.1

0.1

0.1

0.1

50+

Table A–30. Six-Month Prevalence of Post-Traumatic Stress Disorder in Those with Poverty and Substance
Abuse (n = 247)
Post-Traumatic Stress Disorder (6-month)=10.5
White=11.0
Age

Male=5.2

Black=10.0

Female=17.4

Male=6.7

Hispanic=8.6

Female=13.3

Male=6.3

Female=10.5

#19

6.7

10.7

4.1

0.3

12.6

16.4

20–29

2.2

24.5

0.3

15.6

19.4

4.9

30–39

6.3

11.8

14.4

19.2

0.5

25.9

40–49

14.3

8.4

14.9

14.4

0.5

3.8

2.3

11.9

0.3

0.3

0.5

0.2

50+

77
Table A–31. Lifetime Prevalence of Anxiety Disorder in the General Population (n = 7,828)
Anxiety Disorder (lifetime)=24.6
White= 25.3
Age

Black=19.8

Hispanic=25.6

Male=21.3

Female=29.1

Male=12.9

Female=24.8

Male=18.8

Female=32.3

#19

23.7

33.1

12.5

25.5

22.2

36.2

20–29

20.3

29.1

13.9

26.3

22.6

28.4

30–39

22.6

30.2

16.5

27.3

18.3

28.9

40–49

21.1

28.1

8.2

20.9

9.7

42.3

50+

15.7

24.8

9.7

20.0

16.7

41.2

Table A–32. Lifetime Prevalence of Anxiety Disorder in Those in Poverty (n = 977)
Anxiety Disorder (lifetime)=28.9
White=32.2
Age

Black=19.5

Hispanic=32.2

Male=26.8

Female=35.4

Male=15.4

Female=21.3

Male=23.3

Female=38.3

#19

29.5

42.9

18.2

20.8

29.6

56.5

20–29

21.8

36.0

12.5

22.1

21.7

30.8

30–39

37.5

31.3

22.2

17.0

26.7

31.0

40–49

31.0

32.4

9.8

23.8

12.0

42.9

50+

15.4

33.3

11.5

17.2

20.7

49.0

Table A–33. Lifetime Prevalence of Anxiety Disorder with Poverty and Substance Abuse (n = 247)
Anxiety Disorder (lifetime)=41.3
White=40.1
Age

Black=30.0

Hispanic=57.1

Male=35.4

Female=45.3

Male=20.0

Female=40.0

Male=43.8

Female=68.4

#19

60.0

63.6

23.7

39.1

55.6

99.0

20–29

26.7

32.7

16.3

41.5

40.8

55.1

30–39

43.8

70.6

28.9

32.0

50.2

55.5

40–49

28.6

41.5

12.7

44.7

22.6

76.8

50+

20.3

42.6

11.5

32.3

38.9

87.7

78
Table A–34. Six-Month Prevalence of Anxiety Disorder in the General Population (n = 7,828)
Anxiety Disorder (6-month)=14.6
White=14.7
Age

Black=12.8

Male=11.1

Female=18.0

#19

14.7

26.5

20–29

11.7

30–39

Male=5.6

Hispanic=16.0

Female=18.0

Male=11.6

Female=20.2

4.7

23.6

19.4

31.0

18.1

6.9

21.2

15.1

17.2

11.2

17.8

8.3

17.0

7.7

17.2

40–49

9.4

16.5

3.1

14.7

4.8

21.2

50+

9.6

15.5

0.1

11.1

5.6

23.5

Table A–35. Six-Month Prevalence of Anxiety Disorder in Those in Poverty (n = 977)
Anxiety Disorder (6-month)=18.5
White=21.1
Age

Black=12.9

Hispanic=18.9

Male=15.6

Female=24.4

Male=9.0

Female=14.6

Male=15.1

Female=21.5

#19

13.6

30.4

4.5

16.7

22.2

47.8

20–29

16.1

26.6

8.3

16.9

13.0

10.3

30–39

15.6

18.1

22.2

12.8

13.3

13.8

40–49

17.2

23.5

5.0

9.5

6.2

28.6

50+

15.4

20.8

0.3

9.0

7.3

24.9

Table A–36. Six-Month Prevalence of Anxiety Disorder in Those with Poverty and Substance Abuse (n = 247)
Anxiety Disorder (6-month)=28.3
White=28.6
Age

Black=16.7

Male=21.9

Female=36.0

#19

26.7

54.4

20–29

22.2

30–39

Male=6.7

Hispanic=31.3

Female=26.7

Male=42.1

Female=37.1

3.3

30.6

61.9

82.7

28.6

6.1

30.9

36.3

17.8

18.8

47.1

16.4

23.4

37.1

23.9

40–49

14.3

34.8

3.7

17.4

17.3

49.5

50+

21.6

30.8

0.1

16.5

20.4

43.1

79
Table A–37. Lifetime Prevalence of Antisocial Personality Disorder in the General Population (n = 7,828)
Antisocial Personality Disorder (lifetime)=14.8
White=14.4
Age

Black=13.5

Hispanic=20.1

Male=22.2

Female=7.1

Male=19.7

Female=8.9

Male=29.3

Female=11.1

#19

25.9

10.8

29.7

7.3

31.9

12.1

20–29

25.1

9.6

23.8

15.1

32.1

11.2

30–39

22.8

7.8

18.0

8.5

29.8

9.4

40–49

19.3

4.1

12.2

2.3

21.0

13.5

50+

14.4

2.3

16.1

6.7

27.8

11.8

Table A–38. Lifetime Prevalence of Antisocial Personality Disorder in Those in Poverty (n = 977)
Antisocial Personality Disorder (lifetime)=20.7
White=22.6
Age

Black=14.8

Male=34.1

Female=15.5

Male=21.8

#19

36.4

17.9

36.4

20–29

31.0

18.0

30–39

31.3

40–49
50+

Hispanic=23.3

Female=11.8

Male=31.5

Female=17.8

8.3

25.9

21.7

16.7

15.6

30.4

17.9

14.5

22.2

10.6

40.0

17.2

41.4

8.8

13.5

4.8

22.7

7.1

38.5

8.3

17.9

8.9

30.0

18.9

Table A–39. Lifetime Prevalence of Antisocial Personality Disorder in Those with Poverty and Substance
Abuse (n = 247)
Antisocial Personality Disorder (lifetime)=45.3
White=46.7
Age

Black=33.3

Hispanic=48.6

Male=60.4

Female=31.4

Male=33.3

Female=33.3

Male=56.3

Female=42.1

#19

86.7

45.5

55.7

23.4

46.4

51.4

20–29

46.7

28.6

25.6

44.1

54.4

42.4

30–39

62.5

35.3

34.0

29.8

71.6

40.8

40–49

71.4

17.9

20.7

13.5

40.6

16.8

50+

68.1

16.8

27.4

25.0

53.7

44.8

80

Appendix B
Table B–1. Cell Sizes for the Community Sample From the National Comorbidity Survey (n = 7,828)
Cell Size
White
Age

Black

Male

Female

Male

#19

278

260

64

20–29

738

832

30–39

1,007

40–49
50+

Hispanic
Female

Male

Female

55

72

58

101

179

106

116

1,007

133

176

104

128

679

711

98

129

62

52

229

343

31

45

18

17

Table B–2. Cell Sizes for the Poverty Sample From the National Comorbidity Survey (n = 977)
Cell Size
White
Age

Male

Black
Female

Male

Hispanic
Female

Male

Female

#19

44

56

22

24

27

23

20–29

87

139

24

77

23

39

30–39

32

83

18

47

15

29

40–49

29

34

8

21

5

14

50+

13

24

6

9

3

2

Table B–3. Cell Sizes for the Poverty and Substance Use Sample From the National Comorbidity Survey (n = 247)
Cell Size
White
Age

Black

Hispanic

Male

Female

Male

Female

Male

Female

#19

15

11

1

1

2

6

20–29

45

49

5

6

7

6

30–39

16

17

4

5

3

5

40–49

14

7

2

3

3

2

6

2

3

0

1

0

50+

81

Cost-Effectiveness of Routine
Screening for Sexually Transmitted
Diseases Among Inmates in United
States Prisons and Jails

Julie R. Kraut, Ph.D., and Anne C. Haddix, Ph.D., Division of Sexually Transmitted Diseases
Prevention, Health Services Research and Evaluation Branch, Centers for Disease Control and
Prevention; Vilma Carande-Kulis, Ph.D., Epidemiology Program Office, Centers for Disease
Control and Prevention; and Robert B. Greifinger, M.D., National Commission on Correctional
Health Care

Introduction
When the famous bank robber Willie Sutton
was asked why he robbed banks, he answered,
“Because that’s where the money is.” Well,
jails are where infectious diseases are that
most threaten public health.
—Thomas J. Conklin, M.D.
Director of Health Services for the
Hampden County Correctional Center,
Ludlow, Massachusetts

The above quote expresses the sentiments of
sexually transmitted disease (STD) prevention
and treatment specialists regarding the need for
routine screening programs for inmates of
corrections facilities in the United States.
Sexually transmitted diseases are among the
group of infectious diseases whose prevalence is
estimated to be higher among inmates than in the
general U.S. population.1 These high prevalence
rates are due to a concentration of STD risk
behaviors and factors in incarcerated populations.
These include substance abuse, high-risk sexual
activity (including commercial sex work), and the
limited access to health care that is associated
with poverty. Although the National STD Surveillance Program of the Centers for Disease
Control and Prevention (CDC) does not flag cases
identified in corrections facilities, CDC’s STD

division started an annual Jail STD Prevalence
Monitoring Project in 1997 to develop a national
picture of STD prevalence in these facilities. In
addition, there have been numerous local studies
of STD prevalence within these institutions.
These studies have found prevalence of the three
most commonly reported bacterial STDs—
chlamydia, gonorrhea, and syphilis—to be much
greater among inmates than in the general U.S.
population.2 The rate of infectious syphilis in Los
Angeles County’s main jail facility was found to
be more than 11 times higher than the rate in the
county’s general population.3 In jailed women in
New York City, the prevalence of chlamydia was
as high as 27 percent, and that of gonorrhea was
as high as 8 percent. The prevalence of chlamydia
and gonorrhea in asymptomatic male detainees in
New Orleans was 6 percent. A recent study of
the prevalence of chlamydial and gonococcal
infections in women entering jails found that
in Chicago, 13 percent screened positive for
chlamydia and 9 percent screened positive for
gonorrhea; in Birmingham, Alabama, 11 percent
screened positive for chlamydia and 8 percent
screened positive for gonorrhea; and in San
Francisco, 10 percent screened positive for
chlamydia and 5 percent screened positive for
gonorrhea.4 In contrast, in 1996, 1.7–8.4 percent
of women age 15–34 who were tested at family
planning clinics screened positive for chlamydia,
and 3.3 percent screened positive for gonorrhea.

82
Among women age 15–34 who were screened at
STD clinics, about 15.2–17.7 percent screened
positive for chlamydia and 1.8–22.4 percent
screened positive for gonorrhea.5 Family planning
clinics tend to screen both symptomatic and
asymptomatic individuals, whereas STD clinics
screen and treat only symptomatic individuals.
Therefore, STD prevalence rates are expected to
be higher in STD clinic populations than in family
planning clinic populations or in any other population that is screened routinely (i.e., symptomatic and asymptomatic individuals). The high
prevalence of STDs in the incarcerated population
has implications not only for the personal health
of the individual inmates but also for the general
public. The population in corrections facilities has
been growing rapidly over the past decade, and
many of these inmates are released back into the
community each year. If inmates are released
without treatment, they increase the prevalence of
disease in a community and may promote further
transmission of STDs to their sex partners.
The National Commission on Correctional Health
Care (NCCHC) has recommended offering universal, routine screening to all inmates in corrections facilities regardless of behavioral risk
profile for STD for two reasons. First, many
individuals with sexually transmitted infections
may be asymptomatic and therefore unaware that
they are infected. A recent study found high rates
of asymptomatic bacterial sexually transmitted
infections in a high-risk STD cohort: 62 percent
of chlamydia infections were unrecognized in
both men and women, 28 percent of gonorrhea
infections in men and 51 percent in women
were unrecognized, and 40 percent of syphilis
infections in men and 100 percent of syphilis
infections in women were unrecognized.6 Second,
most of the population that enters the corrections
system does not have continuous access to quality
primary health care outside of these institutions.
Therefore, routine screening would enable an
underserved population at high risk for STDs to
receive health care that otherwise might be
unavailable.

Despite NCCHC’s recommendation, many
facilities, particularly jails, do not routinely
screen all inmates.7 Some facilities screen inmates
only if signs or symptoms are present or an
inmate requests testing. Even in facilities that
fully implement routine screening policies,
routine screening may be delayed for up to 14
days past intake. Many jail inmates are released
back into the community within 48 hours, so the
opportunity to screen and treat those inmates is
lost. Therefore, earlier screening, particularly
routine screening on intake, may be a more
effective strategy to decrease morbidity and the
transmission of STDs.
Questions remain about which of the many
strategies for STD prevention and control
activities in jails and prisons is most cost
effective: testing on an inmate’s request only,
testing only if signs or symptoms are present or
there is a sexual contact with a partner suspected
to be infected, routine screening any time before
release, routine screening within 12–48 hours
after intake, or presumptive treatment without
testing of persons with signs or symptoms. The
higher prevalence of STDs in incarcerated populations and the need for routine screening are
widely documented, but information on the
economic feasibility of routine STD screening
programs within corrections facilities is limited.
This report examines the cost-effectiveness of
providing routine screening on intake of inmates
in U.S. prisons and jails for syphilis, gonorrhea,
and chlamydia as compared with a presumptive
treatment strategy, often found in many corrections facilities.8 Because the following
analyses are based on jails and prisons, the
focus is on adult inmates as distinguished from
incarcerated adolescents, who generally reside in
juvenile detention facilities that follow different
rules and policies.

Methods
An intervention may reduce adverse health
outcomes and the medical costs associated with
these outcomes. For the purposes of this study,
the net cost of an intervention is the difference

83
between the intervention’s costs and the averted
medical costs. If the averted medical costs exceed
the intervention’s costs, then the intervention is
cost saving. Conversely, if the averted medical
costs are less than the intervention’s costs,
then the intervention is not cost saving. An
intervention that is not cost saving may be
cost effective if the reduction in adverse health
outcomes is judged to be worth the net cost of
the program. An intervention is considered cost
effective if the benefits it will achieve are worth
the costs, even if those costs are greater than the
money that is saved as a result of averted illness.
Decision tree analysis models9 are used to
examine the cost-effectiveness of routine
screening for syphilis, gonorrhea, and chlamydia.
Disease-specific analyses are conducted because
each infection requires different testing and
treatment approaches and results in different
medical sequelae. Each set of analyses uses a
health care system perspective that considers all
medical costs associated with a screening
program (i.e., testing and treatment). This
perspective was used because most, if not all,
of this population has little or no access to
continuing primary health care outside of the
corrections facility.10 Inmates who are released
from corrections facilities with undiagnosed or
untreated illnesses may compete with other
members of their communities for limited publicsector funds (e.g., Medicaid, publicly funded
hospital emergency rooms), shifting the costs to
facilities outside the prison or jail. Therefore,
each model considers all disease-related costs and
health events that occur over the lifetimes of the
members of the cohort as they move into or out
of a corrections facility. A health care system
perspective differs from a societal perspective,
which includes all benefits of a program and all
costs: direct medical, nonmedical, indirect (e.g.,
employment productivity losses), and intangible
(e.g., pain and suffering) costs.
A modified health-care system perspective
was adopted because this is most useful for
decisionmakers in corrections and public health.
Productivity losses of incarcerated populations
were not addressed because these populations

experience high rates of unemployment and
illegal employment that are difficult to quantify.
Intangible costs of STDs were not addressed
because these costs have not been quantified in
the economic or health literature. Outcomes and
costs associated with primary infection of inmates
were addressed, but not the costs of secondary
transmission of STDs because their associated
costs are difficult to quantify. All analyses were
conducted on hypothetical cohorts of 10,000
inmates.

Syphilis
Syphilis is a sexually transmitted infection caused
by Treponema pallidum. The disease has both
acute and chronic manifestations that typically
occur in distinct, sequential disease stages.
Syphilis is transmitted by direct contact with
infectious exudates from skin lesions, mucous
membranes, and genital secretions of infected
individuals. Ten days to 3 months after exposure
to the agent, an infected person may develop a
lesion at the site of the initial inoculum. The
primary lesion resolves spontaneously in 1–5
weeks. This stage, characterized by genital
lesions, is referred to as primary syphilis.11
After the primary lesion has healed, the organism
spreads through the body, leading to mild signs
and symptoms such as malaise, low-grade fever,
and a generalized rash (with lesions) on the palms
and soles. The stage characterized by these
generalized signs or symptoms is known as
secondary syphilis. Without treatment, these
symptoms resolve spontaneously within 2–6
weeks, although they may recur as long as 4 years
after infection. Secondary syphilis is generally
followed by a symptom-free stage, or latency.
This stage generally lasts from 10 to 20 years and
is characterized by a lack of signs or symptoms.
Transmission may occur during primary, secondary, and, although rarely, in the early latent stage.
During the later stage of latency, it is not
infectious. The infection may remain latent
in individuals until death.12
Clinical complications may occur after this latent
stage in about one-third of persons, possibly
because of waning immunity. They include

84
complications in the cardiovascular system, in the
central nervous system (neurosyphilis), on the
skin, in the mucous membranes, and in the
skeletal system (benign). These late-stage complications can cause mild to severe morbidity and
premature mortality. Central nervous system and
cardio-vascular system complications can lead to
expensive treatment, surgery, hospitalization, or
long-term care.13 Late-stage complications rarely
develop because the infection is often diagnosed
and treated during an earlier stage or because
undiagnosed syphilis is cured when the person
takes a course of penicillin for another purpose
that is also effective in treating syphilis.
Syphilis infections present serious risks during
pregnancy.14 Congenital transmission can occur
before or at delivery regardless of a woman’s
stage of disease. Infection may lead to spontaneous abortion, stillbirth, preterm birth, or
congenital infection. Congenital syphilis may
result in blindness, deafness, or other nervous
and musculoskeletal abnormalities in the infant.
Primary and secondary syphilis can facilitate the
transmission of HIV in sexual partnerships
involving individuals of discordant HIV
serostatus.15 Therefore, the incidence of HIV
transmission is directly linked to syphilis rates.
In most prison settings that test for syphilis,
individuals are first tested with either the rapid
plasma reagin (RPR) or the Venereal Disease
Research Laboratory (VDRL) test. Because of
the large number of false positive results with
these tests, positive tests are confirmed with more
specific tests such as the Fluorescent Treponemal
Antibody Absorption test (FTA–ABS).16 Persons
with positive confirmatory tests are offered
antibiotic treatment.17 In jails, effective screening
policies have been altered to account for the
probability that detainees will be released before
confirmed test results are available. In these
settings, detainees are tested upon admission with
the STAT RPR (a 15-minute onsite test of a
detainee’s blood). Detainees with a reactive test
are treated. In some jails that have onsite laboratory facilities, such as the Cook County Jail in
Chicago, a routine quantitative RPR is performed

on samples that are reactive to STAT RPR.
Jail personnel then review an online syphilis
registry to determine whether detainees with
reactive serologies are in the registry and require
treatment.18 All positive STAT RPR tests are
confirmed and staged with RPRs and FTAs,
which allows appropriate entry into the syphilis
registry. Because most jails do not have onsite
laboratories and immediate access to registries,
the model assumes that detainees are treated
based only on results of the STAT RPR without
additional testing to prevent persons with syphilis
from being released before they get treatment.

Decision tree
A decision tree is a graphic representation of how
all possible events relate (stochastically) to
possible outcomes.19 The decision tree used to
analyze the cost-effectiveness of routine syphilis
screening in jails and prisons compares the health
effects and costs of two options: (1) no routine
universal screening for syphilis on intake, and
(2) routine universal screening on intake. The
decision tree used for the prison setting is shown
in figure 1.20 In the prison setting, the screening is
done with an RPR test on intake, followed by a
FTA–ABS confirmation of positive RPR tests and
treatment of inmates with confirmed tests. In jails,
screening is done with a STAT RPR, followed
by treatment of inmates with reactive serologies.
The models include FTA–ABS confirmation of
positive tests, but do not include costs associated
with entry into and verification with the syphilis
registry. Because clinical manifestations of the
disease are similar for men and nonpregnant
women, a single model was developed for both
sexes. Pregnant women were not considered here.
The decision tree follows a hypothetical cohort of
10,000 individuals throughout their lifetimes. The
model was based on several assumptions. The
first assumption was that at any point during
infection, syphilis might be diagnosed and an
infected person treated for it after release from
jail or prison. The second assumption was that all
inmates who tested positive with either the STAT
RPR alone (jail) or both the RPR and FTA
(prison) tests would receive treatment before
release and that the treatment had a 100-percent

85
Figure 1. Decision Analysis Tree for Examining the Cost-Effectiveness of Screening Men and Women
in Prisons for Syphilis
No Dis

Rx
Prim / Trans

Rx
No Rx / Second

No Screen

Inadverted RX
No Rx / Latent

Rx
Disease

Inadverted Rx

Second / Trans

Rx

No Rx / Latent
Inadvertent Rx

(-) RPR - Travel - No Trans
No Dis.

Late Latent
Late Benign

No Rx
CardioVascular
Late Latent

No Inadverted Rx

Neuro
Late Benign

Rx

Latent / No Trans

Rx

No Inadverted Rx

No Rx
CardioVascular
Late Latent

No Inadvertent RX
(-) FTA - Travel

(+) RPR - FTA
(+) FTA - Rx - Travel

Neuro
Late Benign
No Rx
CardioVascular
Rx
Neuro

(-) RPR - Travel - Trans.
Rx
No Rx - Second. - Trans

Inadverted Rx
No Rx - Latent

Prim.

No Inadverted Rx
Rx

RPR Screen
(+) RPR - FTA

(+) FTA - Rx - Travel - No Trans
Rx

CardioVascular
Inadverted Rx

No Rx - Second. - Trans

Neuro
No Rx/Latent
Rx

No Rx - Latent

No Inadverted Rx

Late Benign
No Rx
CardioVascular

Late Latent

No Inadverted Rx
Rx

Late Latent
Rx

Inadverted Rx

(-) RPR - Travel - Trans.

Second

Late Benign
No Rx

Rx

(-) FTA - Travel - Trans.

Disease

Late Latent
Rx

Neuro

Late Benign
No Rx
CardioVascular

(-) FTA - Travel - Trans

Inadverted Rx

(+) RPR - FTA

Neuro

(+) FTA - Rx - Travel

No Rx/Latent

Inadverted Rx

Rx

Late Latent
Rx
No Inadverted Rx

Late Benign
No Rx

(-) RPR - Travel - No Trans
No Inadverted Rx

Late Latent

CardioVascular

Late Benign

Neuro

No Rx

Latent

CardioVascular
Inadverted Rx
Neuro
(-) FTA - Travel

Late Latent

(+) RPR - FTA

Rx
(+) FTA - Rx - Travel

No Inadverted Rx

Late Benign
No Rx
CardioVascular
Neuro

cure rate. The third assumption was that infected
individuals in whom syphilis was not diagnosed
because those persons were not screened or were
screened but had a false-negative test would
develop the standard stages of syphilis. The fourth
assumption was that inadvertent treatment of
syphilis with an antibiotic prescribed for other
reasons might cure the syphilis infection in some
infected individuals.
Because the length of the interval between
infection and onset of complications affects the
present value of the costs, certain assumptions
were made about time of onset of primary

infection and when complications might occur.
The model assumes that cardiovascular syphilis
requiring surgery or neurosyphilis with general
paresis would result in death 10 years earlier than
without the complication. The model assumes
also that patients with cardiovascular syphilis or
neurosyphilis would require extended medical
followup ranging from 9 to 42 years and that 2
percent of those with neurosyphilis would require
nursing home care over the remainder of their
lifetimes.
All persons in the hypothetical cohort progress
through the decision tree from the point at which

86
they enter a jail or prison until their deaths. Persons
with untreated syphilis are followed throughout
the course of the disease, including latent
infection without clinical manifestations, benign
latency, infection with cardiovascular complications,
and infection with central nervous system complications. The health outcome in the decision
models is the number of undetected syphilis
infections by stage of disease in inmates after they
have passed through intake in the jail or prison.
The model is used also to calculate the number of
persons with syphilis at the time of intake into the
jail or prison whose syphilis eventually would
develop into late-stage clinical disease.

Key parameters
The probabilities used in the syphilis decision tree
are in table 1. Probabilities include the prevalence
of syphilis in jail and prison inmates at the time of
intake. The base-case scenario uses a prevalence
of 8 percent (primary, secondary, and early latent).
Because this prevalence estimate is likely to vary
in different jail and prison settings, this value was
varied in sensitivity analyses.
The model also includes the probability of the
stage of disease in infected persons and probabilities of progression to different stages of
disease. The tree includes the probability of
diagnosis and treatment at all stages of the disease
during an individual’s lifetime, regardless of
incarceration status. The program option that
includes routine universal screening considers the
sensitivity and specificity of STAT RPR (jail
model only), RPR, and confirmatory FTA–ABS
testing for detecting the following three stages of
infection: primary, secondary, and latent.
One-way sensitivity analyses, in which the value
of only one parameter at a time was changed, were
performed on all variables in the model to determine the effect of small changes in parameter
estimates on the cost-effectiveness of the two
program options. Sensitivity analyses on the
prevalence of syphilis infection in the hypothetical cohort of inmates were reported to allow the
results to be generalized to jail and prison settings
with different prevalence levels.

Key costs
Table 2 shows the costs (in 1996 dollars) used in
the syphilis decision analyses. Future costs are
discounted to present value at an annual rate of 3
percent. The models include the cost of routine
universal screening with the STAT RPR and
RPR tests; confirmation testing of positive RPRs
with FTA–ABS tests; and treatment of
individuals who test positive with STAT RPR
(jail model) or RPR and FTA–ABS (prison
model). Treatment costs include all components
of treatment specific to each stage of infection of
persons with primary, secondary, early latent,
late latent, late benign, cardiovascular, and
neurosyphilis. Because the models do not
consider pregnant women or transmission to sex
partners, costs associated with congenital syphilis
and new syphilis cases in sex partners are not
included. Also, costs of HIV infections acquired
as a result of the increased susceptibility to HIV
caused by syphilis are not included.
Treatment costs were estimated by constructing
a clinical treatment plan for each stage of the
disease and then applying costs to each health
care service utilized. Costs for health care
services are based on the Medicare reimbursement rate reported in the Physicians’ Fee and
Coding Guide published by HealthCare
Consultants of America.21

Results
Syphilis—males and females. Tables 3 and 4
show the results of routinely screening all male
and female inmates upon intake in jails and
prisons. At an 8-percent prevalence rate of
syphilis in the hypothetical cohort of 10,000
inmates, a routine universal screening program
would detect and treat 774 inmates with syphilis,
and 542 with infectious primary or secondary
disease. Of the 774 inmates whose syphilis was
detected by the screening program, 42 would
have eventually developed late-stage clinical
disease; 4 persons would have developed
cardiovascular syphilis and 3 persons would have
developed neurosyphilis (not shown). With the
routine universal screening program, 26 inmates
would pass through intake with undetected

87

Table 1. Parameter Estimates for Syphilis Screening Decision Tree
Variable
Prevalence

Estimate (%)

Range (%)

8

0.05–25

References

Stage of Infection on Intake
Primary infection

30

Assumptiona

Secondary infection

40

Assumption

Latent infection

30

Assumption

Risk of Progression of Latent Syphilis
Without Treatment
No progression (late latent)

72

50–100

Clark and Danbolt 1964

CV, late benign

21.5

15–30

Clark and Danbolt 1964

6.5

2–10

Clark and Danbolt 1964

10

5–15

Assumption

Secondary infection

60

40–80

Assumption

Late latent infection

10

5–15

Assumption

100

80–100

Assumption

70

60–80

Assumption

100

80–100

Assumption

Sensitivity of STAT RPR

94

93–97

Blank et al. 1997

Specificity of STAT RPR

88

86–90

Blank et al. 1997

86

84–88

Larsen et al. 1995

Neurosyphilis
Infected Individual Seeks Treatment
Primary infection

Late benign, CV, CNS infection
Inadvertent Treatment
Treatment Success
b

Sensitivity of RPR
Primary infection
Secondary infection

100

98–100

Larsen et al. 1995

Latent infection

98

96–100

Larsen et al. 1995

Specificity of RPR

98

96–100

Larsen et al. 1995

84

82–86

Larsen et al. 1995

Secondary infection

100

98–100

Larsen et al. 1995

Latent infection

100

98–100

Larsen et al. 1995

Sensitivity of FTA
Primary infection

97
95–99
Larsen et al. 1995
Specificity of FTA
The assumptions in this table are based on personal communication with Vicki Pope, CDC.
b
Sensitivity and specificity of tests do not vary by disease stage in this model.
Sources: Blank, S., D.D. McDonnell, S.R. Rubin, J.J. Neal, M.W. Brome, M.B. Masterson, and J.R. Greenspan, “New
Approaches to Syphilis Control: Finding Opportunities for Syphilis Treatment and Congenital Syphilis Prevention in a Women’s
Correctional Setting,” Sexually Transmitted Diseases 24(1997): 218–228; Clark, E.G., and N. Danbolt, “The Oslo Study of the
Natural Course of Untreated Syphilis: An Epidemiologic Investigation Based on a Restudy of the Boeck-Brusgaard Material,”
Medical Clinic North America 48(1964): 613; Larsen, S.A., B.M. Steiner, and A.H. Rudolph, “Laboratory Diagnosis and
Interpretation of Tests for Syphilis,” Clinical Microbiology Review 8(1995); 1–21.
a

88
Table 2. Undiscounted Costs of Syphilis Screening and Treatment of Initial Infection and Complications
Estimatea (1996 $)

Cost
Screening Program Costs
Blood draw
STAT RPR
RPR screening test
FTA confirmation test
Treatment (at intake)
Disease Costs by Stage of Infectionb
Primary and secondary stage
Late latent stage
Late benign stage
Cardiovascular syphilis
Initial treatment—no surgery
Initial treatment—surgery
Annual followup
Neurosyphilis
Initial treatment
Meningovascular complications
General paresis
a
All cost estimates were varied 20% higher and lower in sensitivity analyses.
b
Costs are for diagnosis and treatment outside the jail or prison setting.

$10.00
3.00
3.00
4.50
33.00
331.00
422.00
1,491.00
3,900.00
32,641.00
740.00
8,899.00
213,615.00
159,470.00

Table 3. Number of Syphilis Infections After Intake Into Jails and Prisons With and Without
Routine Universal Screening
No-Screening Option

Routine Universal
Screening Option

Infections Treated*

240

8

232

Secondary syphilis infections

320

10

310

Latent syphilis infections

240

8

232

Total
800
26
* Infections Treated = No-Screening Option – Routine Universal Screening Option.

774

Primary syphilis infections

Table 4. Costs of Screening and No-Screening Options for Syphilis in Prisons and Jails
Cost

No-Screening Option

Routine Universal
Screening Option

Additional Cost/Savings of
Routine Universal
Screening Option*

Prisons
Program cost

$0

$160,648

$160,648

Disease costs

1,975,087

140,065

!1,835,022*

Total costs

1,975,087

300,713

!1,674,374

Program cost

$0

$196,600

$196,600

Disease costs

1,975,087

140,065

!1,835,022

1,975,087

336,665

!1,638,422

Jails

Total costs
* Negative value indicates savings.

89
syphilis, 18 of whom would have primary or
secondary infections. Only 1 person whose
syphilis was not detected on intake into the jail or
prison would eventually develop late-stage
clinical disease, with a 16-percent chance of
developing either cardiovascular or neurosyphilis.
In the prison setting with no routine universal
screening program, the lifetime cost of syphilis
in the hypothetical cohort would approach $2
million (see table 4). Implementing a routine
universal screening program that included
treatment of persons identified as infected
would cost $160,648. Disease costs associated
with routine universal screening would be only
$140,065. Thus, a routine universal screening
program might save almost $1.7 million compared to the no-screening option (see table 4).
In jail settings, the cost of a routine universal
screening program might be slightly higher
because of overtreatment associated with the low
specificity (88 percent) of the STAT RPR test.
The cost of the routine universal screening option
would be $196,600. Approximately 1,104 inmates
who tested positive for syphilis but who were not
infected would receive treatment for an added
cost of $30,360. Savings associated with the jail
program also would approach $1.7 million (see
table 4).
Sensitivity analyses indicate that the finding that
routine universal screening saves costs is stable
under reasonable variations in parameter estimates. Results indicate that routine universal
screening programs would save money in both
jails and prisons in which the prevalence of
syphilis in new inmates was greater than 1
percent. In jails, where release before treatment
can result from delayed diagnosis, overtreatment
costs would be offset by savings in disease costs
if immediate treatment based on a positive STAT
RPR prevented at least five inmates with syphilis
from being released untreated and lost to
followup.
Discussion. Routine universal screening for
syphilis upon intake in jails and prisons is a costsaving strategy for identifying and treating
disease in high-risk populations. Although such

programs require initial investments, the savings
in downstream medical costs of syphilis should
more than pay for the program. Although the costeffectiveness of routine universal screening only
for costs borne by government was not analyzed,
such an analysis would likely have a similar
result. This population may have limited access to
private health insurance, therefore, government
programs will pay much of the downstream
medical costs.
The syphilis analyses have several limitations.
First, the analysis did not account for the
transmission of syphilis during pregnancy. Thus,
the costs and health outcomes associated with
spontaneous abortions, stillbirths, neonatal
mortality, neonatal treatment, and long-term
complications of congenital syphilis were not
included. These costs and health consequences
can be significant. In a 1993 study of female
inmates in the New York City Jail, of the 727
women examined upon admission, more than 2
percent were pregnant and had syphilis.22 Infants
born with congenital syphilis remain hospitalized
7–9 days longer than uninfected infants, at an
additional cost of $5,000–$9,000.23 If costs
associated with congenital syphilis had been
included, the routine universal screening option
would have saved even more money.
The analysis also did not include the cost of HIV
infections attributable to syphilis in inmates.
Identifying and treating syphilis in inmates in jails
and prisons before release has the potential to
prevent transmission of new HIV infections.
Using the model developed by Chesson and
colleagues,24 it was estimated that the jail and
prison screening programs modeled in this paper
also would prevent 10–11 new HIV infections
attributable to syphilis. The lifetime medical cost
of HIV is an estimated $195,188 per infected
person.25 Including these costs would increase the
cost savings of a routine universal screening
program.
Finally, the model did not include transmission
of syphilis to sex partners of members of the
hypothetical cohort. The cost-saving nature of
a routine universal screening program results
overwhelmingly from medical costs prevented

90
by detecting infection before it progresses to
another stage or late-stage disease. The benefits of
interrupting transmission in the community have
not been captured. Public health benefits of a
routine screening program are likely to be far
greater than those projected in this study.

Gonorrhea and Chlamydia
The same decision tree model was used for both
gonorrhea and chlamydia because the only
significant difference between these diseases for
purposes of this study is the treatment regimen.
The model was applied to men and women
separately because men and women experience different health outcomes and sequelae.
Undiagnosed or untreated gonorrhea and
chlamydia may lead to epididymitis in men and
pelvic inflammatory disease (PID) in women.
Therefore, separate gonorrhea and chlamydia
models were devised for men and women.
Each model considers two program options: (1)
universal, routine screening at intake followed by
treatment of inmates who test positive and (2) no
routine screening, but an offer of presumptive
treatment to inmates who request it because of
symptoms. Each model follows individuals in the
cohort as they are diagnosed and treated before
release or as they progress undiagnosed or
untreated for the disease. The models are used
to estimate the difference between a routine
screening program and a program in which
inmates are treated presumptively for an STD.
The difference between the programs is expressed
in terms of total and incremental (moving from
presumptive treatment to routine screening)
health care costs and two health outcomes: (1) the
number of cases of sequelae and (2) the number
of inmates with cases of undiagnosed or uncured
gonorrhea or chlamydia. The first health outcome
shows the benefit of the routine screening
program in terms of the number of cases of
sequelae prevented (i.e., the difference between
the number of resulting cases of sequelae with a
presumptive treatment program and a routine
screening program). The second health outcome
shows the benefits of a routine screening program

in terms of the number of gonorrhea and chlamydia infections detected.

Decision tree models
Figures 2 and 3 show the decision models used to
examine gonorrhea screening in men and women.
Figures 4 and 5 show the models used to examine
chlamydia screening in men and women. The
structure of each model is described before the
data chosen for each probability and cost value is
discussed. This is because even though the same
model structure is used to describe the programs
in prisons and jails, the environments in these two
types of corrections facilities vary, causing
different probabilities to be used.
Data on the probabilities of events and the costs
of the STD tests, treatment, and sequelae were
collected from a variety of sources, including
published studies, working papers, and expert
opinion. All costs are expressed in 1996 dollars.
Costs that were collected from reports before or
after 1996 were adjusted using the Medical
Component of the Consumer Price Index.26 To
check the robustness of the assumptions, sensitivity analyses were conducted to assess the effect
of varying values of uncertain parameters on the
results in all of the models.
Decision tree models—men. Figures 2 and 4
show the decision trees for screening male
inmates in prisons and jails for gonorrhea and
chlamydia. There are two program options: (1)
routine screening on intake or (2) no routine
screening on intake, instead presumptively
treating based on symptoms. The tree is further
divided between those who are and those who are
not truly infected with gonorrhea or chlamydia to
consider all of the different outcomes for each of
these groups. Those who are truly infected may or
may not display symptoms, but with the first
program option, all inmates will be screened.
Starting with the routine-screening-on-intake
program option, the results of a test of truly
infected men may be either positive (true positive)
or negative (false negative). If the test results are
positive and those tested receive treatment, the

91
Figure 2. Decision Analysis Tree for Examining the Cost-Effectiveness of Screening Men for Gonorrhea

Treatment Success
Treated
TreatmentRate

Complications
Not treated
1-TreatmentRate

Prevalence

Complications
1-Sensitivity

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

True Specificity

No Gonorrhea
1-Prevalence

TreatmentRate
Not treated
1-TreatmentRate
Treatment Success

Symptomatic
ProbabilitySymptoms*0.5

Efficacy*Compliance

Complications
Asymptomatic
1-(ProbabilitySymptoms*0.5)

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

Symptomatic
No Gonorrhea
1-Prevalence

ProbabilitySymptomsnoGonorrhea*0.5
Asymptomatic
1-(ProbabilitySymptomsnoGonorrhea*0.5)

treatment either does or does not treat the
infection. If the treatment fails to cure the
infection, men may develop epididymitis, a
sequela of both gonorrhea and chlamydia. If a
man has a positive test result and is not treated for
some reason (e.g., he is no longer incarcerated
when test results are received), then it is assumed
that he has a probability of developing epididymitis. If men are truly infected, but their test
results are negative, then they are not treated and
may develop epididymitis.
Truly uninfected men also will be tested with a
routine screening on intake. If the test results are
negative (true negative), then there is no more
interaction between the health staff and the
inmates. If the test results are positive (false

Epididymitis
no_Epididymitis

no_Epididymitis

no_Epididymitis
no_Epididymitis
no_Epididymitis

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

Prevalence

no_Epididymit

Epididymitis

Complications
Treatment Failure
1-(Efficacy*Compliance)

Gonorrhea

Epididymitis

no_Epididymitis
Treated

False +
1-Specificity

No Routine Screen

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

False -

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

Sensitivity
Gonorrhea

no_Epididymitis
Complications

Treatment Failure
1-(Efficacy*Compliance)

True +

Routine Screen

Efficacy*Compliance

Epididymitis
no_Epididymitis

Epididymitis
no_Epididymitis

no_Epididymitis
no_Epididymitis

positive) and the inmates are still incarcerated at
the time of test results, then they will be treated.
Since these men are truly uninfected, there is no
chance of developing sequelae of gonorrhea or
chlamydia.
In the absence of a routine screening program,
treatment is administered only if inmates have
symptoms and request it. It is assumed that onehalf of symptomatic inmates will request treatment, but that inmates will not request treatment
in the absence of symptoms. The truly infected
may be either symptomatic or asymptomatic. The
truly infected who are symptomatic and who
request treatment are treated, and the treatment is
successful or not successful. If the treatment fails,
there is a possibility of developing sequelae of

92
Figure 3. Decision Analysis Tree for Examining the Cost-Effectiveness of Screening Women for Gonorrhea
Complications
Treatment Success
Efficacy*Compliance
Treated

ProbabilityPIDGonorrheaTreated
No Complications
1-ProbabilityPIDGonorrheaTreated
Complications

TreatmentRate
Treatment Failure
True +

1-(Efficacy*Compliance)

ProbabilityPID
No Complications

Sensitivity

1-ProbabilityPID
Complications
Not Treated

Gonorrhea

1-TreatmentRate

Prevalence

1-ProbabilityPID
Complications
False -

Routine Screen

1-Sensitivity

ProbabilityPID
No Complications
1-ProbabilityPID

True Specificity

No Gonorrhea
1-Prevalence

ProbabilityPID
No Complications

1-Specificity

TreatmentRate
Not Treated
1-TreatmentRate

Efficacy*Compliance
Symptomatic
Treatment Failure
1-(Efficacy*Compliance)
Complications
ProbabilityPID
No Complications
1-ProbabilityPID
Symptomatic
No Gonorrhea
1-Prevalence

ProbabilitySymptomsnoGonorrhea*0.5
Asymptomatic
1-(ProbabilitySymptomsnoGonorrhea*0.5)

gonorrhea or chlamydia. The truly infected who
are asymptomatic are not tested or treated and
may or may not develop epididymitis. The truly
uninfected inmates may have nonspecific symptoms that cause them to present for treatment for
gonorrhea or chlamydia. They may present painful urination in women and men, and vaginal
discharge in women, which may be nonspecific
and indicate infections other than gonorrhea and
chlamydia. Because these inmates would be
symptomatic, it is assumed that they would be
treated presumptively. Since they are truly
uninfected, they will not develop sequelae. The

no_PID

no_PID

ProbabilityPIDGonorrheaTreated
No Complications

ProbabilityPID
No Complications
1-ProbabilityPID

1-(ProbabilitySymptoms*0.5)

PID

no_PID

Prevalence
No Routine Screen

no_PI

no_PID

1-ProbabilityPIDGonorrheaTreated
Complications

ProbabilitySymptoms*0.5

Asymptomatic

PID

PID

Complications
Treatment Success

Gonorrhea

no_PI

no_PID
Treated

False +

PID

PID
no_PID
PID
no_PID

PID
no_PID

no_PID
no_PID

uninfected who do not have symptoms are
assumed never to present or request treatment.
Decision tree models—women. Figures 3 and
5 show the decision trees for gonorrhea and
chlamydia applied to female inmates. These
decision trees are similar to those applied to
male inmates except for two differences. First,
undiagnosed, untreated, or undertreated gonorrhea
and chlamydia can lead to PID in women. Second,
for men, it is assumed that if treatment is provided
and successful, then men are cured of gonorrhea
or chlamydia and have no chance of developing

93
Figure 4. Decision Analysis Tree for Examining the Cost-Effectiveness of Screening Men for Chlamydia
Treatment Success
Treated
TreatmentRate

Complications
Not treated
1-TreatmentRate

Prevalence

Complications
1-Sensitivity

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

True Specificity

No Chlamydia
1-Prevalence

TreatmentRate
Not treated
1-TreatmentRate
Treatment Success

Symptomatic
ProbabilitySymptoms*0.5

Efficacy*Compliance

Complications
Asymptomatic
1-(ProbabilitySymptoms*0.5)

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

Symptomatic
No Chlamydia
1-Prevalence

ProbabilitySymptomsnoChlamydia*0.5
Asymptomatic
1-(ProbabilitySymptomsnoChlamydia*0.5)

sequelae. For women, there is a slight risk of
developing PID even if they are treated successfully for gonorrhea or chlamydia, if treatment is
provided after the infection has already ascended
to the uterus and fallopian tubes.
Key parameters—men and women. Table 5
shows the data values used as probabilities in
base case (column 2) and sensitivity (column 3)
analyses. Based on previous site- and sex-specific
studies, the models assume a 6-percent prevalence of symptomatic or asymptomatic gonorrhea infection and an 8-percent prevalence of
symptomatic or asymptomatic chlamydia
infection in both the male and female cohorts.

Epididymitis
no_Epididymitis

no_Epididymitis

no_Epididymitis
no_Epididymitis
no_Epididymitis

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

Prevalence

no_Epididymi

Epididymitis

Complications
Treatment Failure
1-(Efficacy*Compliance)

Chlamydia

Epididymitis

no_Epididymitis
Treated

False +
1-Specificity

No Routine Screen

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

False -

ProbabilityEpididymitis
No Complications
1-ProbabilityEpididymitis

Sensitivity
Chlamydia

no_Epididymitis
Complications

Treatment Failure
1-(Efficacy*Compliance)

True +

Routine Screen

Efficacy*Compliance

Epididymitis
no_Epididymitis

Epididymitis
no_Epididymitis

no_Epididymitis
no_Epididymitis

These assumptions are varied in sensitivity
analyses. Although many gonorrheal and
chlamydial infections may be asymptomatic,
when symptoms are present they are much more
noticeable to men than to women. The models
include probabilities associated with the development of sequelae for inmates that are undiagnosed
and untreated (including treatment failures).
The routine screening program for gonorrhea
and chlamydia includes the use of a nucleic acid
amplification test, Ligase Chain Reaction (LCR).27
LCR is an FDA-approved urine test that is highly
sensitive and specific. An additional advantage is
a noninvasive specimen collection process.

94
Table 5. Probabilities Used in Baseline and Sensitivity Analyses
Parameter
Prevalence
Gonorrhea
Chlamydia
Progression to Adverse
Sequelae
Epididymitis

Probabilities*

Probability Ranges*

Sources

0.06
0.08

0.01–0.20
0.01–0.30

Glaser and Greifinger 1993
Glaser and Greifinger 1993

0.02

0.01–0.04

Holmes et al. 1993; Washington,
Johnson, and Sanders 1987

0.15
0.15
0.06

0.10–0.20
0.10–0.40
0.01–0.10

Holmes et al. 1993
Haddix, Hillis, and Kassler 1995

0.95 (M), 0.35 (W)
0.67 (M), 0.30 (W)

0.90–0.99 (M), 0.20–0.80 (W)
0.15–0.80 (M), 0.30–0.50 (W)

Holmes et al. 1993
Washington, Johnson, and
Sanders 1987

0.07 (M), 0.07 (W)
0.07 (M), 0.07 (W)

0.10–1.00 (M), 0.10–1.00 (W)
0.10–1.00 (M), 0.10–1.00 (W)

Haddix, Hillis, and Kassler 1995
Haddix, Hillis, and Kassler 1995

0.98 (M), 0.96 (W)
0.86 (M), 0.90 (W)

0.96–1.00 (M), 0.72–1.00 (W)
0.83–0.95 (M), 0.86–0.96 (W)

Koumans et al. 1998; Black 1997
VanDoornum et al. 1995

0.99 (M), 0.99 (W)
0.98 (M), 0.99 (W)

0.98–1.00 (M), 0.96–1.00 (W)
0.97–1.00 (M), 0.99–1.00 (W)

Koumans et al. 1998
VanDoornum et al. 1995

0.50
1.00

0.01–1.00
—

0.97
0.97

0.94–1.00 (M), 0.50–1.00 (W)
0.93–0.98 (M), 0.97–1.00 (W)

PID
If disease is untreated
Gonorrhea
Chlamydia
If disease is treated
Probability of Symptoms
Truly infected
Gonorrhea
Chlamydia
Uninfected
Gonorrhea
Chlamydia
LCR Urine Test
Sensitivity
Gonorrhea
Chlamydia
Specificity
Gonorrhea
Chlamydia
Treatment Before Release
Jail
Prison
Treatment
Efficacy
Cefixime (GC)
Azithromycin (CT)

Glaser and Greifinger 1993
Glaser and Greifinger 1993

Friedland et al. 1996
Martin et al. 1992
Haddix, Hillis, and Kassler 1995
Glaser and Greifinger 1993

Compliance
1.00
0.50–1.00
* M = Men, W = Women
Sources: Glaser, J.B., and R.B. Greifinger, “Correctional Health Care: A Public Health Opportunity,” Annals of Internal Medicine 118(2)(1993):
139–145; Holmes, M.D., S.M. Safyer, N.A. Bickell, S.H. Vermund, P.A. Hanff, and R.S. Phillips. “Chlamydial Cervical Infection in Jailed
Women,” American Journal of Public Health 83(4)(1993): 551–55; Washington, A.E., R.E. Johnson, and L.L. Sanders, “Chlamydia
trachomatis Infections in the United States: What Are They Costing Us?” Journal of the American Medical Association 257(15)(1987):
2070–2072; Haddix, A.C., S.D. Hillis, and W.J. Kassler, “The Cost-Effectiveness of Azithromycin for Chlamydia trachomatis Infections in
Women,” Sexually Transmitted Diseases 22(1995): 274–280; Koumans, E.H., R.E. Johnson, J.S. Knapp, and M.E. St. Louis, “Laboratory
Screening for Neisseria gonorrhoeae by Recently Introduced Non-Culture Tests: A Performance Review With Clinical and Public Health
Considerations,” Clinical Infectious Diseases 27(1998): 1171–1180; Van Doornum, G.J.J., M. Buimer, M. Prins, C.J.M. Henquet, R.A.
Coutinho, P.K. Plier, S. Tomazic-Allen, H. Hu, and H. Lee, “Detection of Chlamydia trachomatis Infection in Urine Samples From Men and
Women by Ligase Chain Reaction,” Journal of Clinical Microbiology 33(1995): 2042–2047; Friedland, L.R., R.M. Kulick, F.M. Biro, and A.
Patterson, “Cost-Effectiveness Decision Analysis of Intramuscular Ceftriaxone Versus Oral Cefixime in Adolescents With Gonococcal
Cervicitis,” Annals of Emergency Medicine 27(1996): 299–304; Martin, D.H., T.F. Mroczkowski, Z.A. Dalu, J. McCarty, R.B. Jones, S.J.
Hopkins, and R.B. Johnson, “A Controlled Trial of a Single Dose of Azithromycin for the Treatment of Chlamydial Urethritis and Cervicitis,”
New England Journal of Medicine 327(13)(1992): 921–925.

95
Figure 5. Decision Analysis Tree for Examining the Cost-Effectiveness of Screening Women for Chlamydia
Complications
Treatment Success

ProbabilityPIDChlamydiaTreated
No Complications

Efficacy*Compliance
Treated

1-ProbabilityPIDChlamydiaTreated
Complications

TreatmentRate
Treatment Failure
True +

ProbabilityPID
No Complications

1-(Efficacy*Compliance)
Sensitivity

1-ProbabilityPID
Complications
Not Treated

Chlamydia

1-TreatmentRate

Prevalence

1-ProbabilityPID
Complications
False -

Routine Screen

1-Sensitivity

ProbabilityPID
No Complications
1-ProbabilityPID

True Specificity

No Chlamydia
1-Prevalence

ProbabilityPID
No Complications

1-Specificity

TreatmentRate
Not Treated
1-TreatmentRate

Efficacy*Compliance
Symptomatic
Treatment Failure
1-(Efficacy*Compliance)
Complications
ProbabilityPID
No Complications
1-ProbabilityPID
Symptomatic
No Chlamydia
1-Prevalence

ProbabilitySymptomsnoChlamydia*0.5
Asymptomatic
1-(ProbabilitySymptomsnoChlamydia*0.5)

The substantially shorter sentences in jail settings
may have an important effect on the effectiveness
of routine STD screening upon intake. The
turnaround for test results is typically longer than
48 hours, but more than one-half of jail inmates
are released within 48 hours of intake. Given
these constraints, it was assumed that jail inmates
who tested positive upon intake would be present
in the corrections facility for test results and
treatment less than 50 percent of the time,
whereas those in prisons would be in the
correctional facility 100 percent of the time.
The model includes also the efficacy and compliance associated with specific treatments for
gonorrhea and chlamydia. Following the 1998
CDC STD Treatment Guidelines, the use of a
single-dose oral treatment regimen of cefixime

no_PID

no_PID

ProbabilityPIDChlamydiaTreated
No Complications

ProbabilityPID
No Complications
1-ProbabilityPID

1-(ProbabilitySymptoms*0.5)

PID

no_PID

Prevalence
Asymptomatic

no_P

no_PID

1-ProbabilityPIDChlamydiaTreated
Complications

ProbabilitySymptoms*0.5

No Routine Screen

PID

PID

Complications
Treatment Success

Chlamydia

no_P

noPID
Treated

False +

PID

PID
no_PID
PID
no_PID

PID
no_PID

no_PID
no_PID

for gonorrhea and a single-dose oral treatment
regimen of azithromycin for chlamydia to ensure
full compliance was assumed. Dispensing singledose treatments may be considered safer and more
feasible than multiple-dose regimens in jails and
prisons.

Key costs—men and women
Table 6 shows the costs used in base case
(column 2) and sensitivity (column 3) analyses.
All costs are valued in 1996 dollars. Costs and
benefits that would be incurred after the first year
are discounted at an annual rate of 3 percent. The
costs of gonorrhea and chlamydia urine testing,
the treatment of cases diagnosed at intake, and the
lifetime costs of disease not detected upon intake
or treated during a late stage of disease have been
included.

96
Table 6. Costs Used in Baseline and Sensitivity Analyses
Component

Cost per
Inmate*

Cost Ranges*

Sources

Program Costs (public sector prices)
Urine test

$8.18

$5.00–15.00

Walsh 1998

Cefixime (Gonorrhea)

5.45

2.00–10.00

Friedland et al. 1996

Azithromycin (Chlamydia)

9.50

5.00–20.00

Haddix, Hillis, and Kassler 1995

527.00

300–1,000

Washington, Johnson, and
Sanders 1987

Lifetime Costs of Sequelae
Epididymitis

Pelvic inflammatory disease (PID)
1,430.00
1,100–5,500
Rein et al. 2000
* Valued in 1996 dollars
Sources: Walsh, C., “Model for Resource Allocation to Prevent Pelvic Inflammatory Disease Due to Infection with Chlamydia
trachomatis,” Ph.D. diss., University of North Carolina, Chapel Hill, 1998; Friedland, L.R., R.M. Kulick, F.M. Biro, and A.
Patterson, “Cost-Effectiveness Decision Analysis of Intramuscular Ceftriaxone Versus Oral Cefixime in Adolescents With
Gonococcal Cervicitis,” Annals of Emergency Medicine 27(1996): 299–304; Haddix, A.C., S.D. Hillis, and W.J. Kassler, “The
Cost-Effectiveness of Azithromycin for Chlamydia trachomatis Infections in Women,” Sexually Transmitted Diseases 22(1995):
274–280; Washington, A.E., R.E. Johnson, and L.L. Sanders, “Chlamydia trachomatis Infections in the United States: What Are
They Costing Us?” Journal of the American Medical Association 257(15)(1987): 2070–2072; Rein, D., W. Kassler, K. Irwin,
and L. Rabiee, “Direct Medical Cost of Pelvic Inflammatory Disease and its Sequelae: Decreasing, but Still Substantial,”
Obstetrics and Gynecology 95(2000): 397–402.

The program costs include testing and treatment
costs. In particular, the testing costs include costs
of the LCR urine test materials and labor for
processing these tests.28
The expected lifetime costs of a case of epididymitis29 and a case of PID30 were derived from
the literature. The cost of PID includes the direct
medical costs of PID and three of its most
common sequelae: chronic pelvic pain, ectopic
pregnancy and tubal-factor infertility. Because
of the controversy over the representativeness
of medical claims data on which Rein and
colleagues’ estimate is based, the estimate for
the baseline amount for PID was increased by
30 percent.

Results
Gonorrhea—men
Table 7 shows the results of routinely screening
male inmates at intake for gonorrhea. For a
hypothetical cohort of 10,000 male prison inmates
with a prevalence of 6 percent, a routine screening
program would prevent 5 cases of epididymitis
and detect 296 cases of undiagnosed or untreated
gonorrhea. A routine screening program for men

in prisons and jails would not be cost saving in
terms of cases of epididymitis averted. An
important concern with gonorrhea and chlamydia
infections in men is ensuring treatment of men in
order to prevent transmission to their sex partners,
especially female sex partners who experience
more serious and costly sequelae than men.
Therefore, the most important outcome among
men is the number of untreated infectious
gonorrhea cases that may be detected by routinely
screening on intake.
This program would detect a substantial number
of untreated infectious cases of gonorrhea and
perhaps decrease rates of transmission to sex
partners. It would cost approximately $267 to
detect a case of gonorrhea. This is not cost saving
but may be considered cost effective.
A routine screening program costs more in jails
because the health care system may invest
substantially in testing but may not be able to
treat all detected cases of gonorrhea owing to the
high rate and quick turnover of the inmates.
Therefore, the full benefits of screening may not
be realized.

97
Table 7. Cost-Effectiveness of a Program to Screen Men Routinely for Gonorrhea, by Setting

Total Costs

Number of Cases
of Epididymitis
Averted

Number of Cases
of Untreated Infectious
Gonorrhea Detected

Additional costs of
routine screening on
intake*

$78,900

—

—-

Number of cases
averted/detected by
routine screening on
intake

—

5

296

Net cost per case
averted/detected

—

$15,780

$267

Additional costs of
routine screening on
intake*

$80,100

—

—

Number of cases
averted/detected by
routine screening on
intake

—

0.19

10

$421,579

$8,010

Prisons

Jails

Net cost per case
averted/detected
—
* As compared with presumptive treatment strategy option.

Table 8. Cost-Effectiveness of a Program to Screen Women Routinely for Gonorrhea, by Setting

Total Costs

Number of Cases of
Pelvic Inflammatory
Disease (PID) Averted

Number of Cases of
Untreated Infectious
Gonorrhea Detected

Additional costs of routine
screening on intake*

$24,000

—

—

Number of cases averted/
detected by routine
screening on intake

—

41

458

Net cost per case
averted/detected

—

$585

$52

Additional costs of routine
screening on intake*

$58,200

—

—

Number of cases averted/
detected by routine
screening on intake

—

16

178

$3,638

$327

Prisons

Jails

Net cost per case
averted/detected
—
* As compared with presumptive treatment strategy option.

98

Gonorrhea—women
Routinely screening women for gonorrhea on
intake into prisons and jails is not cost saving in
terms of detecting cases of gonorrhea or preventing cases of PID (table 8). A routine screening
program, however, detects many cases of
gonorrhea and, in turn, averts sequelae. This
program may be considered cost effective when
considering that it costs the health care system
approximately $585 to prevent a case of PID in
prison and $3,638 to prevent a case of PID in jail.

Sensitivity analyses
One-way sensitivity analyses were conducted on
all parameters in the prison and jail gonorrhea
screening models to determine which parameters
of the model most influenced the final results.
Sensitivity analyses are conducted to determine
whether the model results change if uncertain
parameter values are changed. One-way sensitivity analyses include varying one parameter
value in the decision trees at a time. In prisons
and jails, it did not save money to screen routinely
a hypothetical cohort of 10,000 male inmates for
gonorrhea, in terms of the number of cases of
epididymitis or the number of untreated infectious
cases of gonorrhea detected, regardless of which
parameters were varied.
For a hypothetical cohort of 10,000 women, the
models were sensitive to the following variables
(by setting): prevalence of gonorrhea (prisons and
jails), probability of progression to PID whether a
woman was or was not treated for gonorrhea (in
prison), lifetime direct medical cost of a case of
PID (prison), and the cost of the testing materials
and labor processing time (prison). It would save
money to screen female inmates routinely for
gonorrhea on intake if prevalence rates were at
least 22 percent in jails (figure 6) and at least 8
percent in prisons (figure 7). In addition, a twoway sensitivity analysis (an analysis that involves
changing two parameter values in the decision
trees simultaneously) of gonorrhea prevalence and

treatment rates in the jail setting shows that it
would save money to implement a routine
screening program if the prevalence rate were at
least 8 percent and the treatment rate is 100
percent (not shown). As the treatment rate
declines, the prevalence rate must be higher in
order for the routine screening program to save
money. If the treatment rate is about 40 percent,
then for a routine screening program to save
money, the prevalence rate must be at least 30
percent.
If the probability of progression to PID for
women not treated for gonorrhea is at least 19
percent, instead of 15 percent as in the baseline
model, then routine screening in prison will save
money. If women are treated for gonorrhea, a
routine screening program in prison will save
money as long as the probability of progression
to PID is less than 2.5 percent.
If the lifetime direct medical cost of a case of
PID is at least $2,000, then a routine screening
program for gonorrhea in prison will save money.
If the cost of a case of PID exceeds $5,000, then a
routine screening program in jail will also save
money. If the cost of the test materials and labor
time to conduct a single test does not exceed $6,
then a routine screening program in prison will
save money.

Chlamydia—men
Table 9 shows that a program of routinely
screening for chlamydia among men on intake to
prisons and jails does not save money in terms
of cases of untreated, infectious chlamydia or
epididymitis. This program, however, would
detect a substantial number of undiagnosed cases
of chlamydia and perhaps decrease transmission
from men to women. It would cost the health care
system approximately $198 in the prison setting
and almost $1,100 in the jail setting to detect a
case of uncured chlamydia. It may be considered
cost effective.

99
Figure 6. Sensitivity Analysis: Variations in Expected Value with Variations in Prevalence of
Gonorrhea in Women—Jail Setting
Sensitivity Analysis on Prevalence
$65.00
Routine Screen
No Routine Screen

$58.00

Expected Value

$51.00

$44.00

$37.00

$30.00

$23.00

$16.00
Threshold Values:
Prevalence = 0.220

$9.00

EV = $42.80
$2.00
0.010

0.082

0.155

0.227

0.300

Prevalence

* Expected Value = Program Cost per Person

Figure 7. Sensitivity Analysis: Variations in Expected Value with Variations in Prevalence of
Gonorrhea in Women—Prison Setting

Sensitivity Analysis on Prevalence
$42.00
$37.00

Routine Screen
No Routine Screen

Expected Value

$32.00
$27.00
$22.00
$17.00
$12.00

Threshold Values:
Prevalence = 0.086
EV = $16.75

$7.00
$2.00
0.010

0.058

0.105

Prevalence
* Expected Value = Program Cost per Person

0.153

0.200

100
Table 9. Cost-Effectiveness of a Program To Screen Men Routinely for Chlamydia, by Setting
Total Costs

Number of Cases of
Epididymitis Averted

Number of Cases of Untreated
Infectious Chlamydia Detected

Additional costs of routine
screening on intake*

$80,300

—

—

Number of cases averted/
detected by routine
screening on intake

—

8

405

Net cost per case averted/
detected

—

$10,038

$198

Additional costs of routine
screening on intake*

$79,600

—

—

Number of cases averted/
detected by routine
screening on intake

—

2

73

$39,800

$1,090

Prisons

Jails

Net cost per case averted/
detected
—
* As compared with presumptive treatment strategy option.

Chlamydia—women
For a hypothetical cohort of 10,000 women with a
prevalence rate of 9 percent, a routine-screeningon-intake program in prison would cost approximately $10,000 more than a presumptive
treatment program (table 10). This program,
however, would result in a substantially lower
number of cases of PID and untreated or undiagnosed cases of chlamydia. It would cost the
health care system only $198 in the prison setting
to prevent a case of PID and $18 to detect a case
of untreated infectious chlamydia.
Because the rate of treatment before release from
jails is lower than in prisons, a routine screening
program for women in jails does not save money.
The cost per case of PID prevented is approximately $2,450, which may be considered cost
effective.

Sensitivity analyses
One-way sensitivity analyses were conducted on
all parameters in the prison and jail chlamydia
screening models. In prisons and jails, it does not
save money to screen a hypothetical cohort of
10,000 male inmates routinely for chlamydia, in

terms of the number of cases of epididymitis
averted or the number of untreated, infectious
cases of chlamydia detected, regardless of which
parameters are varied.
For a hypothetical cohort of 10,000 women, the
models were sensitive to the following variables
(by setting): prevalence of chlamydia (prison and
jail), probability of progression to PID if treated
(prison) or untreated for chlamydia (prison and
jail), lifetime direct medical cost of a case of PID
(prison and jail), and the cost of the testing
materials and labor time (prison). It saves money
to screen routinely for chlamydia on intake if
prevalence rates are at least 23 percent in jails
(figure 8) and about 9 percent in prisons (figure
9). A two-way sensitivity analysis of chlamydia
prevalence and treatment rates in jails shows that
it would save costs to implement a routine
screening program if the prevalence rate were at
least 9 percent and the treatment rate were 100
percent (not shown). As the treatment rate
declines, the prevalence rate must be higher in
order for the routine screening program to save
costs. If the treatment rate is about 40 percent,
the prevalence rate must be at least 30 percent for
a routine screening program to save costs.

101
Table 10. Cost-Effectiveness of a Program To Screen Women Routinely for Chlamydia, by Setting

Total Costs

Number of Cases of
Pelvic Inflammatory
Disease (PID) Averted

Number of Cases of
Untreated Infectious
Chlamydia Detected

Additional costs of routine
screening on intake*

$10,300

—

—

Number of cases averted/
detected by routine
screening on intake

—

52

576

Net cost per case averted/
detected

—

$198

$18

Additional costs of routine
screening on intake*

$51,400

—

—

Number of cases averted/
detected by routine
screening on intake

—

21

230

Net cost per case averted/
detected

—

$2,448

$223

Prisons

Jails

* As compared with presumptive treatment strategy option.

Figure 8. Sensitivity Analysis: Variations in Expected Value with Variations in
Prevalence of Chlamydia in Women—Jail Setting
Sensitivity Analysis on Prevalence
$65.00
Routine Screen
No Routine Screen

$58.00

$51.00

Expected Value

$44.00

$37.00

$30.00

$23.00

$16.00
Threshold Values:
Prevalence = 0.232
EV = $45.94

$9.00

$2.00
0.010

0.082

0.155

Prevalence

* Expected Value = Program Cost per Person

0.227

0.300

102
Figure 9. Sensitivity Analysis: Variations in Expected Value with Variations
in Prevalence of Chlamydia in Women—Prison Setting

Sensitivity Analysis on Prevalence
$65.00
Routine Screen
No Routine Screen

$58.00

$51.00

Expected Value

$44.00

$37.00

$30.00

$23.00

$16.00
Threshold Values:
Prevalence = 0.092
EV = $18.46

$9.00

$2.00
0.010

0.082

0.155

0.227

0.300

Prevalence

* Expected Value = Program Cost per Person

If the probability of progression to PID for those
women not treated for chlamydia is at least 31
percent, instead of 15 percent as in the baseline
model, then routine screening will save costs in
jail. For the routine screening program to save
costs in prison, the probability of progression to
PID must be at least 16 percent, instead of 15
percent as in the baseline model. Conversely, a
routine screening program will save money in
prisons as long as the probability of progression
to PID is less than 5 percent for women treated
for chlamydia.
If the lifetime direct medical cost of a case of
PID is at least $1,600, then a routine screening
program for chlamydia will save money in prison.
If the cost of a case of PID exceeds $3,900, then a
routine screening program will save money in jail.
If the cost of the test materials and labor time to
process the test does not exceed $7.20, then a
routine screening program will save money in
prison.

Discussion—gonorrhea and chlamydia
The cost-effectiveness of routine screening for
gonorrhea and chlamydia in jails and prisons, as
examined using many and diverse data sources,
had variable results. Screening is most cost
effective in women with a high prevalence of
disease and for whom high treatment rates before
release can be achieved. Screening does not
appear to be cost effective in preventing epididymitis in men, but the net costs of detecting
infections in men are reasonable. Thus, screening
in male populations may be considered a valid
strategy for preventing transmission to women.
In jail settings, screening programs should be
designed to test as early as feasible after intake to
enable treatment before release and to coordinate
with local public health facilities to ensure
treatment of inmates who require treatment after
release.

103
The gonorrhea and chlamydia analyses have
several limitations. The baseline estimates of
averted costs or savings results are sizable
underestimates. The benefits of routine screening
on intake for each disease are understated because
they exclude some specific direct medical costs
that might be prevented as a result of a routine
screening program. In particular, this model did
not consider the potential role of gonorrhea and
chlamydia infections in facilitating the transmission of HIV and the increased susceptibility to
HIV. The model did not include morbidity and
costs associated with the transmission of gonorrhea and chlamydia from index cases to secondary
partners. This model also did not consider the
issue of reinfection of an index patient by a
partner who is infected and does not receive
effective treatment. The costs of gonorrhea and
chlamydia infections during pregnancy that lead to
endometritis (infection of the uterine lining or
endometrium), chorioamnionitis (infection of the
fetal sac), or congenital infection of the infant that
may cause serious eye and respiratory infections
were not included. The benefits of preventing
these costs, regardless of how minimal the costs
may be, would favor implementing a routine
screening program. If any of the averted costs
mentioned above were included in the models,
then the results would show the routine-screeningon-intake programs to be more cost effective and
possibly cost saving, even at low to moderate
prevalence rates.
Conversely, these models may have underestimated the program costs. In particular, none
of the costs of counseling, partner elicitation,
notification and referral, or recontacting inmates
who are released before they get their test results
were included. These costs were not considered
because it may not be feasible in many jail
settings to provide individual or group counseling
or partner elicitation services during the short time
many inmates are in jail. In addition, only the
single-dose treatments for gonorrhea and
chlamydia recommended by CDC were considered because these are readily administered in
corrections settings (e.g., directly observed
therapy). Use of slightly less expensive multiple-

dose antibiotic regimens, if they could be
administered in a way that would ensure
reasonable adherence, may be an option in some
facilities. Dual treatment for gonorrhea and chlamydia when only one such infection is detected on
screening for a single disease also was not considered; this treatment approach may be cost
effective in some settings.31 Adverse reactions to
cefixime and azithromycin were not considered
because they have been found to be minimal.32
Furthermore, the costs associated with urine-based
screening may be lower than use of tests not based
on urine testing, which require time of a health
care provider and physical examination rooms to
obtain a urethral specimen from a man or an
endocervical specimen from a woman. Finally,
program costs may be underestimated because
treatment of asymptomatic persons who request
treatment owing to sexual contact with an infected
partner was not considered.
Second, the results presented here may not lend
themselves to generalization. Key parameter
values, such as prevalence data, may vary
tremendously among facilities and geographic
regions.
Third, separate models were estimated for each
disease, ignoring the possibility that economies of
scale could be achieved by screening for multiple
diseases at once. For example, one urine sample
may be collected to test for both gonorrhea and
chlamydia. Therefore, the program test costs for
each disease may be slightly lower than the
estimates used in the models. This would change
the results only slightly, however, since the only
difference would be with the urine specimen
collection materials (i.e., the time of the person
who explains the purpose of the test and requests
a urine sample and the container for the urine
sample).
Finally, prisons and jails were treated as separate
institutions. Realistically, many inmates in jail
move to prisons later, but the hypothetical cohorts
that were used did not consider double counting of
inmates who move directly from jails to prisons.

104

Conclusion

Notes

Given the high prevalence of STDs among
incarcerated populations and the costeffectiveness of routine screening on intake for
some STDs, corrections facilities provide an
opportunity to test and treat people who are at
high risk for STDs and who may have little access
to care outside such institutions. All 3 diseases
examined in this paper—syphilis, gonorrhea, and
chlamydia—can be substantially reduced by jails
and prisons employing STD screening on intake
programs. Although the cost-saving nature of
syphilis screening and the cost-effective nature of
gonorrhea and chlamydia screening programs in
some settings do not depend on the assumption
that inmates transmit infection to sex partners, jail
and prison screening programs have the potential
to decrease STD transmission rates to inmates’
sex partners and to the community at large
through future generations of transmission.
Routine screening for syphilis among men and
women in both prisons and jails will ultimately
result in financial savings by preventing expensive disease treatment. Routine screening
for gonorrhea and chlamydia may not generate
savings, but this approach is likely to be cost
effective in both male and female populations in
prisons and jails because of the serious nature of
sequelae in women.

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In jails, this study suggests that cost-effectiveness
of STD screening can be improved and the
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———. 1998. “Expanding Efforts to Prevent
Chlamydial Infection.” New England Journal of
Medicine 339(11): 768–770.

Zimmerman, H.L., J.J. Potterat, R.L. Dukes, J.B. Muth,
H.P. Zimmerman, J.S. Fogle, and C.I. Pratts. 1990.
“Epidemiologic Differences Between Chlamydia and
Gonorrhea.” American Journal of Public Health 80:
1338–1342.

109

Cost-Effectiveness of Preventing
Tuberculosis in Prison Populations
Zachary Taylor, M.D., M.S., and Cristy Nguyen, M.P.H.

Reported TB Cases,
United States, 1953–97

110

Reported TB Cases,
United States, 1975–97

Factors That Contributed to the
Increase in TB Cases
• Deterioration of the tuberculosis (TB)
control infrastructure
• Coinfection with TB and human
immunodeficiency virus (HIV)
• Transmission of TB in congregate settings,
including prisons
• Immigration from countries where TB is
endemic

111

TB Case Rates by State,
United States, 1997

Reported TB Cases by Race and Ethnicity,
United States, 1997

112

Reported TB Cases by Race and Ethnicity,
United States, 1997

Reported TB Cases by Race and Ethnicity,
United States, 1996 and 1997

113

Reported TB Cases by Race and Ethnicity,
United States, 1985, 1992, and 1997

Reported TB Cases by Age,
United States, 1996 and 1997

114

Change in TB Cases by Age,
United States, 1985, 1992, and 1997

TB Cases in Foreign-Born Persons,
United States, 1986–97

115

Trends in TB Cases in Foreign-Born Persons,
United States, 1986–97

Country of Origin of Foreign-Born Persons with TB,
United States, 1997

116

Change in TB Cases by Country of Origin,
United States, 1986, 1992, and 1997

TB in Correctional Facilities
• 1–22 percent of State/Federal prison
inmates are infected with TB
• In 1997, 729 inmates were reported with
active TB disease
• Reported TB outbreaks in correctional
facilities

117

Transmission of TB in
Correctional Facilities
• Confined, congregate living
• Population at risk of TB infection
• Population at risk of HIV infection

Recommendations for Screening
• Screening incarcerated populations for
infection and disease
• Rapid diagnosis and treatment of active TB
• Surveillance of active TB disease and
transmission of TB
• Preventive therapy for eligible inmates and
correctional workers

118

Objectives
• Determine the cost-effectiveness of
screening for TB in prisons
• Examine the effect of the prevalence of HIV
on the cost-effectiveness of screening
inmates
• Compare the relative cost-effectiveness of
screening correctional inmates with
screening other high-risk populations

Methods
• Markov-based decision model using DATA
3.0 by TreeAge
• Societal perspective
• 1-year time frame
• 20-year analytical horizon

119

Outcomes
• Costs
• Health effects
• Effectiveness of screening and preventive
therapy

Results of Base-Case Analysis
Strategy

Total Cost
($)

Active
TB
Cases

No
Screen

26,981,429

1,869

Screen

19,806,920

880

Results are per 100,000 inmates.

Incremental
Cost
(Savings)
($)

Active TB
Cases
Prevented

QALYs
Gained

Cost per
TB Case
Prevented
($)

Cost per
QALY
Gained
($)

---

---

---

---

---

(7,174,509)

989

301

SAVINGS SAVINGS

120

Effect of HIV Prevalence on
Effectiveness of TB Screening
% HIV Infection

Cost
(Savings)

TB Cases
Prevented

0

($2,841,000)

692

2.3
(Base Case)

($7,174,509)

989

5

($12,261,650)

1,336

7.85

($17,631,420)

1,704

Secondary Health Outcomes
Strategy

TB Deaths

TB Deaths
Averted*

INH Hepatitis
Deaths

No Screen

12

---

0

Screen

6

6

1

*Incremental from No Screen

121

Sensitivity Analysis
Vary prevalence of latent M. tuberculosis infection
Incremental Cost per Active TB Case
Prevented ($)

Screen

Low (0.050)

Base Case
(0.122)

High (0.200)

SAVINGS

SAVINGS

SAVINGS

Sensitivity Analysis, continued
Vary prophylaxis efficacy
Incremental Cost per Active TB Case
Prevented ($)

Screen

Low (60%)

Base Case
(73%: HIV+)
(93%: HIV-)

High (93%)

SAVINGS

SAVINGS

SAVINGS

122

Sensitivity Analysis, continued
Vary treatment cost per active TB case
Incremental Cost per Active TB Case
Prevented ($)

Screen

Low ($5,000)

Base Case
($14,435)

High
($20,000)

$2,176

SAVINGS

SAVINGS

Sensitivity Analysis, continued
Vary TB case rate without preventive therapy
Incremental Cost per Active TB Case
Prevented ($)
Very low
HIV+: (0.01)

Screen

HIV-: (0.00066)

Base Case
HIV+: (0.045)
HIV-: (0.0007)

High
HIV+: (0.079)
HIV-: (0.0012)

SAVINGS

SAVINGS

SAVINGS

123

Cost-Effectiveness of Screening
in Various Target Populations
Target Group
HIV-infected
persons

Number of
Cost (Savings)
Active TB Cases Per Active TB
Prevented
Case Prevented
68.6
($7,843)

Source
Nguyen et al.

Prison inmates

98.9

($7,254)

Taylor et al.

Class B1/B2
immigrants

100.0

$12,929

Nguyen et al.

Physicians

20.6

$39,000

Nettleman et al.

20-year-old
AfricanAmerican men

30.7

$110,865

Schechter et al.

Cost-Effectiveness Ratio for
Selected Interventions
Intervention

Comparator

Cost Per Qaly Saved

Lap/shoulder belts
(50%)

No restraints

Cost saving

Screening inmates for No screen
latent TB infection
Annual colorectal
screening
(50–75 yr. old)
Annual
mammography
(Women 55–65 yr.
old)

Cost saving

No screen

$18,000

Annual clinical
breast exam

$150,000

124

Conclusions
• Even with current limitations, screening and preventive
therapy for TB in prison inmates are cost effective and cost
saving compared to no screening and no preventive
therapy
• Results of this analysis were quite robust to changes in
most variables
• Screening prison inmates is favored compared to screening
in other high-risk groups and to other preventive
interventions

125

Cost-Effectiveness of HIV Counseling
and Testing in U.S. Prisons
Beena Varghese, Ph.D., and Thomas A. Peterman, M.D., M.Sc., Division of HIV/AIDS
Prevention—Surveillance and Epidemiology, Centers for Disease Control and Prevention

Introduction
U.S. correctional facilities are becoming
increasingly important in the control of the human
immunodeficiency virus (HIV) epidemic. Since
the first cases of acquired immunodeficiency
syndrome (AIDS) were reported in the early
1980s, the U.S. jail and prison population has
tripled.1 The HIV prevalence rate is markedly
higher in this population than in other parts of the
community. The correctional setting can provide
easier access to this high-risk population.2
Prisons, therefore, can provide important public
health opportunities for identifying HIV-infected
persons, getting them appropriate care, and
providing counseling to prevent further HIV
transmission. They also may enable high-risk,
uninfected persons to be identified and counseled
to reduce their risk of acquiring and then
transmitting HIV infection.
Earlier studies have provided valuable information on the prevalence rates and risk factors of
HIV in jails and prisons and have discussed the
importance of HIV prevention among inmates.3
Given that HIV-prevention resources are limited,
it is important to evaluate the cost-effectiveness
of HIV-prevention programs in prison settings.
HIV counseling and testing have proven to be cost
effective in clinic settings.4 This study evaluates
the cost-effectiveness of HIV counseling and
testing among prison inmates at or near their time
of release.

Methods
Standard methods of cost-effectiveness analysis
were used, relying on a decision model from a
societal perspective.5 The societal perspective
generally includes all costs and benefits of a

program, irrespective of the source of resources,
including patient costs, lifetime treatment costs,
and morbidity costs. Given that the study
populations are prison inmates, the patient time
cost and productivity loss were not calculated in
the model.
Cost estimates for counseling and testing services
in prison were not available. Cost estimates
collected from HIV/STD clinics at the Michigan
Department of Community Health were used and
time estimates and estimates of lifetime treatment
costs were taken from the literature.6 All cost
figures are expressed in 1997 dollars. These are
additional costs that are required to add a unit of
counseling and testing services to an existing
program that offers serologic tests and voluntary
counseling in prisons. No fixed costs are included.
Estimates included the number of future HIV
infections prevented, the total and additional costs
or savings for society, and the total cost to the
prison system. Sensitivity and threshold analyses
were conducted to test the robustness of model
parameters.

Model Probabilities
Figure 1 shows a simplified decision-tree model
comparing counseling and testing with no
counseling and testing in U.S. prisons. Hammett,
Harmon, and Rhodes estimate the HIV seroprevalence for the Federal Bureau of Prisons in
1996 to be 1.5 percent.7 The average State and
regional prevalence rates ranged from 0.3 to 13.6
percent. Therefore, an HIV seroprevalence rate of
1.5 percent was used for the base-case model and
a range of 0.2–15 percent was used in the
sensitivity analysis (table 1).

126
Figure 1. Simplified Decision Tree Model Comparing HIV Prevention Programs in U.S. Prisons

HIV+ partners
/No HIV transmission
Accept counseling
& testing
(3)

(4)

0
HIV transmission

HIV- partners

HIV+

(4)

(5)
No HIV

(2)

(5)
Do not accept

Counseling
& testing

(3) go to (4)
HIV infection

(1)
Accept counseling & testing

Prison HIV
Prevention
Program

(3)

HIV(2)

(1)

HIV(2) go to (6)

No HIV
(6)

Do not accept
(3)

No Counseling HIV+
&Testing
(2) go to (4)

(6)

go to (6)

1
0

1
0

127
Table 1. Model Probabilities and Input Cost
Inputs

Probability,
Percentage (range)

Source

HIV prevalence

1.5 (1–15)

Hammett, Harmon, and Rhodes 2000

Accept voluntary counseling and
testing (CT) in prison
HIV-infected
Uninfected

60 (30–90)
50 (30–90)

Baseline assumption

20 (15–40)

Rutherford et al. 1991
Hoffman, Spencer, and Miller 1995
Toomey et al. 1998

Partners of infected individuals
who are HIV infected
Risk of HIV transmission from
infected to the uninfected partner
No counseling
With counseling

7 (5–30)
5.2 (3.75-22.5)

Mastro and DeVincenzi 1996
DeVincenzi 1994
McKay and Phillips 1991
Holtgrave et al. 1993
Power, Hartnoll, and Daviaud 1988
Casadonte et al. 1990
Van den Hoek, van Haastrecht, and Couhtino
1990
Roggenburg et al. 1990
Farley, Carter, and Hadler 1990

Risk of acquiring HIV infection for
uninfected person
No counseling
With counseling

0.35 (0.20–1.05)
0.315 (0.180–0.945)

Kamb et al. 1998
Power, Hartnoll, and Daviaud 1991
Casadonte et al. 1990
van den Hoek, van Haastrecht, and Couhtino
1990
Roggenburg et al. 1990
Farley, Carter, and Hadler 1990

Inputs
Lifetime treatment cost of HIV

Provider cost of counseling and
testing
HIV-infected
Uninfected

Cost
$175,000
($100,000–250,000)

$67.43
$22.74

Source
Holtgrave and Pinkerton 1997
Hellinger 1993
Gable et al. 1996
Farham et al. 1996
Varghese and Branson 2000

128
Correctional facilities in 16 States have mandatory
HIV testing. The rest have some form of voluntary or on-request HIV testing. The acceptance
level among inmates is not known but Hammett,
Harmon, and Rhodes have suggested that some
inmates will not accept voluntary HIV testing as
they already know their HIV status.8 Others might
be unsure of the confidentiality of the test results.
Therefore, it was assumed that 60 percent of HIVinfected inmates and 50 percent of uninfected
inmates would accept the voluntary counseling
and testing offered to them, with a range of 30–90
percent for sensitivity analysis.
Several partner notification studies found that
18–40 percent of the partners of HIV-infected
individuals are infected.9 Although a similar
estimate for the prison population is not known,
based on these studies it was assumed that 20
percent of the partners of HIV-infected inmates
would be HIV positive. Therefore, HIV may be
transmitted among the remaining 80 percent of
their partners.
Racial and ethnic minorities and injection drug
users (IDUs) are overrepresented in U.S.
correctional systems. A recent survey found that
35 percent of male and 30 percent of female
inmates have injected drugs.10 Information is not
available, however, on the risk of HIV transmission for this population.11 The risk of HIV
transmission from a released, infected inmate to
an uninfected person in the community was
therefore assumed to be similar to the risk of HIV
transmission among discordant couples. Crosssectional studies of heterosexual couples with an
infected male index patient have reported that
10–30 percent of their female partners were
infected with HIV at the time of the test.12 A
longitudinal study of sexually active, HIVseropositive persons reported that transmission to
the partner occurred in 7 percent of cases within
2 years.13 For the analysis, a no-counseling
transmission rate of 7 percent was used for the
base model, with a range of 5–30 percent in the
sensitivity analysis.

Studies have shown that 20–80 percent of people
will reduce their risk behaviors when they learn
they are HIV seropositive.14 Another study used
point estimates of 20 and 50 percent for its model
to measure the benefits of counseling and
knowledge of seropositivity on reducing risk
behavior.15 Studies have reported conflicting
evidence on the effectiveness of counseling in
risk reduction. Some have reported significant
risk reduction following counseling,16 although
others have found no significant benefits.17
Therefore, for the analysis, given the nature of the
population, a lower estimate of 25 percent was
used for the effectiveness of counseling in
reducing risk behavior and a range of 10–50
percent was used for the sensitivity analysis.
The risk of acquiring HIV infection in a sexually
transmitted disease (STD) clinic patient was
found to be 0.35 percent in the year following
enrollment in a randomized controlled prevention
trial.18 In that study, client-centered counseling
resulted in a 20 percent reduction in risk of
acquiring a sexually transmitted infection by the
12-month followup. Based on that finding, it was
estimated that counseling uninfected prison
inmates in prison would reduce their risk of
acquiring HIV infection by 10 percent in 1 year,
with a range of 5–20 percent for sensitivity
analysis.

Estimates of Future HIV Infections
Averted
To estimate the number of HIV infections that can
be prevented through counseling, information on
the risk of HIV transmission among heterosexual
couples was used,19 combined and coupled with
estimates of the effectiveness of counseling on
risk reduction.20 A value of one was assigned for
the outcome of HIV transmission and zero was
assigned for no HIV transmission. Therefore, the
expected value obtained from the analysis gives
the total number of HIV infections that would
occur by following a particular path of the
decision tree. The difference between the number
of future HIV infections resulting with and
without counseling and testing intervention yields
the number of infections that can be prevented by
the intervention (see figure 1).

129

Input Costs

treatment costs for HIV range from $154,000 to
$250,000, at a 3 percent discount rate.22 An
estimate of $175,000 was used for the base
model, with a range of $100,000–250,000 for
sensitivity analysis.

Cost estimates for counseling and testing in a
prison setting are not available in the literature.
Therefore costs in 1997 dollars of adding
counseling and testing services to an existing
HIV/STD clinic were used (see table 1). For
infected inmates, the costs of counseling and
testing include wages for administrators,
counselors, phlebotomists, and laboratory staff;
and costs of serum collection kits, EIA and
Western Blot tests, and controls.21 To the
provider, these add up to a total of $67.43 for
each seropositive inmate. Seronegative inmates
cost the provider only $22.74 each because they
do not need a Western Blot test and post-test
counseling requires less time.

Results
The baseline model shows that offering
counseling and testing to 10,000 prison inmates
(an acceptance rate of 50–60 percent and HIV
prevalence of 1.5 percent) would prevent three
future cases of HIV at a net cost of $12 per
inmate to the prison system. From a societal
perspective, offering no counseling and testing
services would result in 43 future cases of HIV
at a cost of $7,500,000. Offering voluntary
counseling and testing services would prevent
three future cases of HIV and result in societal
savings of more than $410,000 (table 2).

The societal costs include these provider costs
plus the lifetime treatment costs for HIV infection. Studies have estimated that the lifetime

Table 2. Cost and Benefits of HIV Counseling and Testing (CT) in U.S. Prisons:
Baseline Result and Sensitivity Analysis
Description of Variable
(baseline value)

Range

Cases
Averted

Societal Cost
No CT

CT

Societal
Savings

Provider
Cost

Prevalence of HIV (1.5%)

0.2
15

2
14.5

$6,310,000
$19,910,000

$6,090,000
$17,540,000

$220,000
$2,370,000

$112,734
$156,014

Inmates who accept HIV counseling
and testing (CT) (50-60%)

30
90

2.4
3.7

$7,500,000
$7,500,000

$7,200,000
$6,980,000

$300,000
$520,000

$113,502
$119,570

Risk of HIV transmission from HIVinfected inmates to their partners, with
no CT (7%)

5
30

2.6
7.1

$7,080,000
$12,830,000

$6,740,000
$11,200,000

$340,000
$1,630,000

$116,536
$116,536

Effectiveness of counseling in reducing
risk behavior for HIV-infected persons
(25%)

10
50

2.3
4.3

$7,500,000
$7,500,000

$7,230,000
$ 6,880,000

$270,000
$620,000

$116,536
$116,536

Effectiveness of counseling in reducing
risk behaviors for HIV-uninfected
persons (10%)

5
20

2.3
4.8

$7,500,000
$7,500,000

$7,220,000
$6,790,000

$280,000
$710,000

$116,536
$116,536

100,000
250,000

3
3

$4,290,000
$10,720,000

$4,100,000
$10,080,000

$190,000
$640,000

$116,536
$116,536

3

$7,500,000

$7,090,000

$410,000

$116,536

Lifetime treatment cost of HIV
(175,000)
Baseline

130
The one-way sensitivity analysis (changing the
value of one parameter at a time) for the model
parameters shows that offering counseling and
testing to prison inmates will remain beneficial to
society under a wide range of parameter values,
with savings ranging from $200,000 to more than
$2 million (see table 2). On the other hand, total
costs to the prison system are affected by HIV
prevalence and acceptance rate of counseling
among prisoners.
A threshold analysis was also conducted to
estimate specific parameter values at which prison
counseling and testing would not be a cost saving
to society. This would occur if: (1) lifetime
treatment cost of HIV infection decreased to less
than $40,000; (2) risk of HIV transmission from
infected to uninfected persons decreased to 1
percent (from 7 percent); or (3) risk of infection
among the uninfected decreased to 0.1 percent
(from 0.35 percent).

Discussion
The study shows that offering HIV counseling
and testing services in prisons prevents future
cases of HIV and saves society money. Given the
high societal costs of HIV infection, the average
provider cost of $39,000 to prevent a future case
of HIV seems reasonable. The cost to the prison
system decreases with an increase in HIV
prevalence, increased risk of transmission, or
increased effectiveness of counseling. Most State
prisons in the Northeast and a few in the South
report HIV prevalence of at least 3 percent. The
State prison systems with HIV prevalence rates in
excess of 3 percent house almost 31 percent of all
State prisoners in the United States.23 These State
prison systems are ideal for HIV counseling and
testing programs.
The model also shows that when HIV prevalence
is less than 5 percent, most of the benefits in
terms of future cases prevented come from
prevention counseling of uninfected inmates
who do not acquire infection rather than from
preventing secondary transmission from infected
inmates. Therefore, HIV counseling and testing
programs are beneficial not only because they
inform infected inmates of their status, prevent

transmission to uninfected partners, and help
infected inmates get care (this study does not
address the benefits of providing care to HIVinfected inmates), but also because they inform
uninfected inmates of their status and protect
them from becoming infected.
It may be difficult for a prison system to accept
the cost of a prevention intervention such as HIV
counseling and testing where the benefits are
averted future cases. Funding prevention programs that result in decreased future costs to
society may seem too altruistic to some, but given
the high recidivism rates among HIV-infected
inmates, the benefits of prevention will more than
likely accrue to prison systems.
Models that use epidemiological data to quantify
benefits of prevention are highly dependent on
accurate and representative data. The lack of
relevant cost and epidemiological data among
prison populations is a concern for this study. The
decision model has used HIV transmission and
infection rates between heterosexual couples and
based its estimates on effectiveness of counseling
on studies of heterosexual populations. Given that
many prison inmates are IDUs and are suspected
of having higher than normal HIV transmission
rates due to dual modes of transmission (needles
and sex), cost savings would increase with higher
transmission rates.
Studies on the effectiveness of counseling on
reducing risk behavior among IDUs are limited
and contradictory, so counseling has been
assumed to be half as effective in this group as in
the heterosexual groups studied. As relevant
information on transmission rates becomes
available, required changes can be made to this
model to increase the accuracy of the estimates.
Because of the lack of estimates for prison
populations, cost estimates for HIV treatment
have been based on data from clinics. The lifetime treatment cost of $175,000 per case of HIV
infection is almost certainly a conservative
estimate, in part because of the increase in life
expectancy provided by new therapies. A higher
lifetime treatment cost would increase the societal
savings per case prevented. Also, the morbidity
and mortality costs associated with HIV infection

131
were not included, resulting in an underestimate
of societal savings obtainable through prison HIV
counseling and testing.
One limitation of this and all other models is that
results should be considered within the context of
the probabilities and information used in the
analysis. A second important limitation is the lack
of information on effectiveness of counseling and
cost estimates for prison populations, which will
probably lead to an underestimate of benefits. The
third limitation is the underestimate of benefits
from HIV prevention due to the use of a 1- to 2year risk period of HIV infection instead of a
lifetime risk, and the decision not to account for
second- and third-generation transmission of HIV.
This leads to underestimating the societal cost
savings. Finally, the model is a prevention model
that does not estimate the benefits and costs
associated with treating HIV-infected persons
who are identified by prison counseling and
testing.
In summary, the analysis shows that quality HIV
counseling and testing of prison inmates, under
the given model assumptions, is a cost-saving
prevention program that would prevent many
future cases of HIV and save society money. Even
from the prison perspective, the average cost of
this prevention intervention seems reasonable.

Notes
1. Glaser, J.B., and R.B. Greifinger, “Correctional
Health Care: A Public Health Opportunity,” Annals of
Internal Medicine 118(2)(1993): 139–145.
2. Vlahov, D., “HIV–1 Infection in the Correctional
Setting,” National Institute on Drug Abuse Research
Monographs 118(1992): 51–61; Altice, F.L., F.
Mostashari, P.A. Selwyn, P. Checko, R. Singh, S.
Tanguay, and E.P. Blanchette, “Predictors of HIV
Infection Among Newly Sentenced Males,” Journal of
Acquired Immune Deficiency Syndrome and Human
Retrovirology 18(5)(1998): 444–453.
3. Glaser, J.B., and R.B. Greifinger, “Correctional
Health Care: A Public Health Opportunity” (see note
1); Vlahov, D., “HIV–1 Infection in the Correctional
Setting” (see note 2).

4. Kamb, M.L., M. Fishbein, J.M. Douglas, F. Rhodes,
J. Rogers, G. Bolan, J. Zenilman, T. Hoxworth, C.K.
Malotte, M. Iatesta, C. Kent, A. Lentz, S. Graziano,
R.H. Byers, and T.A. Peterman, “Efficacy of RiskReduction Counseling to Prevent Human Immunodeficiency Virus and Sexually Transmitted Diseases:
A Randomized Controlled Trial. Project RESPECT
Study Group,” Journal of the American Medical
Association 280(13) (1998): 1161–1167; Varghese, B.,
T.A. Peterman, and D.R. Holtgrave, “CostEffectiveness of Counseling and Testing and Partner
Notification: A Decision Analysis,” AIDS
13(13)(1999): 1745–1751.
5. Varghese, B., T.A. Peterman, and D.R. Holtgrave,
“Cost-Effectiveness of Counseling and Testing and
Partner Notification: A Decision Analysis” (see note
4).
6. Farnham, P.G., R.D. Gorsky, D.R. Holtgrave,
W.K. Jones, and M.E. Guinan, “Counseling and
Testing for HIV Prevention: Costs, Effects, and
Cost-Effectiveness of More Rapid Screening Tests,”
Public Health Reports 111(1): 44–53; Holtgrave,
D.R., and S.D. Pinkerton, “Updates of Cost of Illness
and Quality of Life Estimates for Use in Economic
Evaluations of HIV Prevention Programs,” Journal of
Acquired Immune Deficiency Syndrome and Human
Retrovirology 16(1)(1997): 54–62; Varghese, B., and
B.M. Branson, “Cost and Cost-Effectiveness of Oral
Fluid HIV Testing Compared to Serum Testing”
(abstract), in XIII International AIDS Conference
Abstracts, Durban, South Africa, July 9–14, 2000,
Abstract ThpeC5433.
7. Hammett, T.M., P. Harmon, and W. Rhodes, “The
Burden of Infectious Disease Among Inmates and
Releasees From Correctional Facilities,” paper prepared for the National Commission on Correctional
Health Care, Chicago, Illinois, May 2000. (Copy in
this volume.)
8. Ibid.
9. Rutherford, G.W., J.M. Woo, D.P. Neal, K.J. Rauch,
C. Geoghegan, K.C. McKinney, J. McGee, and G.F.
Lemp, “Partner Notification and the Control of Human
Immunodeficiency Virus Infection: Two Years of
Experience in San Francisco,” Sexually Transmitted
Diseases 18(2)(1991): 107–110; Hoffman, R.E., N.E.
Spencer, and L.A. Miller, “Comparison of Partner
Notification at Anonymous and Confidential HIV Test
Sites in Colorado,” Journal of Acquired Immune
Deficiency Syndrome and Human Retrovirology

132
8(4)(1997): 54–62; Toomey, K.E., T.A. Peterman,
L.W. Dicker, A.A. Zaidi, J.E. Wroten, and J. Carolina,
“HIV Partner Notification: Cost and Effectiveness
Data From an Attempted Randomized Controlled
Trial,” Sexually Transmitted Diseases 25(6)(1998):
310–316.

Conference on AIDS, June 23, 1990, San Francisco,
CA; Farley, T., M. Carter, and J. Hadler, “HIV
Counseling and Testing in Methadone Programs:
Effects on Treatment Compliance,” paper presented at
the Sixth International Conference on AIDS, June 23,
1990, San Francisco, CA.

10. Hammett, T.M., M. Gross, and J. Epstein, 1992
Update: HIV/AIDS in Correctional Facilities, Issues
and Practices, Washington, DC: U.S. Department of
Justice, National Institute of Justice, 1994, NCJ
144398.

18. Kamb, M.L., M. Fishbein, J.M. Douglas, F.
Rhodes, J. Rogers, G. Bolan, J. Zenilman, T. Hoxworth, C.K. Malotte, M. Iatesta, C. Kent, A. Lentz, S.
Graziano, R.H. Byers, and T.A. Peterman, “Efficacy of
Risk-Reduction Counseling to Prevent Human
Immunodeficiency Virus and Sexually Transmitted
Diseases: A Randomized Controlled Trial. Project
RESPECT Study Group” (see note 4).

11. Glaser, J.B., and R.B. Greifinger, “Correctional
Health Care: A Public Health Opportunity” (see note
1); Vlahov, D., “HIV–1 Infection in the Correctional
Setting” (see note 2).
12. Mastro, T., and I. De Vincenzi, “Probabilities of
Sexual HIV-1 Transmission,” AIDS 10(1996):
S75–S82.
13. De Vincenzi, I., “A Longitudinal Study of Human
Immunodeficiency Virus Transmission by Heterosexual Partners. European Study Group on
Heterosexual Transmission of HIV,” New England
Journal of Medicine 331(6)(1994): 341–346.
14. McKay, N.L., and K.M. Phillips, “An Economic
Evaluation of Mandatory Premarital Testing for HIV,”
Inquiry 28(3)(1991): 236–248.
15. Holtgrave, D.R., R.O. Valdiserri, A.R. Gerber, and
A.R. Hinman, “Human Immunodeficiency Virus
Counseling, Testing, Referral, and Partner Notification
Services: A Cost-Benefit Analysis,” Archives of
Internal Medicine 153(10)(1993): 1225–1230.
16. Power, R., R. Hartnoll, and E. Daviaud, “Drug
Injecting, AIDS, and At-Risk Behavior: Potential for
Change and Intervention Strategies,” British Journal of
Addiction 83(6)(1988): 649–654; Van den Hoek,
J.A.R., H.J.A. van Haastrecht, and R.A. Couhtino,
“Heterosexual Behavior of Intravenous Drug Users in
Amsterdam: Implications for the AIDS Epidemic,”
AIDS 4(5)(1990): 449–453; Casadonte, P.P., D.C.
DesJarlais, S.R. Friedman, and J.P. Rotrosen,
“Psychological and Behavioral Impact Among
Intravenous Drug Users of Learning HIV Test
Results,” International Journal of Addiction
25(4)(1990): 409–426.
17. Roggenburg, L., B. Sibthorpe, H. Tesselaar, et al.,
“Characteristics of IVDUs Who Have Been HIV
Tested,” paper presented at the Sixth International

19. De Vincenzi, I., “A Longitudinal Study of Human
Immunodeficiency Virus Transmission by Heterosexual Partners. European Study Group on Heterosexual Transmission of HIV” (see note 13).
20. Kamb, M.L., M. Fishbein, J.M. Douglas, F.
Rhodes, J. Rogers, G. Bolan, J. Zenilman, T. Hoxworth, C.K. Malotte, M. Iatesta, C. Kent, A. Lentz, S.
Graziano, R.H. Byers, and T.A. Peterman, “Efficacy of
Risk-Reduction Counseling to Prevent Human
Immunodeficiency Virus and Sexually Transmitted
Diseases: A Randomized Controlled Trial. Project
RESPECT Study Group” (see note 4); McKay, N.L.,
and K.M. Phillips, “An Economic Evaluation of
Mandatory Premarital Testing for HIV” (see note 14);
Holtgrave, D.R., R.O. Valdiserri, A.R. Gerber, and
A.R. Hinman, “Human Immunodeficiency Virus
Counseling, Testing, Referral, and Partner Notification
Services: A Cost-Benefit Analysis” (see note 15);
Power, R., R. Hartnoll, and E. Daviaud, “Drug
Injecting, AIDS, and At-Risk Behavior: Potential for
Change and Intervention Strategies” (see note 16);
Casadonte, P.P., D.C. DesJarlais, S.R. Friedman, and
J.P. Rotrosen, “Psychological and Behavioral Impact
Among Intravenous Drug Users of Learning HIV Test
Results” (see note 16); Van den Hoek, J.A.R., H.J.A.
van Haastrecht, and R.A. Couhtino, “Heterosexual
Behavior of Intravenous Drug Users in Amsterdam:
Implications for the AIDS Epidemic” (see note 16);
Roggenburg, L., B. Sibthorpe, H. Tesselaar, et al.,
“Characteristics of IVDUs Who Have Been HIV
Tested” (see note 17); Farley, T., M. Carter, and J.
Hadler, “HIV Counseling and Testing in Methadone
Programs: Effects on Treatment Compliance” (see
note 17).

133
21. Varghese, B., T.A. Peterman, and D.R. Holtgrave,
“Cost-Effectiveness of Counseling and Testing and
Partner Notification: A Decision Analysis” (see note
4); Farnham, P.G., R.D. Gorsky, D.R. Holtgrave, W.K.
Jones, and M.E. Guinan, “Counseling and Testing for
HIV Prevention: Costs, Effects, and CostEffectiveness of More Rapid Screening Tests” (see
note 6); Varghese, B., and B.M. Branson, “Cost and
Cost-Effectiveness of Oral Fluid HIV Testing
Compared to Serum Testing” (see note 6).
22. Holtgrave, D.R., and S.D. Pinkerton, “Updates of
Cost of Illness and Quality of Life Estimates for Use in

Economic Evaluations of HIV Prevention Programs”
(see note 6); Hellinger, F.J., “The Lifetime Cost of
Treating a Person With HIV” Journal of the American
Medical Association 270(4)(1993): 474–478; Gable,
C.B., J.C. Tierce, D. Simison, D. Ward, and K. Motte,
“Costs of HIV/AIDS at CD4 Counts Disease Stages
Based on Treatment Protocols” Journal of Acquired
Immune Deficiency Syndrome and Human Retrovirology 12(4)(1996): 413–420.
23. Hammett, T.M., P. Harmon, and W. Rhodes, “The
Burden of Infectious Disease Among Inmates and
Releasees From Correctional Facilities” (see note 7).

135

What Is the Value of Immunizing Prison
Inmates Against Hepatitis B?
Robert Lyerla, Ph.D.

Hepatitis B and Correctional
Environments
• Inmates at increased risk for Hepatitis B
virus (HBV) infection
• Risk is associated with high-risk drug and
sex practices before incarceration
• Incidence of new infections (1–1.5 percent)
is 10 times higher than in the general U.S.
population

136

Epidemiology of Hepatitis B in
Correctional Settings
• Risk for HBV transmission during incarceration is low
– Related to behaviors?
•
•
•
•

Injection drug use?
Men having sex with men?
Tattooing?
Fights?

• Risk is as high or higher than for groups recommended for
vaccine for occupational reasons
– Health care workers (1–6 percent/year)
– Correctional officers (1–2 percent/year)
– Incarcerated individuals (1–1.5 percent/year)

Strategy to Eliminate HBV
Transmission in United States
• Comprehensive plan proposed in 1991 by the
Advisory Committee on Immunization Practices
(ACIP)
– 4 components, including high-risk adolescents and
adults
– Surveys find low coverage in high-risk groups

• Identify settings where high-risk individuals can
be vaccinated
– Criminal justice system?

137

Missed Opportunities for
Hepatitis B Vaccination
• Sentinel counties
– Of acute cases, 20 percent had been incarcerated
– 18 percent had household or sexual contact with
case

• National Survey of Injection Drug Users
(IDUs), 45 cities
– Between 1987 and 1989
– 17,000 IDUs identified
– 81 percent report jail or prison

Issues Related to Hepatitis B
Vaccine Programs
• Vaccination schedules
– Altered schedules
– Value of 1, 2, or 3 doses

• Prevaccination testing for susceptibility
– Greater than 30 percent prevalence
– Consequences of test results

• Postvaccination testing serologic response
– Not recommended

• Prevention of perinatal HBV transmission from
female inmates to their infants

138

Hepatitis B Vaccine Seroconversion Rates
(>10mIU/mL)
After 1 dose
20–50 percent
After 2 doses
85 percent
After 3 doses
Greater than 95 percent

Recommendations—I
• Implement hepatitis B vaccination programs in all
correctional facilities
• Make efforts to achieve compliance with the 3dose vaccine series
• Consider prevaccination screening in populations
with an expected prevalence greater than 30
percent
• Integrate with other STD/HIV prevention
programs

139

Recommendations—II
• Need programs to prevent perinatal transmission
• Need close cooperation between public health and
criminal justice agencies to develop and
implement hepatitis B vaccination programs
– Staff training
– Drug treatment centers
– Followup of released prisoners
• Treatment or vaccine series completion

Future Needs—Collaborations
• Algorithm for cost analysis
– Cost associations

• Healthy People 2010—Section 2213.6B
– Hepatitis B vaccine among inmates
• No baseline data
• Does a mechanism exist (periodic survey)?

141

Cost-Effectiveness Analysis of Annual
Screening and Intensive Treatment for
Hypertension and Diabetes Mellitus
Among Prisoners in the United States

Donna M. Tomlinson, M.D., M.Sc., Fellow, Division of Cardiology, Department of Medicine, Beth Israel
Medical Center; and Clyde B. Schechter, M.A., M.D., Associate Professor, Department of Community
and Preventive Medicine, Mount Sinai School of Medicine

Hypertension and diabetes mellitus are the most
common chronic illnesses among adults. They
occur in the prison population and are responsible
for substantial morbidity, particularly after
release. The prison setting offers an opportunity
to initiate screening for and treatment of these
conditions in an environment that is conducive to
high levels of patient compliance. At present, in
most correctional facilities, these diseases are
diagnosed opportunistically and may not receive
state-of-the-art treatment.
In this paper, a Monte Carlo simulation is constructed that projects the economic and health
consequences over 20 years of initiating annual
screening and intensive treatment for these
illnesses. The model derives its underlying
demographics from information supplied by the
National Commission on Correctional Health
Care. The prevalence of hypertension and
diabetes are modeled by applying to this population the age-, sex-, and race-specific rates
observed in the National Health and Nutrition
Examination Survey III.1 The occurrence of
complications is then predicted using results of
the Diabetes Control and Complications Trial, the
Wisconsin Epidemiologic Study of Diabetic
Retinopathy, and the Framingham Heart study.
Implementing the proposed program would, over
the next 20 years, result in a gain of 386,108 lifeyears in the cohort of approximately 1.6 million
persons currently incarcerated. The immediate
and subsequent costs for screening and treating

this population are $4,214,720,066, or $131.71
per prisoner per year. These costs are partially
offset by concurrent reductions in expenditures
for treating the complications of these diseases.
When the conventional discount rate of 3 percent
per annum is applied, the cost-effectiveness ratio
for implementation is between $11,300 and
$27,100 depending upon what levels of compliance and immediate costs of screening are
assumed. Even under the worst-case scenario,
this program is a more economical allocation of
health care resources than many widely accepted
preventive health practices.
The authors recommend that prison systems adopt
annual screening for hypertension and diabetes
and intensive treatment of both diseases to obtain
tight control of both.

Introduction
Hypertension and diabetes mellitus are the two
most common chronic illnesses among adults.
Both are major risk factors for developing
coronary heart disease and renal failure.
Hypertension is also the major risk factor for
stroke, and one of the leading causes of peripheral
vascular disease. Diabetes is the most common
cause of blindness in adults and leads to painful
neuropathy and amputation of limbs. It has been
known for many years that treatment of hypertension reduces the incidence of complications.
More recently, it has been demonstrated that tight

142
control of glucose in both Type I2 and Type II3
diabetes can also reduce the incidence of
complications.
Prisoners are younger than the U.S. population
as a whole and correspondingly have a lower
prevalence of hypertension and diabetes. Screening for these diseases, even in this relatively lowprevalence population, might nevertheless be
productive for several reasons:
•

•

•

•

The prison population already has health care
facilities and physicians at its disposal and
makes frequent use of them; therefore, no
costs to create capacity would be incurred.
Prisoners do not lose income or free leisure
activity while using the health care system;
therefore, the usual indirect costs that
encumber screening programs do not exist.
Followup and adherence to dietary and
medical regimens can be enforced in the
prison environment to a greater extent
than outside. (It might even be hoped that
establishing a behavioral pattern of compliance with treatment in prison might lead to
continued good compliance following release
as well.)
The direct screening costs for both diseases
are modest, and the confirmatory evaluation
of abnormal results is both inexpensive and
safe.

The following analysis of the costs, consequences,
and cost-effectiveness of screening and aggressive
treatment for hypertension and diabetes mellitus
in the imprisoned population of the United States
has been carried out at the request of the National
Commission on Correctional Health Care
(NCCHC).

Methods
The major complications that are predicted to
occur as a result of hypertension and diabetes
mellitus among the current incarcerated
population in the United States were identified

through a Monte Carlo simulation model
programmed using @Risk.4 The costs and
consequences of identifying and treating hypertension and diabetes among these prisoners were
predicted and the cost-effectiveness ratio
calculated. The cost-effectiveness ratio was
defined as the increase in costs resulting from
instituting screening and treatment divided by the
increase in quality-adjusted life-years associated
with that.
The simulation model projected the occurrence of
the following outcomes:
•

Coronary heart disease (CHD) including
angina pectoris myocardial infarction.

•

Congestive heart failure.

•

Stroke.

•

Hypertensive renal failure.

•

Diabetic nephropathy progressing to renal
failure.

•

Diabetic neuropathy progressing to lower
extremity amputation.

•

Diabetic retinopathy progressing to blindness.

•

Death.

The overall logic of the simulation was as follows:
C

Assign sex, race, and initial age of the
simulated subject according to the
distributions known for the imprisoned
population.

C

Using age-, sex,- and race-specific distributions
derived from the NHANES–III data, assign
the simulated patient a smoking status,
diabetic status, systolic blood pressure (SBP),
total cholesterol, and high-density lipoprotein
(HDL) cholesterol level. If the simulated
subject is a diabetic, also assign a duration
of diabetes and initial stage for diabetic
retinopathy, neuropathy, and nephropathy.

143
Simulated followup begins at current age and
continues for 20 years (or until the simulated
patient “dies,” whichever comes first). Each
patient’s current vital status; incarceration status;
current SBP and lipid levels; and, if diabetic,
current stage of diabetic retinopathy, neuropathy,
and nephropathy are randomly determined on an
annual basis. The probability of developing each
of the study endpoints in this year is calculated,
and then it is randomly determined which, if any,
of such events occur.
Because CHD incidence rates are gender
dependent and incidence rates of complications of
diabetes differ by race, separate simulations were
run for each combination of three racial or ethnic
groups (white, Hispanic, and black) and both
sexes. Twenty thousand subjects were simulated
for each of these race-sex strata. The strata were
then combined and the results adjusted to the
racial/ethnic and sex distribution of the
imprisoned population.
Population costs were calculated by applying
average estimated unit costs to tallies of outcome
events and person-years of morbid states and by
assessing appropriate costs of screening, diagnostic followup, and treatment in the screen-andtreat strategy.

The Population
Demographics of the incarcerated population
Table 1 shows the numbers of prisoners of
various ages, sexes, and races.5

Age-, sex-, and race-specific distributions of
chronic disease
Appropriate sample weights were applied to the
NHANES–III data (National Center for Health
Statistics, 1997) to estimate smoking prevalence,
SBP, total cholesterol, HDL, and prevalent cases
of diabetes mellitus; analyses were carried out
using Stata version 6.0.6
Smoking status. The case definition of smoking
was defined as an affirmative response to the
NHANES–III question about smoking within the
past year because the risks of coronary heart
disease associated with smoking are known to
decline to near baseline rates after 1 year of
abstinence. It was assumed that smoking status
would not change over time. Table 2 shows the
probabilities of being a smoker for a given age,
sex, and race combination. These probabilities
were used to predict smoking prevalence for each
simulated individual.

Table 1. Demographics of the Incarcerated Population
Age
#19

Black Male

Black Female

White Male

White Female Hispanic Male

Hispanic Female

46,489

1,392

24,146

1,366

16,824

636

20–24

124,795

8,143

90,807

6,817

57,170

3,768

25–29

150,220

13,989

107,131

10,049

66,205

4,448

30–34

136,607

14,841

111,898

10,360

52,009

4,381

35–39

95,126

10,249

81,380

7,466

36,447

2,840

40–44

55,613

4,517

57,290

4,582

21,629

1,881

45–49

23,349

1,811

32,944

1,863

12,569

1,059

50–54

9,166

667

20,348

1,330

5,615

372

55–59

5,297

339

12,428

487

3,602

179

60–64

3,480

96

7,498

288

1,743

63

65+

3,564

155

5,297

235

548

10

653,706

56,199

550,167

44,843

274,361

19,637

Total

144
Table 2. Probability of Being a Smoker
Male

Female

Age Group

White

Black

Other

White

Black

Other

#19

0.230

0.154

0.103

0.270

0.043

0.006

20–24

0.410

0.268

0.306

0.333

0.212

0.095

25–29

0.378

0.324

0.288

0.390

0.298

0.004

30–34

0.363

0.403

0.431

0.334

0.370

0.005

35–39

0.369

0.517

0.374

0.274

0.313

0.258

40–44

0.319

0.487

0.395

0.236

0.318

0.116

45–49

0.354

0.525

0.386

0.280

0.352

0.088

50–54

0.325

0.444

0.191

0.222

0.266

0.050

55–59

0.273

0.464

0.548

0.237

0.356

0.193

60–64

0.207

0.375

0.090

0.246

0.235

0.351

$65

0.147

0.247

0.359

0.112

0.112

0.118

Distribution of systolic blood pressure, initially
and over time. Systolic blood pressure in
homogeneous population groups follows an
approximately log-normal distribution. SBP is
known to be higher in African-Americans and in
diabetics. The NHANES–III data were used to
estimate the mean and standard deviation of the
natural logarithm of SBP in each stratum of
individuals defined by age group, sex, racial or
ethnic group, and diabetes status. Each subject
was assigned an initial SBP by sampling from
a log-normal distribution with the corresponding parameters. The tails of the log-normal
distribution are heavier than those of actual SBP
distributions, so the corresponding values were
truncated to limit the simulated SBPs to realistic
values.
Blood pressure rises with age. This was modeled
by adding an annual increment to the simulated
blood pressure which equals the coefficient of age
in the race-, sex-, and diabetes-specific regression
of SBP with age in the NHANES–III data. Large
random fluctuation caused by various factors
occurs over time as well. The test-retest correlation of diastolic blood pressure measurements has been estimated to be 0.437 and that
for systolic blood pressure is even lower.8
More consistent blood pressure measurements
require measurement procedures that have not
been adopted in general clinical practice and are

unlikely to be used in the correctional health care
context. In each year of the simulation, a normally
distributed, mean-zero, random increment to
blood pressure was added to the previous year’s
blood pressure. The variance of the distribution
was chosen to create a 1-year intercorrelation of
0.50 among SBP measurements. The principal
reason for simulating SBP measurements (rather
than hypertension) is to apply the American Heart
Association (AHA) prediction formula9 for CHD.
Because the measurement procedures used in the
Framingham study (from which the AHA formula
is derived) are somewhat more rigorous than
standard clinical practice, this enhanced intercorrelation seems reasonable.
To illustrate, for white males, the logarithm of
initial SBP was sampled from a normal
distribution with mean 0.00327 × age + 4.673
(+0.0268 if diabetic) and standard deviation
0.113. The resulting log SBP was trimmed to a
minimum of 4.23 and a maximum of 5.5
(restricting SBP to the range 70–245). The
exponential of this value was used as the initial
SBP. For subsequent years, the logarithm of SBP
was taken to be the previous year’s log SBP +
0.00327 (to reflect aging) + a mean-zero normally
distributed random fluctuation with standard
deviation 0.08. The same trimming limits were
applied and the result exponentiated to determine
the next year’s SBP. Similar procedures with

145
race- and sex-specific coefficients were used for
women and blacks. SBPs for Hispanics were
simulated using the equations for whites because
analysis of the NHANES–III data found no
substantial differences between these groups.
Table 3 shows the regression equations used to
predict the log of SBP for various racial and
ethnic groups and both sexes.
Distribution of total cholesterol and HDL
cholesterol, initially and over time. Total
cholesterol and HDL also follow approximately
log-normal distributions in homogeneous
population groups. It is known that total
cholesterol tends to be elevated and HDL
cholesterol depressed among persons with high
blood pressure compared with those with normal
blood pressure, and among diabetics compared
with nondiabetics. In addition, HDL cholesterol
tends to be lower among those with higher total
cholesterol. These intercorrelations could be
captured by estimating the mean logarithm of
total cholesterol from a race- and sex-specific
regression equation involving age and systolic
blood pressure and then estimating the mean
logarithm of HDL cholesterol from age and total

cholesterol. The process was similar to that
outlined for SBP.
For white males, the logarithm of initial total
cholesterol was sampled from a normal
distribution with mean 4.03 + 0.2264 × SBP +
0.0038 × age, with standard deviation 0.1944,
trimmed to limits of 4.3 and 6.55. For subsequent
years, the logarithm of total cholesterol was
incremented by 0.0038 + a zero-mean normally
distributed error term with a standard deviation of
0.137, again trimmed to the same limits. The
equations for females and nonwhites had different
constant terms, but were otherwise the same. The
same standard deviation was used for both sexes
and racial groups. Table 4 shows the regression
equations used to predict the logarithm of total
cholesterol in race- and sex-specific groups.
For HDL cholesterol, the logarithm was sampled
from a normal distribution with mean 3.769
!0.00064 × age + 0.00012 × total cholesterol and
a standard deviation of 0.297 for white males. The
trimming limits were 2.08 and 5.28. For females
and nonwhites, separate equations and standard
deviations were estimated, as shown in table 5.

Table 3. NHANES–III Regression Equations Used to Predict the Log of Systolic Blood Pressure
LogSBP Black Female = age × 0.0055882 + dm × 0.040263 + 4.557157

SD = 0.113

LogSBP Black Male = age × 0.0037727 + dm × 0.0289417 + 4.667224

SD = 0.112

LogSBP White Female = age × 0.0054558 + dm × 0.0552535 + 4.524341

SD = 0.113

LogSBP White Male = age × 0.0032679 + dm × 0.0267574 + 4.672714

SD = 0.113

Table 4. NHANES–III Regression Equations Used to Predict the Log of Total Cholesterol
Black Female = 0.2263468 × LogSBP + 0.0037968 × age + 4.0330064
Black Male = 0.2263468 × LogSBP + 0.0037968 × age + 4.0077188
White Female = 0.2263468 × LogSBP + 0.0037968 × age + 4.0524686
White Male = 0.2263468 × LogSBP + 0.0037968 × age + 4.027181

Table 5. NHANES–III Regression Equations Used to Predict the Log of HDL Cholesterol
Black Female = !0.0011172 × age + 0.0013044 × cholesterol + 3.790949

SD=0.2984

Black Male = !0.0003883 × age + 0.0004286 × cholesterol + 3.836287

SD=0.2963

White Female = !0.0000327 × age + 0.0003573 × cholesterol + 3.896419

SD=0.2963

White Male = !0.0005691 × age + 0.0001175 × cholesterol + 3.768782

SD=0.2967

146
As with SBP, for both total and HDL cholesterol
values, Hispanics were treated as whites based on
lack of significant differences. Separate parameter
estimates for females and for blacks were used.

Diabetes: Prevalence, Duration, and
Incidence
The case definition of diabetes mellitus used was:
a history of using oral hypoglycemic agents or
insulin preparations or a fasting blood glucose
exceeding 125 mg/dL followed by a 2-hour
specimen exceeding 140 mg/dL.

Diabetes prevalence
Table 6 shows the assumed prevalence of diabetes
by age group, sex, and race. With the criterion for
diabetes used, the number of cases of diabetes
among Hispanics in the NHANES–III data was
too small to provide stable estimates of
prevalence in several age-sex subgroups. For this
reason, in the model, the same prevalence rates
were used for whites and Hispanics.

Diabetes duration
The rates of progression of complications of
diabetes depend upon the duration of the disease.
Time since diagnosis of diabetes was estimated
using a model that was fitted to data from the
NHANES–III survey. Within the NHANES–III

survey, diabetes duration was defined as the
difference between the date of examination and
the date when the subject was first told of a
diagnosis of diabetes. Graphical and descriptive
exploratory analysis of this variable suggested
that within narrow age groups, the distribution of
duration followed an exponential distribution.
The rate parameter for the distribution appeared
to increase linearly with age. The duration of
diabetes was treated as a survival time variable
and fit an exponential regression model with age
as a continuous predictor variable. Each simulated
diabetic subject was assigned an initial duration
of diabetes by sampling from an exponential
distribution (truncated at current age) with the
parameter calculated from the regression model.
Duration ~ Exponential (α + β × age)
Maximum likelihood estimates of a = 1.1 and b =
0.2 were used. For each prevalent diabetic
prisoner, a duration of diabetes was assigned by
sampling from an exponential distribution with
mean = 1.1 + 0.2 × age.

Diabetes incidence
Age-, sex-, and race-specific incidence rates for
diabetes mellitus are difficult to find. Because
diabetes is not screened for routinely, is not
reportable, and is initially asymptomatic, most

Table 6. Prevalence of Diabetes Mellitus
Age Group

Male White

Male Nonwhite

Female White

Female Nonwhite

#19

0.001

0.009

0.011

0.009

20–24

0.004

0.006

0.004

0.006

25–29

0.004

0.008

0.001

0.017

30–34

0.003

0.012

0.009

0.017

35–39

0.027

0.014

0.018

0.017

40–44

0.038

0.036

0.047

0.062

45–49

0.051

0.107

0.032

0.084

50–54

0.086

0.120

0.062

0.116

55–59

0.118

0.244

0.081

0.157

60–64

0.136

0.226

0.128

0.133

$65

0.127

0.195

0.103

0.164

147
newly diagnosed cases are not truly incident. The
age-specific estimates of incidence shown in
table 7 were derived from surveillance reports
gathered by the Centers for Disease Control and
Prevention (CDC).10

proteinuria to end-stage renal disease was then
simulated using duration-, sex-, and race-specific
annual rates,11 as shown in table 8.

Diabetes: Prevalence, Incidence, and
Progression of Complications

In addition to diabetic nephropathy, hypertensives
are at risk of developing end-stage renal disease.
Suitable data could not be identified on the
incidence of renal failure by blood pressure, age,
and race. Instead, total numbers of hypertensives
that are being treated for end-stage renal disease
under Medicare, broken down by age group, were
obtained from the U.S. Renal Data System.12
These numbers were divided by estimates from

Stages of diabetic nephropathy—initial
prevalence and progression
Following Eastman et al., an initial 10.5 percent
prevalence of microalbuminuria among prevalent
diabetics was assumed. Progression through frank

Remarks about hypertension and renal disease

Table 7. Incidence of Diabetes Mellitus
Age Group

Cases per 1,000 per Year

0–44

1.56

45–64

6.45

65+

4.18

Table 8. Rates of Progression of Complications of Diabetes
Race

Duration of
Diabetes

From Normal
to Microalbuminuria

Microalbuminuria
Frank Proteinuria

Frank Proteinuria
ESRD

White

0–4

0.0267

0.1572

0.0042

Black

Hispanic

5–9

0.0267

0.1572

0.0042

9–11

0.0267

0.1572

0.0042

12–13

0.0267

0.1572

0.0385

14–20

0.0267

0.1572

0.0385

21+

0.0267

0.1572

0.0740

0–4

0.1215

0.1572

0.0042

5–9

0.1215

0.1572

0.0042

9–11

0.1215

0.1572

0.0042

12–13

0.1215

0.1572

0.0385

14–20

0.1215

0.1572

0.0385

21+

0.1215

0.1572

0.0740

0–4

0.1719

0.1572

0.0042

5–9

0.1719

0.1572

0.0042

9–11

0.1719

0.1572

0.0042

12–13

0.1719

0.1572

0.0385

14–20

0.1719

0.1572

0.0385

21+

0.1719

0.1572

0.0740

148
NHANES–III of the total numbers of hypertensives (defined as systolic blood pressure $140
mmHg) in these age groups. The resulting
prevalence rates were taken to represent lifetime
incidence. Annual incidence rates for hypertensives were then estimated by attributing the
risk over the life expectancy of people in each age
group. Although this method of estimating
incidence is far from ideal, given the relatively
small number of hypertensives and the low
incidence of end-stage renal disease among them
in the target population, even major errors in
these estimates will exert little influence on the
overall results of the analysis.

Retinopathy.14 For instance, it was assumed that
20 percent of prevalent diabetics already have
nonproliferative diabetic retinopathy.
Diabetic retinopathy was modeled as having five
stages: normal (R1), nonproliferative (R2), proliferative (R3), macular edema (R4), and visual
acuity < 20/100 in better eye (R5). Progression
through these stages can be direct, or stages R3 or
R4 can be skipped with direct advancement from
R2 to R4 or from R3 to R5. Table 10 summarizes
the annual transition probabilities among these
stages taken from Javitt et al.15

American Heart Association Model of
CHD Risk

Stages of diabetic neuropathy—initial
prevalence and progression
It was assumed that 3.5 percent of prevalent
diabetics have symptomatic neuropathy.
Incidence of symptomatic neuropathy and
progression to amputation were simulated using
duration-, sex-, and race-specific rates from
Eastman et al.,13 as shown in table 9.

Stages of diabetic retinopathy—initial
prevalence and progression
The model of diabetic retinopathy was taken from
the Wisconsin Epidemiologic Study of Diabetic

The Framingham study is the best known and
longest running cohort study of the epidemiology of cardiovascular disease. Over the years,
numerous formulas for predicting risk of coronary
heart disease (or specific manifestations thereof)
from the standard risk factors have been derived
from the Framingham findings. To estimate the
risk of CHD in the study model, a model developed by the American Heart Association that
relies on age, gender, diabetes, smoking, systolic
blood pressure, and total cholesterol/HDL
cholesterol ratio as predictors was used.16 That

Table 9. Simulation of Symptomatic Neuropathy and Progression to Amputation
Race

Duration of
Diabetes (yrs.)

From Normal
to Symptomatic

Symptomatic 1st
Amputation

1st Amputation
2nd Amputation

White

0–8

0.0144

0.0280

0.1386

9–13

0.0144

0.0350

0.1386

14–19

0.0144

0.0467

0.1386

20+

0.0144

0.1400

0.1386

0–8

0.0432

0.0840

0.4158

9–13

0.0432

0.1050

0.4158

14–19

0.0432

0.1401

0.4158

20+

0.0432

0.4200

0.4158

Nonwhite

149
Table 10. Probabilities of Progression of Diabetic Retinpathy
Race

Diabetes
Duration

From R1
to R2

From R2
to R3

From R2
to R4

From R3
to R5

From R4
to R5

White

0–4

0.073

0.0025

0.047

0.088

0.05

5–9

0.129

0.0090

0.095

0.088

0.05

10–14

0.116

0.0095

0.092

0.088

0.05

15+

0.113

0.0260

0.080

0.088

0.05

0–4

0.154

0.0050

0.099

0.088

0.05

5–9

0.272

0.0190

0.200

0.088

0.05

10–14

0.245

0.0200

0.194

0.088

0.05

15+

0.238

0.055

0.169

0.088

0.05

0–4

0.196

0.007

0.126

0.088

0.05

5–9

0.346

0.024

0.255

0.088

0.05

10–14

0.311

0.025

0.247

0.088

0.05

15+

0.303

0.070

0.214

0.088

0.05

Black

Hispanic

formula predicts the 4-year risk of incident CHD
(defined as myocardial infarction, sudden death,
and stable or unstable angina). A 1-year risk of
incident CHD was calculated by assuming that the
hazard is constant over the 4-year interval and
applying the standard conversion formula.

Framingham-derived proportionate
morbidity ratios
The American Heart Association formula predicts
risk of CHD as a whole but does not distinguish
among its various manifestations. Because
different costs were to be assigned to different
manifestations of CHD, the incidence of
myocardial infarction and angina (both stable and
unstable) were estimated as follows: Counts of
incident cases of CHD, myocardial infarction,
and angina were taken from the reports of the
Framingham study.17 Age-group- and sex-specific
proportionate morbidity ratios were then calculated and applied. For example, among 55- to
64-year-old males in the Framingham study, 182
myocardial infarctions were observed among 305
incident cases of coronary heart disease. The ratio
0.597 was therefore used as the probability that a
simulated subject with predicted incident CHD in
a given year would have a myocardial infarction.

Other complications of hypertension
In addition to CHD, hypertension is the major risk
factor for strokes and congestive heart failure and
is a major contributor to renal failure as well. To
model the development of strokes and congestive
heart failure, the logistic regression models
developed in the Framingham Heart study for
these outcomes were used.18 The modeling of
hypertensive renal failure has been described
earlier.

General Population Mortality Rates
Age-, sex-, and race-specific general population
mortality rates were taken from Vital Statistics of
the United States, 1998.19

Discharge From Incarceration
Duration of time in prison is difficult to estimate
from available data. Prospective studies of
cohorts of inmates from incarceration through
discharge and subsequent reincarcerationdischarge cycles have not been published.
Sentence on admission cannot be used as a proxy
for time to be served because actual time served
may be substantially shorter or longer. Among
prisoners discharged in a given year, information

150
on time served is available, but these prisoners
may not be representative of all those currently
incarcerated. Time served varies from State to
State and facility to facility. Furthermore,
differences exist between those sentenced for
violent and nonviolent offenses. After review of
several data sources, it was assumed that the
average inmate serves 4.5 years and that the
distribution of length of stay is exponential. This
corresponds to an annual discharge probability of
slightly greater than 0.20 and is consistent with
Beck et al.20

Effects of Treatment
Hypertension is readily treated in the vast
majority of compliant patients. The effect of
blood-pressure-lowering interventions was
modeled by truncating the systolic blood pressure
distribution at 140 mmHg when simulating the
effects of treatment. This reflects rigorous
treatment. As a consequence of the lower blood
pressures, the risks of coronary heart disease and
renal failure are reduced, and these reductions
are reflected in lower counts of those events.
Treatment of hypertension was assumed to have
no effect on the incidence or progression of
complications of diabetes.
Treatment of diabetes has not yet been shown to
clearly reduce the incidence of coronary heart
disease. It does, however, substantially reduce the
risk of microvascular complications and the rate
at which they progress.21 In an analysis of the
Diabetes Control and Complications Trial (DCCT),
Eastman and colleagues fit a proportional hazards
model to the incidence of the various stages of
complications. It was found that with tight control

of diabetes (HbA1c maintained at 7.2 percent),
the relative risk for microalbuminuria is 0.34
and with compared routine diabetic care (HbA1c
maintained at 10.0 percent), the relative risk for
frank proteinuria is 0.073. With good diabetic
control, the relative risk of incidence of each
stage of neuropathy is 0.175.22
With good diabetic treatment, the progression
rates from retinopathy stages R3 and R4 to stage
R5 are reduced. Treated annual progression
probabilities were taken to be 0.0148 and 0.033,
respectively, for all races and all durations of
diabetes. (Compare with the rates of progression
assumed for untreated diabetes shown in table
10.) For incident background retinopathy, the
relative risk is estimated at 0.04; for macular
edema, 0.67; and for proliferative retinopathy,
0.126.

Costs of Morbid Outcome Events
When preventive programs such as the one
contemplated here are introduced, savings are
realized as a result of avoided future morbidity.
Although the savings so obtained seldom exceed
the outlays necessary to achieve them, they represent a meaningful offset against the total cost of
an intervention. Many of the complications of
hypertension and diabetes are quite costly, so this
offset is appreciable. Table 11 shows the assumed
costs for each of the complications modeled.
The costs per person-year of congestive heart
failure were estimated by dividing the annual
Medicare expenditures for this diagnosis by the
number of Medicare patients with the diagnosis.23
The costs of diuretics and ACE inhibitors were

Table 11. Estimated Unit Costs of Complications of Hypertension and Diabetes
Morbid Event or State

Unit Cost

Person-year with congestive heart failure

$2,188.40

Person-year with a lower extremity amputation

4,808.46

Incident case of coronary heart disease

15,952.00

Person-year of blindness

16,207.00

Person-year with end-stage renal disease

46,207.00

Incident stroke

50,000.00

151
added to that sum because these are not covered
by Medicare or reckoned in their reports. The
costs of lower extremity amputation were calculated by amortizing the costs associated with an
amputation and subsequent rehabilitation and
followup care and over the expected lifespan of
amputees.

additional facilities or service capacity are
required to carry out these tests. Some additional
expenses will be incurred for repeat blood pressure and blood glucose measurements to confirm
abnormal initial results. Overall, however, the
average per capita annual cost of screening and
confirmatory tests likely will not exceed $15.

The costs of incident coronary heart disease and
those of a person-year with end-stage renal
disease are taken from Eastman et al.;24 those
of a person-year of blindness are taken from
Javitt et al.25 Most published estimates of the
costs of stroke exceed $90,000,26 but costs of lost
earnings and productivity figure heavily in those
calculations. Because it is assumed that prisoners
are not gainfully employed while incarcerated and
primarily earn low wages after release, Matchar’s
lower estimate that excludes these costs was
used.27

Costs of Treatment

Not all stages of all complications incur costs.
Microalbuminuria requires no treatment and is
asymptomatic. Consequently no costs were
assigned to its presence. The early stages of
retinopathy necessitate both surveillance and
treatment, but these costs are included in
estimating treatment costs for diabetes (see
below), so they are not counted again here.

To achieve the benefits of treatment, resources
must be expended to lower blood pressure and
control hyperglycemia. For mild hypertensives,
treatment with dietary modifications and exercise
is often sufficient to bring about a normal blood
pressure. In those requiring medication, adequate
treatment can be achieved for almost all hypertensives by using a diuretic plus a beta-blocker.
Assuming that the least expensive generic brands
of drugs are used, and assuming five physician
checkups per year, the annual per capita cost of
treating hypertension will be approximately
$388.40.28 Eastman and colleagues have reported
the average increased costs associated with
aggressive diabetic treatment as $1,983 per
person-year.29 This amount includes the costs of
pharmacotherapy with insulin or oral agents,
materials for home glucose monitoring, periodic
eye examinations, and routine diabetic eye and
foot care.

Costs of Screening and Diagnosis

Effects of Treatment on Quality of Life

A major advantage of the prison setting for
screening is the essential absence of indirect
costs. Screening for hypertension and diabetes
mellitus in a prison simply requires applying
a sphygmomanometer and drawing a blood
glucose level during one of the numerous visits
made by prisoners each year to the prison
physician. Because prisoners are not gainfully
employed and are not free to pursue self-selected
leisure activities, no opportunity costs attach to
their undergoing these tests. Because prisoners
average more than 10 physician visits per year
(R. Greifinger, personal communication), no

Although treatment for hypertension often
produces side effects, these are less pronounced
with modern regimens than they were in the past.
No direct effect on quality of life was assumed
for treatment of either hypertension or diabetes
mellitus. Instead, this effect was reckoned by
counting the person-years of less than ideal
quality of life avoided when aggressive treatment
is used. Table 12 shows the quality-of-life
adjustment factors assumed. Detailed studies of
quality of life with congestive heart failure are
currently being carried out by several
investigators.

152
Table 12. Quality-of-Life Adjustments for Morbid Outcomes of the Analysis
Complication

Quality-of-Life Adjustment

Congestive heart failure

0.9

Status—after lower extremity amputation

0.8

Blindness

0.7

End-stage renal disease

0.6

Status—after cerebrovascular accident

0.5

Congestive heart failure is a heterogeneous
condition that can result in minimal impairment or
in major disability. The average quality-of-life
adjustment factor was estimated to be 0.9,
reflecting the preponderance of mild congestive
heart failure. The factors for lower extremity
amputation, blindness, end-stage renal disease,
and cerebrovascular accident were taken from
Eastman et al.,30 Javitt et al.,31 and Matchar.32
These figures were used as in the following
example: Each person-year of congestive heart
failure avoided by treatment results in a gain of
0.1 (=1!0.9) quality-adjusted life-years.

Results
As noted earlier, the effects of screening for
and aggressively treating diabetes mellitus
and hypertension are manifested in several
dimensions: Survival is improved, morbidity is
reduced, expenses for screening and treatment are
incurred, and savings for treatment of avoided
complications are realized. The diverse effects
on various types of morbidity, as well as the
improvement in survival, can be summarized by
enumerating quality-adjusted life-years (QALY)
and tallying the expenditures, net of any savings
associated with reduced later morbidity. The
overall impact may then be summarized as a
single number, the cost-effectiveness ratio (CER),
defined as:
CER =

Costs ( with treatment) - Costs ( without tr eatment)
QALY ( with treatment) - QALY ( without tr eatment)

Future events and costs are considered less
valuable than those in the present. Accordingly,
it is conventional, when calculating costeffectiveness ratios, to discount both the monetary
stream in the numerator and the morbidity/

mortality stream in the denominator at 3 percent
per annum.33

Survival and reduction in morbidity
Over 20 years of followup, without screening
and treatment, the 1,599,409 persons currently
incarcerated are expected to accrue 7,616,668.5
person-years of survival in prison, and an
additional 22,567,690 person-years of life outside
prison. With aggressive screening and treatment
and assuming 100-percent compliance, they will
live 7,620,436.5 person-years in prison and
22,950,030.0 person-years outside prison. Thus,
screening and treatment have the potential to
salvage 386,108 person-years of life for this
cohort over 20 years. Of these, more than 99
percent will be lived outside prison. In addition to
increased survival, screening and treatment
substantially reduce morbidity. Person-years of
blindness are reduced by 31,697 with 94.1 percent
of this realized outside prison and 61,021
episodes of coronary heart disease are avoided
with 91.7 percent of them outside prison. Personyears of congestive heart failure are reduced by
31,555 with 89.25 percent of those outside prison
and 44,400 strokes are avoided with more than 90
percent outside prison. Finally, 15,395 personyears of end-stage renal disease are avoided with
94.6 percent of them outside prison.

Expenditures
To achieve these benefits, outlays are made for
screening and treatment. Using the cost estimates explained earlier, the total direct cost of
screening in this population for 20 years will be
$204,817,860. The total costs of hypertension
treatment over this same period will be
$11,873,569,188. The cost of treatment for

153
diabetes will be $2,822,545,288. These expenses
will be partially offset by the savings from
avoided complications. Sixty-three percent of the
diabetes screening costs will be incurred outside
prison, as will 75 percent of the hypertension
treatment costs and 82 percent of the diabetes
treatment cost. The proportion of the benefit
realized outside prison is still greater.

Cost-effectiveness ratios
When discounting at 3 percent is applied to
reflect the distribution of costs, deaths, and
morbid events over time, the cost-effectiveness
ratio for the screening and aggressive treatment
strategy is $11,300 per QALY gained (rounded
to the nearest $100). This figure makes this
screening and treatment program one of the
best investments of health care dollars available.
This program would be more cost effective
than widely accepted measures such as mammography screening in women age 50–59, or
even cervical cancer screening in sexually active
women. Except for the assumption of 100-percent
compliance, all assumptions have been made
conservatively, to bias the costs upward and the
benefits downward. The figure of $11,300 per
QALY gained is really a cost-efficacy ratio. In the
real world, 100-percent compliance will not be
achieved.
Modeling partial compliance is problematic. Most
noncompliance consists of lapses in adherence or
incomplete dosing of medications. Estimates of
the extent of these behaviors are hard to acquire.
Instead, compliance has been modeled as follows.
Noncompliance is assumed not to reduce treatment costs. It is assumed, however, that noncompliance reduces the benefits of treatment
by an amount equal to the noncompliance rate.
In other words, 80-percent compliance in prison
is modeled by recasting the calculations using
the full costs of treatment, but recognizing
only 80 percent of the in-prison benefit. This
noncompliance model would be correct if, for
example, the specified fraction of patients made
regular physician visits and purchased their
medicines, but then discarded them. In reality,
noncompliance usually involves skipping some
visits and consuming less medication. This starker

model of noncompliance overestimates the costeffectiveness ratio for a treatment plan.
A realistic assumption might be that 80-percent
compliance can be obtained while in prison, with
50-percent compliance outside prison. Under
this 80/50 compliance assumption, the costeffectiveness ratio rises to $22,200 per QALY.
This still compares favorably with the costeffectiveness ratios of widely accepted practices.
The assumption that 80-percent compliance can
be achieved in prison is reasonable. But because
the cost-effectiveness ratio is sensitive to
compliance rates, a less favorable scenario was
also examined: 50-percent compliance both in and
out of prison. The 50-percent compliance rate is
widely believed to be obtained outside prison for
treatment of hypertension and diabetes. This
assumption makes a realistic assessment about
compliance out of prison, combined with the
assumption that adherence is not improved under
conditions of incarceration. This might be
regarded as a worst-case scenario. Even in these
pessimistically constructed circumstances the
cost-effectiveness ratio rises only slightly, to
$22,600 per QALY.

Recommendations and Discussion
Limitations
The approach taken in this analysis has limitations. It is a leap of faith to assume that the
prevalence of the conditions investigated and their
sequelae are properly represented by the relied
on sources (primarily NHANES–III and the
Framingham study). This leap of faith is necessitated by the lack of studies of the incarcerated
population specifically. Putting together estimates
of risk-factor prevalence from NHANES–III with
prognosis projections from Framingham is also
problematic because of partially differing case
definitions and the absence of ethnic stratification
in the Framingham models.
The analysis also makes simplifying assumptions
about the prison population. For example, it is
assumed that there is no value to inmates’ time
while incarcerated and that they will earn low

154
wages after release. Because suitable statistics
about recidivism were not available, it is also
assumed that once released from prison they do
not return. A better accounting of recidivism
would modify the distribution of costs and
benefits between the prison system and the
community outside prison, but would affect the
cost-effectiveness ratios negligibly, if at all. In a
related matter, the analysis takes no account of
possible additional criminal behavior during the
additional years of survival and better health.
The cost estimates used in this analysis are a few
years old. Adjustment to 1999 dollars would
increase the estimated cost-effectiveness ratios
only slightly because health care inflation has
been moderate in the past 5 years and none of
the estimates are from sources older than that.
It has been assumed that annual screening for
hypertension and diabetes can be carried out for
only $15 per capita by using existing capacity and
disregarding indirect costs. This assumption
might be excessively optimistic. Some facilities
might not currently perform routine blood tests, in
which case the incremental costs of screening for
diabetes would be higher. Even when the costeffectiveness ratios are recalculated, assuming
$45 per person per year, those ratios only rise by
approximately 20 percent.
Finally, the model treats the prison population as
essentially homogeneous across jurisdictions and
facilities. The age-, sex-, and race-specific
prevalence of hypertension and diabetes or the
distributions of lipids and smoking may differ by
geography or by prison. Although this does not
invalidate the overall conclusion, examining such
heterogeneity might make it possible to identify
target areas that present unusually good opportunities for prevention or other places where a
less intensive program might be sufficient.

Recommendations
Using conservative assumptions throughout,
the conclusion seems inescapable that annual
screening for hypertension and diabetes, followed
by aggressive treatment of these conditions, is an
excellent investment of health care resources.
Hypertension screening and treatment should be

carried out in accordance with the recommendations of the Joint National Committee for the
Detection, Evaluation and Treatment of High
Blood Pressure.34 Screening for diabetes can be
accomplished with a single fasting blood sugar.
If the result exceeds 125 mg/dL, a subsequent
postprandial blood sugar can be obtained, and a
diagnosis made if the result exceeds 140 mg/dL.
Subsequent treatment should include “home”
glucose monitoring, dietary management, and
appropriate use of insulin or oral hypoglycemic
agents, with a target HbA1c level of 7.2 percent.
Routine diabetic care should include periodic
examinations of the optic fundi and the feet.
Most of the costs of the program and an even
larger share of its benefits will be incurred outside prison. The results are sensitive to the degree
of treatment compliance attained, but even under
relatively pessimistic assumptions, the costeffectiveness ratio still remains a bargain compared with many widely accepted preventive
practices.
The United States Preventive Services Task
Force’s Guide to Clinical Preventive Services
currently recommends screening for hypertension
by taking blood pressure but does not specify a
particular frequency. The task force does not
currently recommend screening for diabetes. Its
recommendation, however, predates the demonstration that aggressive treatment of diabetes
substantially reduces complications.35 It is
expected that future editions of the Guide will
endorse screening for diabetes mellitus.
Policymakers look beyond cost-effectiveness
ratios to other considerations. Some might
question the justice of providing state-of-the-art
health care to those who have transgressed
society’s rules while others outside prison lack
access to even rudimentary health care. It is also
debatable whether providing first-rate health care
to prisoners is politically viable in the current
climate. To some extent, both of these concerns
are mitigated by the observation that the bulk of
the impact of the proposed interventions will be
attained after prisoners are released, having paid
their debt to society and begun contributing to the
economy again.

155
In addition to the recommendations for screening
and treatment, it is recommended that the authorities responsible for correctional facilities make
health information specific to prisoners available.
The simplest way to accomplish this might be to
include a sample of prisoners in future iterations
of the National Health and Nutrition Examination
Survey. Reports on the health status of prisoners
will prove invaluable in planning, setting, and
evaluating health care policy for this large
segment of the U.S. population.

Notes
1. National Center for Health Statistics, National
Health and Nutrition Examination Survey III.
Washington, DC: U.S. Department of Health and
Human Services, Centers for Disease Control and
Prevention, 1997.
2. Diabetes Control and Complications Trial Research
Group, “The Effect of Intensive Treatment of Diabetes
on the Development and Progression of Long-Term
Complications in Insulin-Dependent Diabetes
Mellitus,” New England Journal of Medicine
329(1993): 977–986.
3. U.K. Prospective Diabetes Study Group, “U.K.
Prospective Diabetes Study (UKPDS),” Diabetologia
34(1991): 877–890.
4. Palisades Decision Tools, Newfield, NY.
5. Hornung, C.A., B.J. Anno, R.B. Greifinger, and
S. Gadre, “Health Care for Soon-To-Be-Released
Inmates: A Survey of State Prison Systems,” paper
prepared for the National Commission on Correctional Health Care, Chicago, Illinois, June 1999.
(Copy in this volume.); R. Scott Chavez, personal
communication.
6. Stata Corp., College Station, TX.
7. Schechter, C.B., and R.S. Adler, “Bayesian Analysis
of Diastolic Blood Pressure Measurement,” Medical
Decision Making 8(1988): 182–190.
8. Schechter, unpublished observations.
9. Anderson, K.M., P.W.F. Wilson, P.M. Odell, and
W.B. Kannel, “An Updated Coronary Risk Profile: A
Statement for Health Professionals,” Circulation
83(1)(1991): 356–362.

10. Geiss, L.S., W.H. Herman, M.G. Goldschmid,
F. DeStefano, M.S. Eberhardt, E.S. Ford, R.R.
German, J.M. Newman, D.R. Olson, S.J. Sepe et al.,
“Surveillance for Diabetes Mellitus—United States,
1980–1989,” Morbidity and Mortality Weekly Report
42(SS–2)(1993): 1–20.
11. Eastman, R.C., J.C. Javitt, W.H. Herman, E.J.
Dasbach, C. Copley-Merriman, W. Maier, F. Dong,
D. Manninen, A.S. Zbrozek, J. Kotsanos, S.A.
Garfield, and M. Harris, “Model of Complications of
NIDDM. II: Analysis of the Health Benefits and CostEffectiveness of Treating NIDDM With the Goal of
Normoglycemia,” Diabetes Care 20(5)(1997):
725–734.
12. National Institute of Digestive and Kidney
Diseases, Division of Kidney, Urologic, and
Hematologic Diseases, United States Renal Data
System: 1999 Annual Data Report, Bethesda, MD:
National Institutes of Health, National Institute of
Digestive and Kidney Diseases.
13. Eastman, R.C., J.C. Javitt, W.H. Herman, E.J.
Dasbach, C. Copley-Merriman, W. Maier, F. Dong,
D. Manninen, A.S. Zbrozek, J. Kotsanos, S.A. Garfield, and M. Harris, “Model of Complications of
NIDDM. II: Analysis of the Health Benefits and CostEffectiveness of Treating NIDDM With the Goal of
Normoglycemia” (see note 11).
14. Klein, R., “Hyperglycemia and Microvascular and
Macrovascular Disease in Diabetes,” Diabetes Care
18(1995): 258–268; Eastman, R.C., J.C. Javitt, W.H.
Herman, E.J. Dasbach, C. Copley-Merriman, W.
Maier, F. Dong, D. Manninen, A.S. Zbrozek, J.
Kotsanos, S.A. Garfield, and M. Harris, “Model of
Complications of NIDDM. II: Analysis of the Health
Benefits and Cost-Effectiveness of Treating NIDDM
With the Goal of Normoglycemia” (see note 11).
15. Javitt, J.C., L.P. Aiello, Y. Chiang, F.L. Ferris, J.K.
Canner, and S. Greenfield, “Preventive Eye Care in
People With Diabetes is Cost-Saving to the Federal
Government: Implications for Health-Care Reform,”
Diabetes Care 17(8)(1994): 910–917.
16. Anderson, K.M., P.W.F. Wilson, P.M. Odell, and
W.B. Kannel, “An Updated Coronary Risk Profile: A
Statement for Health Professionals” (see note 9).
17. Kannel, W.B., and T. Gordon, eds., The Framingham Study: An Epidemiological Investigation of
Cardiovascular Disease, Washington, DC: U.S.
Government Printing Office: Section 26, 1987.

156
18. Ibid.
19. National Center for Health Statistics, Vital
Statistics of the United States, 1998. Washington, DC:
U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention, 1999.
20. Beck, A., D. Gilliard, L. Greenfeld, C. Harlow, T.
Hester, L. Jankowski, T. Snell, J. Stephan, and D.
Morton, Survey of State Prison Inmates, 1991,
Washington, DC: U.S. Department of Justice, Bureau
of Justice Statistics, 1993, NCJ 136949: 7.
21. Diabetes Control and Complications Trial Research
Group, “The Effect of Intensive Treatment of Diabetes
on the Development and Progression of Long-Term
Complications in Insulin-Dependent Diabetes
Mellitus” (see note 2); U.K. Prospective Diabetes
Study Group, “U.K. Prospective Diabetes Study
(UKPDS)” (see note 3).

Economic Impact of Stroke,” Neurology 45(2 Supp.
1)(1995): S6–S9.
27. Matchar, D.B., “The Value of Stroke Prevention
and Treatment,” Neurology 51(3 Supp. 3): S31–S35.
28. Pearce, K.A., C. Furberg, B.M. Psaty, and J. Kirk,
“Cost Minimization and the Number Needed to Treat
in Uncomplicated Hypertension,” American Journal of
Hypertension 11(1998): 618–629.
29. Eastman, R.C., J.C. Javitt, W.H. Herman, E.J.
Dasbach, C. Copley-Merriman, W. Maier, F. Dong,
D. Manninen, A.S. Zbrozek, J. Kotsanos, S.A.
Garfield, and M. Harris, “Model of Complications of
NIDDM. II: Analysis of the Health Benefits and CostEffectiveness of Treating NIDDM With the Goal of
Normoglycemia” (see note 11).
30. Ibid.

22. Eastman, R.C., J.C. Javitt, W.H. Herman, E.J.
Dasbach, A.S. Zbrozek, F. Dong, D. Manninen, S.A.
Garfield, C. Copley-Merriman, W. Maier, J.F.
Eastman, J. Kotsanos, C.C. Cowie, and M. Harris,
“Model of Complications of NIDDM. I: Model
Construction and Assumptions,” Diabetes Care
20(5)(1997): 725–734.

31. Javitt, J.C., L.P. Aiello, Y. Chiang, F.L. Ferris, J.K.
Canner, and S. Greenfield, “Preventive Eye Care in
People With Diabetes is Cost-Saving to the Federal
Government: Implications for Health-Care Reform”
(see note 15).

23. Funk, M., and H. Krumholz, “Epidemiologic and
Economic Impact of Advanced Heart Failure,” Journal
of Cardiovascular Nursing 10(2)(1996): 1–10.

33. Gold, M.R., J.E. Siegel, L.B. Russell, and M.C.
Weinstein, eds., Cost-Effectiveness in Health and
Medicine, New York: Oxford University Press, 1996:
230–235.

24. Eastman, R.C., J.C. Javitt, W.H. Herman, E.J.
Dasbach, C. Copley-Merriman, W. Maier, F. Dong,
D. Manninen, A.S. Zbrozek, J. Kotsanos, S.A. Garfield, and M. Harris, “Model of Complications of
NIDDM. II: Analysis of the Health Benefits and CostEffectiveness of Treating NIDDM With the Goal of
Normoglycemia” (see note 9).
25. Javitt, J.C., L.P. Aiello, Y. Chiang, F.L. Ferris,
J.K. Canner, and S. Greenfield, “Preventive Eye Care
in People With Diabetes is Cost-Saving to the Federal
Government: Implications for Health-Care Reform”
(see note 15).
26. Taylor, T.N., “The Medical Economics of Stroke,”
Drugs 54(Supp. 3)(1997): 51–54; Dobkin, B., “The

32. Matchar, D.B., “The Value of Stroke Prevention
and Treatment” (see note 27).

34. Joint National Committee for the Detection,
Evaluation, and Treatment of High Blood Pressure,
The Sixth Report of the Joint National Committee on
the Prevention, Detection, Evaluation, and Treatment
of High Blood Pressure, Bethesda, MD: National
Institutes of Health, National Heart, Lung, and Blood
Institute, 1997.
35. U.S. Preventive Services Task Force, Guide to
Clinical Preventive Services, 2d. ed., Baltimore, MD:
Williams and Wilkins, 1996: 39–52, 193–208.

157

Providing Psychiatric Services in
Correctional Settings
Bonita M. Veysey, Ph.D., and Gisela Bichler-Robertson, M.A., Rutgers University
School of Criminal Justice

Introduction

Jails

Persons with mental illnesses present special
problems to corrections administrators and staff.
Left untreated, they are at increased risk of
suicide, victimization, causing disturbances
among inmate populations, and disciplinary
infractions. In the community, these problems
persist, as well as increased risks of homelessness,
health problems, and, under certain circumstances,
violence.

The United States has approximately 3,500 jails
today. These locally operated facilities provide
pretrial detention and short-term confinement
after sentencing. They are best characterized as
people-processing organizations with heavy
flowthrough. Jails are increasingly important in
identifying and treating acute and chronic medical
and psychiatric conditions at a time when indigent
care is dwindling. Unlike community-based
treatment providers, jails, by their very nature,
cannot refuse any individual presented to them by
legitimate authority.

Providing mental health services to offenders who
require them is necessary for the safety and wellbeing of offenders and staff, the smooth operation
of corrections, and community safety and quality
of life. To ensure continuity of care, police and
corrections administrators must come together
with mental health and substance abuse providers
to identify and close the gaps in service. Law
enforcement and community corrections staff,
in particular, must work aggressively with
community leaders to develop effective linkages to help persons with mental illnesses live
successfully in the community, particularly at
critical transition points between incarceration
and the free community.
Each point in the criminal justice system brings
with it unique service challenges. Institutional
corrections differ significantly from community
corrections. Jails and prisons, while similar in
many aspects of psychiatric care, differ on several
points. The following sections discuss the opportunities to provide mental health services in jails,
prisons, and community corrections.

Jails have a substantial constitutional obligation to
provide minimum care. Custodial facilities have
both the duty to protect and the duty to treat
serious medical and psychiatric conditions. In
addition to case law such as Estelle v. Gamble1
and Bowring v. Godwin2 that establishes the
standards of medical and mental health care,
Langley v. Coughlin3 provides a list of the several
specific claims that, in conjunction with deliberate
indifference, indicate constitutionally inadequate
mental health care.4 Clearly, providing mental
health services to persons with mental illnesses
who come into contact with the criminal justice
system is not an option, but a constitutional
necessity. Despite these requirements, a study of
mental health services in U.S. jails with rated
capacities of 50 or more detainees indicated that,
while most jails offered at least one mental health
service, few jails provided a comprehensive range
of services.5 Approximately 83 percent of all U.S.
jails provided intake screening and 60 percent

158
provided mental health evaluations, but only 42
percent provided psychiatric medications. In
response to emergencies, only 43 percent
provided crisis intervention services, 73 percent
provided suicide prevention services, and 72
percent provided access to inpatient hospitalization. Finally, only 21 percent of jails provided
case management or discharge planning.6
Jail mental health services are typically focused
on identification, crisis management (including
suicide prevention), and short-term treatment.
Two basic principles guide the minimum requirements: (1) persons in detention should not leave
the facility in worse condition than when they
arrived and (2) persons should not be punished for
being identified as having a need (i.e., the identification of a mental illness should not affect
access to other services or the length of time
spent in jail).

Screening, assessment, and evaluation
Screening, assessment, and evaluation are the
three stages at which jails identify persons in need
of psychiatric care. The initial screen is typically
conducted by a corrections officer at booking.
The purpose of this screen is to identify persons
in need of a more detailed mental health evaluation and those at risk for suicide. Officers are
not trained clinicians and are not expected to
make decisions regarding treatment. The booking
officer’s job is to refer all individuals who,
because of their responses to specific questions
or by their appearance or behavior, appear to be
at risk.
A mental health assessment is often a second step
toward providing treatment. This can be done by a
mental health worker or by medical staff within
the context of a medical history. Both the booking
screen and the medical examination are done on
all individuals who are booked into the jail and
assigned housing. The mental health assessment
is conducted only on persons identified by the
booking screen or by the medical department.
At the final stage, persons assessed as needing
psychiatric services are referred for a full
psychiatric evaluation. Psychiatric evaluations

are usually conducted by a psychiatrist and often
result in the prescription of medication.
Screening, assessment, and evaluation are critical
points in the service delivery system for providing appropriate services because information
uncovered at these points affect classification
decisions and whether detainees will receive
mental health and other treatment services.
Screening instruments used by booking officers
should include a minimum set of questions related
to symptoms of affective and psychotic disorders,
history of mental health treatment, current use of
prescribed psychotropic medication, and risk of
suicide.

Classification and housing
Structurally, jails are designed to control the
potential for violence. Their primary mandate is
to hold individuals in a secure environment and
prevent physical injury to either staff or detainees.
Single-cell tiers and pods, highly regimented
schedules, lack of privacy, and an expectation
of an unquestioning response to authority are
characteristics of correctional facilities designed
to maximize control and reduce opportunities for
breaches in security (e.g., escapes, riots and
violent incidents, use of contraband). Individuals
with acute mental illnesses may have extreme
difficulties conforming their behavior to what is
required. This structure may, in fact, create an
additional unintended burden on detainees with
mental illness and increase disciplinary incidents
and related punishment.
Classification refers to the process by which
individuals booked into the jail are assigned
housing. Appropriate classification takes into
account the seriousness of the current offense and
risk of violence; special needs, such as medical or
mental health problems; gender and age; and
adjudication status. Most jails assign different
security levels within their facilities and have
different kinds of housing, including general
population, medical (where persons diagnosed
with acute mental illnesses or suicide risk may be
placed), and administrative segregation. Some
jails also provide specialized housing, such as

159
mental health units for persons with stable
conditions, substance abuse therapeutic communities, trustee housing, and juvenile units.
Because many jails do not provide inpatient care
or specialized housing for individuals diagnosed
with mental illnesses, many detainees are transferred to civil psychiatric facilities to receive
treatment. While this is a humane and medically
sound policy, it has serious, unintended consequences. First, a transfer out of the jail for
evaluation or inpatient treatment interrupts and
may significantly delay the adjudication process,
extending the period of confinement. Second, the
inpatient facility may not be within the locality.
This means that the individual may not be able to
see family and other support persons easily, if at
all.

Medication and psychiatric followup services
Medication and medication monitoring are major
issues for jail psychiatry. Some jails do not allow
the prescription of certain antidepressants and
tranquilizers because of their cost or potential for
abuse. Despite indications or previous treatment,
some individuals cannot receive the medication of
choice due to standing policies. On the other
hand, these policies exist for good reason. Detainees with significant addictive disorders may
request psychiatric medications as a substitute for
their drug of choice. Each case must be reviewed
carefully before medication is prescribed and at
regular intervals thereafter to assure that the
medications are appropriate to the need.
Overprescription of medication is as problematic
as underprescription. Because many facilities are
overcrowded, housing is limited and management
of detainee populations is more difficult. In
stressed environments, there is a temptation to
overprescribe medications for the sole purpose
of tranquilizing the detainee. From the jail’s
perspective, this is a reasonable policy because it
enhances the jail’s security. From a human rights
perspective, it is an unjustified use of chemical
restraints and violates constitutional rights. In
addition, the medication may interfere with the
detainee’s ability to participate in his or her
adjudication process.

Crisis intervention and suicide precautions
Every jail should have established procedures
to identify and respond to psychiatric crises,
including suicide risk. Emergency responses may
include emergency evaluations, close observation in a special housing area, removal of the
individual to a medical/surgical or inpatient unit
within the jail, or transfer to a psychiatric facility
outside the jail. In addition, physical and chemical
restraints may be used under the supervision of
medical staff. The critical feature of emergency
response is providing a safe environment for
acutely distressed detainees. This sometimes
requires the removal of objects that may be used
to injure oneself or to harm others. This should
not be interpreted to mean that clothing should be
removed or that the individual be isolated. These
two common procedures often exacerbate the
problem.
The policies and procedures governing the use of
seclusion and physical and chemical restraints
should be carefully reviewed for their application.
Some mental health systems are beginning to
consider these issues in response to a growing
awareness of how these procedures damage
individuals’ physical and emotional well-being.

Case management and discharge planning
Most jails do not provide case management or
discharge planning services. Arguably, release
planning can be the most important service a jail
can provide to reduce the probability of return.
For all persons with special needs, linkages to
community services, particularly if the linkage
is more than a telephone appointment, can make
a significant difference in engagement in
community-based services.
Although most jails acknowledge this important
service, the manner in which inmates are processed limits a jail’s ability to develop effective
linkages. Most importantly, it is critical to understand that the court makes release decisions.
Except when inmates serve specific sentences,
jails do not typically know when someone will be
released, whether it is pretrial or on sentencing.
Therefore, beginning discharge planning early

160
in confinement is important. On release, individuals with mental illnesses typically require
specific community-based services, including,
at a minimum, housing, financial support and
entitlements, health care, and mental health clinic
services. Of all the potential problems that jails
encounter in discharge planning, the most
difficult to negotiate is continuity of mental health
treat-ment, particularly providing uninterrupted
med-ication. Lack of medication and basic
necessities of life (i.e., housing, clothing, food,
and health care) virtually guarantee the return of
the individual to jail.

Prisons
Prisons are correctional facilities that hold
sentenced inmates generally for more than 1 year.
These facilities are operated by the Federal and
State governments, and increasingly by private
companies. Currently, the Federal government
operates 112 facilities, including traditional
prisons; work farms; boot camps; and Immigration
and Naturalization Service, Bureau of Indian
Affairs, and military facilities. State governments
operate 928 facilities, including traditional
prisons, youth detention facilities, work farms,
boot camps, and specialty units for prisoners (e.g.,
forensic hospital units, substance-abuse treatment
facilities, medical units). Private companies
currently run 156 correctional facilities, including
traditional prisons and specialty facilities (e.g.,
sex offender units, substance abuse facilities).
The responsibility for mental health provision
varies from State to State; in some States, psychiatric care is provided under the auspices of
the State mental health authorities, and in others,
under the auspices of the State corrections authority. As in jails, behavioral health services in State
and Federal prisons are frequently contracted out.
Of the State-operated adult prison facilities, 83
percent provide mental health screening and
assessment, 80 percent provide and monitor
medications, and 77 percent provide access to
inpatient care. In addition, 36 percent of prisons
have specialized housing for individuals with
stable mental health conditions and 87 percent
of correctional facilities offer some form of
counseling or verbal therapy.7

Jails and prisons differ somewhat in the scope of
mental health services provided. This reflects the
difference in average lengths of confinement. As
stated earlier, jails process a large volume of
detainees and have relatively short lengths of
stay. Therefore, jail mental health services are
primarily concerned with suicide prevention and
stabilization of acute conditions. Prisons, on the
other hand, are more aptly described as contained
communities where individuals may spend many
years. Therefore, prisons provide a greater range
of services emphasizing long-term support,
including residential units for individuals with
stable conditions who cannot be placed in general
population, case management, and counseling and
verbal therapies.

Screening and assessment
Most States have a reception center where
inmates are processed and assigned permanent
housing. This central facility often holds new
inmates for several months, during which time the
inmates’ needs and security levels are determined.
This is the key point in identifying mental health
treatment needs. Because inmates may arrive
from local facilities in stable condition with or
without accompanying medical and psychiatric
records, prisons must have a capacity to assess
individuals continuously for psychiatric problems.
Screening and evaluation are conducted in prisons
in much the same way as in jail settings. An
initial screen is conducted on all incoming
inmates and evaluations are ordered for those who
appear to require services.

Crisis intervention and suicide precautions
Mental health crises can occur at any time. Given
the cyclic nature of many serious mental illnesses,
crises should be expected. Therefore, crisis
services must be available 24 hours a day in all
facilities. Early response is critical to stabilize the
individual and prevent further deterioration of the
inmate’s condition. Possible emergency responses
are similar to those in jails, including emergency
evaluations, close observation in a special
housing area, physical or chemical restraints, and
moving the individual to an inpatient unit inside
or outside the facility.

161

Mental health treatment

Community Corrections

Given the long periods of confinement of most
prison inmates, greater opportunities exist to
provide long-term mental health care. In addition
to medication and periodic reviews, individual or
group therapies and rehabilitation programs may
be developed and implemented in prison settings.
Some behavioral interventions appear promising.

Community corrections is a generic term used to
describe the authorities responsible for supervising offenders serving a community sentence
and individuals released from detention while
awaiting trial. These include traditional probation
and parole departments, pretrial services, and
alternatives to incarceration programs. According
to the Community Corrections Division of the
National Institute of Corrections, the primary
intent of community corrections supervision
in most U.S. jurisdictions has changed from
rehabilitation to risk reduction through a
community-based sanction.8 The main goal is the
protection of the community. With growing
correctional populations and ever increasing
costs of incarceration, community corrections
alternatives, with their emphasis on “control,
treatment, and services outside an institutional
placement,” are gaining popularity.9

Specialized housing and inpatient care
Meeting the needs of inmates with mental
illnesses over long periods of time requires a full
array of housing options, including inpatient care,
short-term crisis beds, long-term residential
treatment units, and general population housing.
Inpatient care is a necessary component of
treatment, but does not necessarily have to be
provided within the facility. Prisons, however,
must have the capacity to access such care.
Other residential alternatives can dramatically
reduce the need for inpatient beds. These units do
not necessarily require 24-hour medical supervision and are a cost-effective alternative to
inpatient care. Acute crisis beds may be available
to provide short-term relief short of inpatient
hospitalization. Inmates with mental illnesses
often have difficulty adjusting to and managing
the stresses of prison life and are often vulnerable
to abuses by other inmates and staff. Long-term
residential treatment units can provide a safe and
therapeutic environment in which to live. These
units may be permanent or transitional.

Discharge planning
Discharge planning is more complicated in
prisons than in jails. First, prisons are often
located far from the inmate’s home community.
Further, formal or informal relationships are
rarely developed between State prison staff and
local providers. A prison-based case manager can
do little to facilitate continuity of care on the
inmate’s release. In the case of a release to parole,
communication between corrections departments
may allow for prerelease planning and the possibility of requiring mental health treatment as a
condition of release.

Risk reduction functions by motivating offenders
to refrain from criminal activities or, for those
who cannot or will not refrain, removing the
offender from the community. It is becoming
clear that an emphasis on surveillance alone
increases the probability of early detection of
violations, but does not reduce criminal behavior
or assist offender rehabilitation. If the goal of
probation is risk management, programs that are
designed to reduce criminal activity or increase
community integration may offer long-term
solutions by intervening before recidivism occurs.
Like jails and prisons, probation and parole
departments have experienced explosive growth
over the past decade. In 1995, 2,620,560 adults
were under active probation supervision and
648,921 were under active parole supervision.
The growing community corrections population
includes increasing numbers of persons with
special treatment needs. Although probation
caseloads continue to grow, departmental
expenditures have not kept pace.10 With evergreater reliance on community corrections to
manage persons at risk, departments are required
to provide quality services with fewer resources.

162
The management of persons with mental illnesses
is particularly problematic for community
corrections agencies. Unlike jails and prisons,
community corrections incur no constitutional
mandate to provide health care, including
psychiatric services, to individuals under
community supervision. Because community
corrections agencies do not have 24-hour physical
custody of the offender, they are not required to
maintain an individual’s health status. Community
corrections agencies are not required to provide
universal medical or psychiatric care or even
access to these services. For persons with mental
health treatment conditions, community corrections must only assure access to appropriate
treatment and supervision of participation. If
mental health treatment is not a condition of
release, individuals receiving mental health
services do so voluntarily. These persons should
be able to access mental health resources in the
same manner as any other community member.
The double stigma of being identified as both an
offender and a recipient of mental health services
(and commonly with comorbid substance abuse or
dependence) creates real barriers in accessing
services in the community. In this time of fiscal
constraints and competition for scarce resources,
offender services and services for persons with
serious mental illnesses have a low priority. In
addition, decreasing community resources,
particularly the lack of 24-hour emergency mental
health services, have increased the likelihood that
persons with mental illnesses will come into
contact with the criminal justice system.11 Without
an affirmative decision to make this group a
priority, these individuals will continue to cycle
through the criminal justice and public mental
health systems.

Roles for mental health practitioners in
community corrections
Because providing mental health services is not
required, the involvement of mental health practitioners in community corrections is not clear or
obvious. There are, however, several opportunities for community corrections to engage
community-based mental health practitioners to
assist them in accomplishing their goals. These

fall into the general categories of assessment/
evaluation, training, and treatment, and exist at
the points of adjudication and probation intake,
investigation, or supervision.

Adjudication and the courts
An important change in the interface between
community corrections and mental health occurs
in the administration of specialty courts. Over the
past decade, mental health diversion programs
and, more recently, mental health courts have
been gaining in popularity. Many jurisdictions are
using these programs to engage offenders in
community-based mental health services instead
of serving jail time. Whether the programs are for
pretrial release or fully adjudicated cases,
community corrections agencies often supervise
these offenders and their participation in required
services in the community. Court-based or
program-based mental health professionals
(including psychiatrists, psychologists, and
psychiatric social workers) play an important role
in assessing the status and needs of persons
appropriate for specialty courts or diversion.
These programs cannot function as intended
without professionally trained staff to assist in
screening and recommending services.

Training and education
Community mental health practitioners can
provide an invaluable resource to community
corrections departments through preservice and
inservice training and education. Field officers
who may supervise persons with mental illnesses
on generic caseloads and officers who supervise
mental health caseloads both need training. The
intensity and detail of the training may differ
depending on the officer’s role in relation to
persons with mental illnesses. A basic understanding of mental health issues and appropriate
crisis management, as well as substance abuse
and emergency medical treatment, should be
included in preservice training, supplemented as
needed by inservice training. Community
corrections officers who supervise specialized
caseloads of individuals with mental illnesses
should have a greater knowledge base, including
the symptoms of mental illnesses; uses and effects
of common psychotropic medications; the range

163
of mental health services, their purposes, and
goals; and most important, the availability of
emergency and community-based mental health
services and how to access them.
Cross-training is an important component in all
settings where criminal justice and mental health
professionals work together. For effective community supervision of persons with mental illnesses, community corrections staff and mental
health providers must understand each other’s
roles.

Mental health treatment, rehabilitation, and
support programs
Community corrections is first and foremost a
corrections agency. Community corrections
should continue to perform its traditional duties
without expanding its responsibilities to include
treatment. Mental health treatment providers are
experts in their fields and should be fully utilized
by community corrections departments. Accomplishing the overall goal of community integration and long-term success of persons with
mental illnesses requires community corrections
department involvement in partnerships with
community mental health, substance abuse, and
other human services agencies. Creative
collaboration can accomplish the goals of all
systems.
Most community corrections departments provide
access to mental health treatment on an as-needed
basis. Community corrections departments or
individual officers broker services as the need
arises. In this case, the department will identify
all necessary services and negotiate access for
specific individuals. Given the small percentage of persons with mental health treatment
conditions under community supervision, many
departments believe that arranging for services
for individuals as needed accomplishes the
community corrections department’s short-term
goals of meeting the court’s supervision requirements in the most flexible, cost-effective manner.
This ad hoc brokering approach may be the best
strategy in small communities, where familiarity
with the offender and informal interagency
relationships are the norm. In larger communities,

however, this approach to access to services is
time consuming, labor intensive, and may create
service redundancies.
Some community corrections agencies have
developed standing contracts with community
providers. These working agreements support
the activities of both systems and the clients they
jointly serve. Community agencies that work with
individuals serving community sentences are
more likely to be familiar with corrections practices and more receptive to involuntary clients.
Such arrangements may also allow community
corrections officers to intervene at the mental
health service provider site when emergencies
involve persons under their supervision.
Some of the most comprehensive and promising
programs for individuals with mental illnesses are
jointly sponsored and developed by community
mental health agencies and community corrections departments. Departments that have developed surveillance and revocation practices in
conjunction with appropriate, integrated mental
health services that individuals are willing to use
have had good results. Joint ventures acknowledge
that the community corrections department is not
the best agency to determine the clinical and
support needs of persons with mental illnesses.
Typically, collaborative efforts between community corrections and community mental
health agencies use one of two strategies: (1)
single-point access to services; or (2) holistic
programs with colocation of services.
Single-point access to community-based
services. This approach involves the joint
development of community corrections–mental
health case management programs, particularly
Intensive Case Management (ICM) or Assertive
Community Treatment (ACT) programs. The
core ideas within both of these service approaches
are: (1) client centered, (2) continuity of care,
(3) comprehensive services, (4) 24-hour, 7-day
availability, (5) small caseloads, (6) and service
delivered in natural environments. ICM models
may use one case manager or a team of case
managers. ICM programs typically provide
support for many domains of living, including

164
mental health, substance abuse, housing, money
management, and other support services. Intensive case managers may also provide counseling
and training in daily living activities. ICM
funding and the intensity of the services are
flexible. Such programs appear to be effective in
reducing the inappropriate use of psychiatric
services and the number of days spent in hospitals
and jails by some of the most difficult to serve
individuals.

Both single-point access and comprehensive
colocation of services appear to be effective
strategies in managing persons with mental
illnesses who are serving community sentences.
These programs reduce the duplication of services
(particularly case management services), increase
information flow, and have superior client outcomes, while reducing recidivism and attending to
the individual’s reintegration into his or her
community.

ACT models share many of the same core
components as ICM models. The distinguishing
feature of ACT models is the use of interdisciplinary teams of clinical and support staff.
Teams typically include psychiatrists, registered
nurses, psychiatric social workers, and other
paraprofessional case workers. Each team is able
to provide “generic mental health services,
psychiatric evaluations, crisis intervention,
individual therapy, group therapy, medication
administration/monitoring, assistance with
activities of daily living, budgeting, and full case
management services.”12

Notes

These models have had a great deal of success,
reducing both hospital admissions and average
number of inpatient days among persons with
mental illnesses in the community.13 Applied to
criminal justice populations, several studies have
found that ICM programs reduce the risk of
violence in the community, including fewer
average days in jail, fewer arrests, and reduced
incidence of harmful behavior.14
Collaborative colocation of services. It is
often difficult for persons with mental illnesses
to negotiate one, much less multiple, service
systems. In response, some innovative programs
for persons with mental illnesses use day
reporting/day treatment centers that combine
community corrections monitoring with comprehensive mental health services. In addition to
core clinic and case management services, these
programs often provide money management,
housing, assistance with gaining other needed
supports, education and job training, and close
monitoring through daily reporting.

1. Estelle v. Gamble, 429 U.S. 97 (1976).
2. Bowring v. Godwin, 551 F.2d 44 (4th Cir 1977).
3. Langley v. Coughlin, 888 F.2d 252 (2d Cir. 1989).
4. Cohen, F., and J. Dvoskin, “Inmates with Mental
Disorders: A Guide to Law and Practice,” Mental and
Physical Disability Law Reporter 16(3–4)(1992):
39–46, 462–470.
5. Steadman, H.J., and B.M. Veysey, Providing
Services for Jail Inmates With Mental Disorders,
Research in Brief, Washington, DC: U.S. Department
of Justice, National Institute of Justice, 1997, NCJ
162207.
6. Ibid.
7. Manderscheid, R.W., and M.A. Sonnenschein, eds.,
Mental Health, United States, 1992, Rockville, MD:
U.S. Department of Health and Human Services, 1992,
DHHS (SMA) 92–142.
8. Barajas, E., Jr., B.J. Nidorf, and R.P. Stroker,
“Reinventing Community Corrections,” in Topics in
Community Corrections, Longmont, CO: U.S.
Department of Justice, National Institute of
Corrections, Summer 1993.
9. Ibid.
10. Byrne, J.M., A.J. Lurigio, and C. Baird, “The
Effectiveness of the New Intensive Supervision
Programs,” Research in Corrections 2(2)(1989): 1–49;
Jacobs, J.B., Inside Prisons: Crime File Series Study
Guide, Washington, DC: U.S. Department of Justice,
National Institute of Justice, 1986, NCJ 100743.

165
11. Veysey, B.M., and H.J. Steadman, Double
Jeopardy: Persons With Mental Illnesses in the
Criminal Justice System, report to Congress,
Washington, DC: Center for Mental Health Services,
1995.
12. Plum, T.B., and S. Lawther, “How Michigan
Established a Highly Effective Statewide CommunityBased Program for Persons With Serious and
Persistent Mental Illness,” Outlook (July–August–
September 1992): 2–5.

13. Ibid.
14. See Dvoskin, J.A., and H.J. Steadman, “Using
Intensive Case Management to Reduce Violence by
Mentally Ill Persons in the Community,” Hospital and
Community Psychiatry 45(7)(1994): 679–684 for a
review of the New York, Texas, and British Columbia
studies.

167

Communicable Diseases in Inmates:
Public Health Opportunities
Jonathan Shuter, M.D.

Overview
At midyear 1997, more than 1.7 million people, or
1 of every 155 U.S. residents, were in either jail
or prison. At yearend 1997, 1 of every 117 males
and 1 of every 1,852 females in this country were
sentenced prisoners under State or Federal
criminal jurisdiction.1 Fifteen million arrests are
made annually,2 and more than 10 million
individuals are released from detention each year.
Approximately two-thirds of incarcerated
individuals are in State and Federal facilities, and
the remaining one-third are in local, generally
short-term-stay jails.3 Any discussion of the
public health implications of prisoners in this
country must pay heed to these statistics. The
incarcerated community cannot and must not be
considered a small, separate population with
minimal relevance to the outside community.
People who are currently in the criminal justice
system, those who have been in the past, and
those who are destined to be in the future
comprise a large segment of the overall population of this country, particularly in the urban
centers. Furthermore, the view that physical
separation limits the health threat of prisoners to
the outside community is a dangerous misconception. The number of inmates released into the
community annually4 should dispel this myth, as
should the average length of stay in local jails,
which is often on the order of several days to
several weeks. In a worst-case view these
facilities can serve as places where arrestees go,
acquire and/or transmit infection, and are quickly
released to further spread their infection in the
outside community.5
Although public sentiment in an era of more
restricted health care may resist the idea of
expanding the scope and intensity of medical
services in correctional facilities, the public

health community in this Nation resoundingly
endorses the aggressive diagnosis and treatment
of prisoners as a critical, cost-effective measure
to improve health both inside and outside the
facilities.6 The period of incarceration is a crucial
window of opportunity for health care interventions because prisoners often have little other
interaction with the health care establishment.
The correctional facility offers the additional
benefit of access to this population at a time when
the prisoners’ thinking is not clouded by active
drug use or pressing survival concerns such as the
need for housing or food. The incarcerated men
and women of this country suffer from staggering
rates of communicable diseases. This review will
concentrate on syphilis, gonorrhea, chlamydia,
trichomoniasis, human immunodeficiency virus
(HIV), tuberculosis, and hepatitis B and C. Some
of these diseases are life threatening, some are
short-lived, easily curable infections, and some
are completely asymptomatic. One feature that
all of these conditions have in common is their
tremendous public health impact, whether it
be the massive suffering and costs associated
with HIV infection; the pelvic inflammatory
disease (PID), infertility, and ectopic pregnancies caused by gonorrhea and chlamydia; or the
cirrhosis and hepatocellular carcinoma caused
by viral hepatitis. Another common feature of
all of these infections is the ability of a small
core group of individuals possessing specific
sociodemographic and/or physiologic characteristics to exert a disproportionate force in the
spread of illness through communities.

Theoretic Model
This review’s goal is not to present a detailed
mathematical model of disease transmission
through a community. Sophisticated models
exist that attempt to define the dynamics of

168
communicable diseases within given populations,
and the development of such models have been
the subjects of many articles and texts.7 However,
an understanding of certain parameters that
govern the spread of infections through a population is vital to the selection of appropriate
interventions to halt the spread. The starting point
for most of the mathematical models is the
formula, R0 = bDc, where the terms of the
equation are defined as follows:8
•

•

•

•

R0 is the reproductive rate of the infection,
and is defined as the mean number of
secondary cases of infection generated by a
primary case in a susceptible population. It is
a fundamental principle of these models that a
disease can only survive over time in society
when R0 >1. In other words, a disease for
which an average of less than one secondary
case is generated from each primary case will
disappear over time within the population.
b is the probability of transmission of disease
from an index case to a new contact. There
are many sociobiologic parameters that may
influence this variable, such as immunity
against the pathogen, cofactors of disease
transmission, host susceptibility to infection,
preventive measures designed to interrupt
transmission, etc.
D is the duration of infectiousness. Factors
such as the natural history of the disease, the
immune status of the infected individual,
timeliness of diagnosis (which depends, in
turn, on access to care and level of symptoms)
and treatment (if the disease is treatable), and
mortality rate of infected persons determine
the value of this variable.
c is the appropriately averaged number of new
contacts per unit time. As discussed later,
there are situations in which the relationship
of c to R0 are not linear but exponential.9
Furthermore, for diseases that are vaccine
preventable, c may be modulated downward
by protective immunity, and may better be
defined as the appropriately averaged number
of susceptible new contacts per unit time.

A related concept that is crucial to understanding
the epidemiology of the infections to be discussed
is that the influence on disease transmission
through a community is not evenly distributed
among all infected individuals. An HIV-infected,
former injection drug user (IDU) who is in a
strictly monogamous relationship and uses an
effective means of birth control is unlikely to
infect more than one person with HIV and is of
lesser public health import than an active IDU
supporting his or her habit through prostitution.
The concept of a “core group” of highly sexually
active “supertransmitters” of disease is widely
accepted. The dramatic impact and costeffectiveness of programs aimed at removing
individuals from the core group have been well
validated in mathematical models and in realworld studies.10
This review will discuss the epidemiology and
public health implications of specific disease
states in the incarcerated population.

Nonviral Sexually Transmitted Diseases
Epidemiology
Syphilis. Of the nonviral sexually transmitted
diseases (STDs), syphilis has received the most
attention for a variety of reasons:
•

Of the nonviral STDs, syphilis is most closely
associated with HIV acquisition and
transmission.11

•

The long-term sequelae of inadequately
treated or untreated syphilis are more feared
than those of other STDs.

•

Of the nonviral sexually transmitted
pathogens, the vertical transmission of
Treponema pallidum is associated with the
most serious outcomes.

•

The characteristics of diagnostic tests for
syphilis lend themselves to rapid screening and treatment that are ideal for the
correctional setting.

169
In a landmark study of STDs in correctional
facilities published by Hammett et al.,12 a review
of syphilis serologies in 23 different correctional
systems employing routine screening of all
inmates (who did not refuse testing) throughout
the Nation revealed a prevalence of seropositivity
of 4.0 percent in a population of more than
200,000 inmates incarcerated in 1993 and 1994.
Rates among females tested were more than triple
the rates among males (9.9 versus 2.9 percent,
P<0.001). Rates were highest in the Northeast,
Middle Atlantic, and South. A recent unpublished
report by the same author estimates that in 1997,
there were almost 78,000 prison and jail inmates
and almost 558,000 releasees with syphilis
infection.13 In Chicago, cases diagnosed in Cook
County Jail accounted for 22 percent of all newly
diagnosed cases in the city in 1996.14 Similarly,
the Rhode Island prison system housed 39 percent
of the individuals newly diagnosed with syphilis
in that State between 1989 and 1993.15 Female
inmates in the New York City jail system, who
have particularly high rates of many STDs, had a
prevalence of syphilis requiring treatment of 26
percent in a sample of 727 new admissions in
1993,16 and the prevalence in a sample of newly
incarcerated pregnant women was 19 percent in
the same facility in 1996.17
The public health potential of interventions to
reduce the burden of syphilitic infection in the
incarcerated population of this country is great.
In many large cities, control of syphilis in the
correctional system is a crucial component of
citywide control, since the jails and prisons may
house a sizable fraction of all city cases. In this
sense, delivery of prompt and responsible
diagnostic testing and treatment to inmates is
similar to providing these services in municipal
STD clinics. The concentration of syphilis among
inner-city crack-addicted minority women, who
often trade sex for drugs or money, has received
much attention in recent years.18 Failure to treat
these women properly has been associated with a
rise in congenital syphilis cases in New York,19
and newly instituted initiatives to improve
treatment have resulted in a decline in numbers
of infants requiring treatment for congenital
syphilis.20 Although crack-addicted prostitutes are

a difficult patient population to deliver ongoing
medical care to, interventions aimed at changing
the risk behaviors of prostitutes have reduced
rates of STDs and HIV transmission in other
countries.21
In response to the reemergence of syphilis,
including congenital syphilis, as an urban scourge
with a predilection for drug-addicted, minority
women, New York City and Chicago initiated
innovative programs to better diagnose and treat
syphilis in incarcerated females. Both cities
instituted a computer link between the correctional system and the city department of health
syphilis registry, and performed the Stat rapid
plasma reagin (RPR) test on all female admissions
to the system. The Stat RPR test yields results
within 15 minutes, a characteristic that is crucial
in correctional systems where mean lengths of
stay are on the order of days. New arrestees were
generally kept in the admission area until the test
results were available and were offered treatment
according to Centers for Disease Control and
Prevention (CDC) recommendations before being
housed. In the Chicago jail system, women who
were seropositive for syphilis and required
treatment were twice as likely to receive treatment
before release than women who were diagnosed
using conventional testing with its attendant 3- to
5-day delay in treatment.22 A similar program in
New York City also led to substantial increases in
rates of women receiving therapy (as compared to
historical controls), and was accomplished with
a startup cost of $8,300 and a per test cost
(including quality controls but excluding labor
costs) of $0.25.23
Despite the availability of fairly inexpensive
diagnostic and treatment modalities, and the
broad support of the medical and public health
community for aggressive screening and treatment of syphilis in the correctional setting, the
existing state of affairs is extremely disappointing. In a CDC survey of city and county
jails throughout the country, less than one-half
(46–47 percent) offered routine screening for
syphilis as a matter of policy.24 Facilities boasting
the most aggressive screening policies actually
screened less than one-half of arrestees (48

170
percent). Thus, on average, less than one-quarter
of arrestees were tested for syphilis during their
incarceration. In those jails offering testing only
to patients with suggestive symptoms or signs, a
dismal 2–7 percent of inmates were actually
tested.

based on amplification of microbial genetic
material via the ligase chain reaction (LCR) holds
great promise for the future. They are highly
sensitive and specific tests that can be performed
on urine specimens.28 At this time, however, the
tests are slow and costly.

Gonorrhea. Although generally less prevalent
than syphilis in the incarcerated population,
gonorrhea is a significant pathogen among
prisoners in this country, particularly in younger
inmates. Like the other nonviral STDs, Neisseria
gonorrhea is an important organism both by
virtue of its own pathogenicity and because of the
company it keeps. Gonorrhea is a disease with
significant morbidity including painful urethritis;
cervicitis; proctitis; epididymitis; pharyngitis; and,
in its disseminated form, tenosynovitis, arthritis,
and occasionally, endocarditis. It is often involved
in the development of PID and can be transmitted
vertically to the newborn causing ophthalmia
neonatorum. It is one of the most easily transmitted of the sexually transmitted pathogens with
the likelihood of male-to-female transmission of
approximately 50–90 percent and the corresponding figure for female-to-male transmission of
20–80 percent.25 Coinfection with N. gonorrhea
facilitates the transmission of HIV,26 and infection
with N. gonorrhea may render an individual more
susceptible to HIV infection.27

There is less information available about rates of
gonorrhea in jails and prisons than about syphilis.
Few correctional facilities incorporate routine
screening for gonorrhea into standard practice.
The study by Hammett and colleagues that
collected information from correctional facilities
in 11 States found that 2.5 percent of 80,825
inmates undergoing routine screening were
infected with N. gonorrhea.29 Gender-specific
data in their survey revealed an overall prevalence
of 3.3 percent among women and 2.0 percent
among men (P <0.001). In their review of 1997
data, Hammett, Harmon, and Rhodes estimated
that almost 18,000 prisoners and almost 77,000
releasees were infected with gonorrhea, and
female prevalence rates were 75 percent higher
than male prevalence rates.30 The disease is more
common among adolescents, with prevalences as
high as 18 percent among females and 5 percent
among males.31 In an unpublished study of
universal gonorrhea screening in the Chicago jail
system from 1995 that involved more than 81,000
facility admissions, 1.5 percent of men and 4.3
percent of women were infected.32 In the New
York City jail system, the prevalence of gonorrhea was 8 percent in new female arrestees in
1988.33

Several highly reliable testing methods are
available for the diagnosis of gonorrhea. The
gold standard of culture on Thayer-Martin
medium is available through most institutional,
governmental, and commercial microbiology
laboratories. Although technically simple to
perform, the test requires pelvic examination for
females, urethral swabbing for males, and at least
24–48 hours of incubation time in the laboratory.
Another widely used technique involves direct
probing of clinical specimens for gonococcal
genetic material. While this method obviates the
need for incubation, it is not a rapid test in the
sense of yielding results within minutes in the
clinic setting. The genetic probe assays suffer
from some loss of sensitivity when compared to
culture, and they also require pelvic examination
or urethral swabbing. A new generation of tests

The potential utility of aggressive interventions
to control gonorrhea rates has not been as well
studied as it has for syphilis. Screening and
treatment programs involving prostitutes in the
Philippines in the 1960s and selective mass
screening and treatment in Greenland during the
same decade were effective in decreasing the
prevalence of infection in these populations.34
In the Philippines, the decreased rates among
prostitutes resulted in a decreased incidence of
gonorrhea in locally stationed U.S. military
personnel. Both of these studies demonstrated a
failure to sustain benefit after the programs were
terminated.35 It is likely that gonorrhea control

171
efforts would be more successful today with the
availability of more effective oral treatments, less
cumbersome diagnostic techniques, and the
greater social acceptability of condom usage. The
tremendous potential of mass screening and
treatment programs to reduce rates of gonorrhea,
particularly those aimed at core group members,
has been hailed by public health authorities in the
United States for more than 20 years.36 The
overall impact of such programs would be
compounded greatly today by the reduction in
HIV transmission effected by gonorrhea
eradication.
Chlamydia. The appreciation of the importance
of Chlamydia trachomatis as a sexually
transmitted pathogen is a recent development
when compared to the former two organisms.
This, combined with the relatively cumbersome
nature of chlamydia culture is responsible for the
scarcity of information regarding the prevalence
of the disease in prisoners. Like gonorrhea, it is
associated with a range of disease presentations in
men, women, and infants infected by vertical
transmission. It is more likely than gonorrhea to
cause asymptomatic or paucisymptomatic
infections,37 and the duration of carriage in
untreated patients is longer than that for N.
gonorrhea. It also has been implicated as a
cofactor in the transmission and acquisition of
HIV.38
Clinicians may diagnose chlamydia through a
variety of techniques. The gold standard is
McCoy cell culture of a cervical or urethral swab,
which is a costly and time-consuming tissue
culture procedure. Tests that probe clinical
specimens for chlamydial genetic material also
are available, either alone or in combination kits
with probes that react with N. gonorrhea. These
tests are highly specific but their sensitivity is
variable. While more convenient than tissue
culture for the clinical laboratory, these are not
rapid tests and they are fairly expensive. Finally,
LCR tests can be performed on urine samples, but
this promising technique suffers from the same
shortcomings in diagnosing chlamydia as it does
for the diagnosis of gonorrhea.39 Because the
organism is relatively difficult to isolate for

definitive diagnosis and because untreated
chlamydial infection may be quite destructive
without causing symptoms, public health agencies
have endorsed the use of empiric therapy in
certain highly selected populations. Because
patients with gonorrhea have a high rate of
coinfection with chlamydia, gonorrhea patients
are generally treated for both diseases.40 Patients
with nongonococcal urethritis are generally
treated for chlamydia, and many correctional
facilities treat men with leukocyte esterase
activity on urinalysis for gonorrhea and
chlamydia.41 Finally, patients with PID and
patients seeking assistance for infertility are
generally treated for chlamydia because of the
pathogen’s frequent involvement in these
conditions.
The review of Hammett and colleagues found a
prevalence of 2.6 percent among women and 3.3
percent among men (2,379 women in four States
were studied, and only 30 men) in facilities that
screened routinely for chlamydia.42 Hammett’s
unpublished report incorporating data from 1997
estimated that almost 43,000 inmates and almost
186,000 releasees had chlamydia infection during
that year.43 The diagnostic methodology was not
described. One study in the New York City jail
system found a 27 percent prevalence of active
chlamydia infection among adult women admitted
to the facility in 1988.44 The authors of this study
concluded that rates such as these may justify a
program of empiric treatment for all women
admitted to the facility. A troubling finding has
been the high prevalence of chlamydia found in
adolescent prisoners. Male adolescents arrested
in Georgia had a 6.9 percent prevalence of
chlamydia infection on admission,45 and infection
rates as high as 30 percent in female adolescents
admitted to prison have been reported.46
The public health objectives of chlamydia control
programs are twofold: reducing the incidence of
PID and reducing HIV transmission/acquisition.
Although neither of these two outcomes has been
studied specifically in an incarcerated population or among prostitutes, a large-scale study of
selective mass chlamydia screening and treatment
was conducted in Washington State between 1990

172
and 1992. Women who admitted to a risk
behavior associated with chlamydia infection
were randomly assigned to a screening program
or usual care. Those women who were assigned to
the screening group were more likely to receive
treatment and significantly less likely to develop
PID during the specified followup period.47 Such
programs are justifiable not only in terms of
reductions in personal suffering but also in terms
of cost savings.48 Although STD control programs
have been effective in reducing rates of HIV
transmission, the specific contribution of
chlamydia control to these effects has not been
studied.
Trichomoniasis. Trichomonas vaginalis is
a pathogen that causes vaginitis, cervicitis,
urethritis (in both sexes), and dyspareunia and
is associated with poor pregnancy outcomes
and vertical infection of newborns. It is also a
cofactor in HIV transmission/acquisition,49 and
may be a cofactor in the development of PID.50
Until recently, direct culture of the organism was
not widely available in clinical laboratories.
Therefore, the epidemiology of trichomoniasis in
various populations has relied on relatively
insensitive tests such as Pap smears and direct
microscopy of cervical wet preps. The few data
that exist on prevalence of trichomoniasis in
incarcerated populations suggest that it may be
the most common of all the nonviral STDs51 and
the availability of simple, reliable, inexpensive
culture kits for the testing of cervical/vaginal
swabs in females and centrifuged urine specimens
in males will allow better definition of the
epidemiology of this infection in correctional
facilities in the future.
Three studies in the Northeast have demonstrated
astoundingly high rates of trichomoniasis among
female inmates. A sample of female detainees in
the Rhode Island correctional system between
1987 and 1992 revealed a rate of trichomoniasis
on Pap smear of 43 percent.52 In an unpublished
study of new female admissions to a large New
York City jail in 1991, direct culture was positive
for T. vaginalis in 47 percent.53 In a more recent
study conducted in the same facility, newly

arrested pregnant women had an identical
prevalence of 47 percent on direct culture using
the newly available InPouch TV culture system.54
In the latter two studies, all women were also
screened for syphilis, gonorrhea, and chlamydia,
and the prevalence of trichomoniasis exceeded the
prevalences of all of these other STDs combined.
The prevalence of trichomoniasis in male inmates
has not been studied, but the medical community
has recently begun to appreciate the importance
of T. vaginalis as a cause of nongonococcal
urethritis in men.55
No formal studies have been done of the public
health benefit of screening and treatment interventions for trichomoniasis in incarcerated
populations. A recently published editorial
supports instituting routine screening for this
extraordinarily common pathogen in correctional facilities.56 In groups of individuals with
prevalences of trichomoniasis approaching onehalf of the overall population, it would also be
reasonable to explore the role of presumptive
therapy of the disease.

Potential interventions
The aforementioned statistics make a persuasive
case that the Nation’s jails and prisons are crucial
targets for establishing better STD control in the
community. Although the public health community applauds the concept of better directing
STD control programs toward prisoners, the most
recent report of the United States Public Health
Service has shown existing programs to be woefully inadequate.57 Although not all prisoners
belong to the STD core group that must be a
primary target of any sensible STD control policy,
jails and prisons house a population among whom
core group members are grossly overrepresented.
Many of these individuals are relatively or
completely asymptomatic and do not obtain
routine medical care in the outside community.
STD-reduction programs should focus on the
elements of the mathematical model described
above: reducing the likelihood of disease
transmission per contact (b), reducing the
duration of infectivity (D), and reducing the mean
number of new contacts per unit of time (c).

173
Reducing the likelihood of transmission
per contact. The ultimate method of reducing the
likelihood of transmission of an STD per contact
is by curing the STD, but treatment/cure is
subsumed under variable D in the model. The
variable b, in the present discussion, assumes
that the individual is still actively infected (i.e.,
screening/treatment programs have failed to cure
the patient) or the patient has become reinfected.
The best method available to reduce the
likelihood of transmission per sexual contact is
the use of barrier protection with male and/or
female condoms. There is no question that the
consistent use of barrier protection reduces the
rate of transmission of the nonviral STDs as well
as HIV.58 Even inconsistent use of condoms
affords some level of protection. The great
challenge is to make condoms socially acceptable,
and to empower individuals, particularly women,
to insist on their consistent use with all sexual
partners. While such ideas are simple in theory, in
reality the issue of insistence on condom usage is
complicated by a multitude of behavioral and
social factors including embarrassment, fear of
loss of relationship, and fear of emotional or
physical victimization.59 Notwithstanding these
issues, harm-reduction programs stressing
education and behavior modification have been
effective in increasing condom usage in inner-city
populations.60 These efforts are aided by greater
societal acceptance of condoms as a consequence
of public health statements, media awareness, and
advertisements. Obviously, the cost of condoms
must not be prohibitive, and ideally they should
be available to these target populations free of
charge.
Behavior-modification and harm-reduction
research has consistently observed that multiplesession educational interventions are far more
effective at curbing risk behaviors than singlesession interventions.61 The ideal approach to
reducing b would include multiple culturally
appropriate educational sessions led by peer
counselors who teach the many dangers of unsafe
sexual practices, the importance and proper use of
barrier protection, and empowerment techniques
to encourage safer sexual practices even under
adverse social circumstances. Interventions begun

in correctional facilities would be linked to harmreduction programs in the outside community;
would incorporate drug rehabilitation; and would
address housing needs, job training, and ongoing
medical concerns.62 Such programs, while
expensive, would offer the hope of controlling
multiple factors that drive STD transmission in a
community. Simultaneous reductions in risk of
transmission, rate of partner exchange, and
duration of infectivity would have a multiplicative
effect in reducing the reproductive force of these
infections in the population.
Reducing the duration of infectiousness.
Significant reductions in duration of infectiousness are the most readily achievable of all the
goals described. Any effort at reducing duration
of infectivity in the inmate population must rest
upon timely screening and prompt treatment.
Screening and treatment programs in correctional
facilities should be coordinated closely with local
health departments for the purposes of oversight,
contact tracing, reporting, and recordkeeping. The
following screening and treatment methods are
proposed for the specified nonviral STDs.
Syphilis. There is persuasive evidence that
correctional facilities, at least in major cities,
house a substantial fraction of all syphilis cases in
their regions. There is also evidence that rapid
screening and treatment can be accomplished
inexpensively in the jail and prison settings, and
that these programs dramatically increase rates of
appropriate treatment delivery.63 Finally, evidence
suggests that a pilot program of this sort has
reduced the overall syphilis burden in at least one
major urban center.64 For all these reasons, a Stat
RPR test (or its functional equivalent) should be
performed on all new admissions to jails and
prisons in the Nation and inmates should remain
in the clinical area until results are available so
that immediate treatment according to CDC
guidelines can be administered. These efforts
should be closely coordinated with the local
public health agencies. All inmates found to be
seropositive for syphilis should be referred for
immediate HIV testing (unless they are already
known to be HIV infected) and for intensive
harm-reduction training. Routine screening may

174
be discontinued in facilities or regions where the
prevalence of syphilis is so low that it is not a
significant public health concern. In areas where
screening is discontinued, syphilis prevalence
should be measured periodically in order to detect
increases.
Gonorrhea. Every correctional facility in the
country should establish the baseline rate of
gonorrhea in new arrestees. Direct culture, genetic
probe assays, or LCR may be used as diagnostic
modalities. The latter test, while costly, has the
advantage of higher acceptance rates, particularly
among males, because urethral swabbing is not
necessary. Males who refuse these tests should be
screened for urine leukocyte esterase activity. All
inmates diagnosed with gonorrhea (including
males who are urine leukocyte esterase positive)
should receive single-dose oral therapy for the
infection according to CDC guidelines and should
be referred for immediate HIV testing and
intensive harm-reduction training. Correctional
facilities with very low rates of gonorrhea may
elect to restrict screening to high-risk groups such
as adolescents and prostitutes, as well as inmates
with symptoms or signs suggestive of gonorrhea.
Communities with low prevalences of gonorrhea
should institute routine screening in correctional
facilities when significant increases in incidence
are detected in the community or during periodic
screening in the local jails or prisons. All other
facilities should institute the practice of routine
screening of new admissions. Testing and
treatment should be offered in the most
expeditious manner possible.
Chlamydia. The morbidity and societal costs
associated with chlamydial disease in terms of
acute symptomatic infection, PID, ectopic
pregnancy, infertility, and amplified HIV
transmission/acquisition are so great that broad
screening of sexually active females is widely
supported.65 If such a measure is considered cost
effective in the general community, it is certainly
indicated in correctional facilities where rates
are higher and core group members are overrepresented. Every correctional facility in the
Nation should screen new admissions for

chlamydial infection. Until the LCR is adapted
for economical, quick mass screening, women
should be tested with one of the widely available
genetic probe kits and males should be tested for
leukocyte esterase activity in urine samples.
Inmates testing positive for chlamydia infection
should receive single-dose therapy with azithromycin and should be referred for intensive harmreduction training and immediate HIV testing.
These programs should be coordinated with the
local public health authorities. Facilities in which
the entire inmate population or identifiable
subsegments thereof demonstrate chlamydia
prevalence greater than 20 percent should
consider empiric treatment without diagnostic
screening of these groups immediately upon
admission.
Trichomoniasis. The medical community is just
beginning to understand the importance of T.
vaginalis in prisoners. The few studies available
suggest that it is the most prevalent of the nonviral STDs in females.66 Its prevalence in male
inmates remains undefined. Correctional facilities
throughout the country should conduct studies to
define the prevalence of trichomoniasis in their
locales using inexpensive culture kits such as the
InPouch TV for testing cervicovaginal specimens in female inmates and centrifuged urine
specimens in males. Inmates who are culture
positive for T. vaginalis should receive singledose therapy with metronidazole, and should be
referred for immediate HIV testing and intensive
harm-reduction training. For populations with
very high rates of trichomoniasis, the advisability
of empiric therapy without screening should be
considered in a cost-benefit model.
Reducing the mean number of new contacts
per unit of time. The rate of partner exchange
may be the most important of the variables in the
mathematical model. It is not simply an arithmetic
mean of new partners per unit of time across the
community, but also incorporates a measure of
variance that is related to c exponentially. Community members who have a substantially higher
rate of partner exchange than the remainder of the
community affect the reproductive force (R0) of

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STDs exponentially and produce an effect that is
far out of proportion to their numbers.67

Human Immunodeficiency Virus

For the purpose of the present discussion, it
would be best to divide nonmonogamous inmates
into two groups, those who trade sex as a
commodity for drugs or money (i.e., prostitutes)
and those who do not. There is evidence that
educational interventions that heighten awareness
regarding the dangers of having sexual contact
with numerous partners may be effective in innercity populations.68 Culturally appropriate
messages delivered by respected personalities and
peers are the most likely to be effective.69 Even
among nonprostitutes, efforts to encourage
moderation in the use of alcohol and other drugs
should go hand-in-hand with discussions of
sexual practices. As with all attempts at behavior
modification, ongoing reinforcement of the
message through media campaigns, ongoing
group sessions, and advertisements are the most
likely to have a lasting impact. For inmates who
rely on sex as
a means of income, the problem is more complicated. The complex and tragic interplay of
drug use, prostitution, nonviral STDs, and HIV
in inner-city minority women is well
established.70 Efforts to control these processes
must hinge on drug rehabilitation programs, and
correctional facilities are a reasonable target for
resources committed to these pursuits.

HIV, the pathogen that causes acquired
immunodeficiency syndrome (AIDS), is
responsible for perhaps the most significant
epidemic of our era. From the time that the virus
first penetrated urban communities in the late
1970s it has caused an epidemic in continuous
evolution. Beginning in the early 1980s, when
AIDS was first described by the medical
community, it involved primarily men who had
sex with men.72 Almost from the outset, the
involvement of IDUs and their heterosexual
partners in the epidemic was recognized.73 The
two decades of the epidemic have witnessed some
of modern medicine’s greatest victories and its
most abysmal failures. In the United States as a
whole, AIDS is becoming an endemic rather than
an epidemic disease,74 and antiretroviral therapy
allows infected patients to live longer and better
with a new-found hope of prolonged survival.75
Mortality rates from AIDS have dropped dramatically.76 At the same time, HIV infection is
decimating the populations of many third world
countries that lack the resources to treat the
afflicted. There are also populations within this
country that are being ravaged even as the overall
effect levels off in the Nation as a whole. In the
early days of the epidemic, females constituted a
very small fraction of those infected. In the 1990s,
as the epidemic slowed in the male homosexual
and bisexual population, an alarming trend of
steadily increasing incidence among women was
noted. AIDS case rates are increasing in women,
particularly urban women belonging to ethnic
minority groups, more rapidly than any other
major demographic category.77 The HIV epidemic
in the United States today is being driven by IDUs
and their sexual partners.78 In certain neighborhoods of cities in this country cumulative
AIDS case rates exceed 5 percent of the entire
population and a great many more are infected
with HIV but have not developed AIDS.79 Persuasive evidence that in some, if not most, of the
major urban epicenters of HIV in this country,
the jails and prisons represent epicenters within
epicenters.80

Furthermore, society should not give up on those
individuals who continue to engage in prostitution
and drug use. Legal and educational interventions
have been highly effective in reducing rates of
STDs and HIV among prostitutes and their clients
and have proven successful in active IDUs.71
Harm-reduction programs in correctional facilities
should teach inmates who are active drug users
and prostitutes how to mitigate the health risks
that are inherent in their practices. Limitations
on the practice of prostitution through mass
educational and legal interventions aimed at prostitutes and their clients also play an important role
in reducing rates of partner exchange.

Epidemiology

176
Data are available from U.S. correctional facilities
in the 1990s to define the extent of HIV infection
and AIDS within the inmate population. Many,
probably most, inmates with HIV infection are
not aware of their diagnosis and are relatively
asymptomatic. Therefore, the most legitimate
method for defining the prevalence of HIV infection in prisoners is blinded serologic testing or
mandatory universal testing. Both of these
methods have been employed in jurisdictions
throughout the United States.81 Inmates with
AIDS, the advanced stage of HIV infection characterized by severe immune system dysfunction,
come to the attention of public health agencies
because AIDS is a reportable disease throughout
the country. Although individuals with AIDS
consume a larger share of health cost resources
per capita and they have been at the center of
legal and ethical controversies surrounding such
issues as adequate treatment, segregation,
quarantine, and compassionate release, they are
probably a less significant threat to the public
health than asymptomatic, undiagnosed, HIVinfected prisoners. As with all STDs, asymptomatic infectious individuals who remain
undiagnosed comprise the segment of the core
group that is most likely to infect numerous
partners.82 Studies investigating HIV seroprevalence provide the best reflection of this
group in correctional facilities.
Facilitywide HIV seroprevalence studies. The
review by Hammett and colleagues.83 summarizes
the findings of mandatory and blinded HIV testing
from jails and prisons in 32 States from 1985 to
1994. Prevalences of HIV infection ranged from
0 to 25.6 percent (the latter among women in
New York City). States with prevalences of HIV
among prisoners exceeding 5 percent were New
York, New Jersey, Massachusetts, Florida, and
Illinois. Although HIV infection in the United
States is a disease predominantly of men, in jails
and prisons, particularly in the Northeast, rates
among female inmates are higher. This observation is related to the high rate of drug use
among female arrestees and the intersecting
epidemics of crack use, syphilis, and HIV in
urban minority women.84

Voluntary HIV testing studies. Testing for
HIV in response to the inmate’s request is the
prevalent system for HIV testing in the Nation’s
correctional facilities. This system has advantages
and disadvantages. The advantages are that it
respects prisoner autonomy, it most closely
resembles what occurs in the outside community,
and results are useful to the individual patient (in
contrast to blinded serosurveys) and may be
useful in estimating overall facility prevalences.
The disadvantages are that voluntary testing
programs generally fail to test inmates who do not
actively seek out testing, thus missing a sizable
and important population. Furthermore, aggregate
results of such programs may underestimate
actual prevalences because individuals who are
less likely to be infected are more likely to
volunteer for testing.85 Voluntary testing programs, which are the most common testing
strategy in correctional facilities throughout the
Nation, have been useful for individual HIV
diagnoses, but have been a public health failure of
the first order because the numbers of inmates
availing themselves of the testing services have
fallen far short of the ideal.
AIDS prevalence studies. In 1994, a survey of
47 State and Federal prison systems revealed
4,827 cases of AIDS among prisoners with
institutional prevalences ranging from 0 to 2.4
percent.86 By the end of that year, 4,588
individuals in the United States had died of AIDS
while behind bars representing 2 percent of all
AIDS-related deaths in the Nation. Inmates in the
New York and New Jersey correctional systems
bore the greatest brunt of this fatal epidemic.
Hammett, Harmon, and Rhodes estimate that
8,900 prison and jail inmates had AIDS in 1997
representing 4 percent of those living with AIDS
in the United States. Moreover, they estimate that
17 percent of those living with AIDS in this
country passed through a correctional facility at
some point during the year. According to their
mathematical model there were three to four HIVinfected inmates without AIDS for every one with
AIDS.87

177

Theoretic model
Although the forces that govern the spread of the
nonviral STDs through a community—likelihood
of transmission per contact (b), duration of
infectivity (D), and average rate of new partner
acquisition (c)—also apply to HIV infection,
a number of sociological and physiological
distinctions complicate efforts at HIV control
in the community. Important sociological differences include the following:
•

In most cases, testing for HIV requires an
informed consent and counseling process that
is unique among STDs.

•

Information pertaining to individual HIV
status requires a higher level of
confidentiality than that for other STDs.

•

HIV-infected individuals are subject to
stigmatization and discrimination to an extent
unrivaled by other STDs.

•

Medications used to treat HIV infection are
extremely expensive.

•

The Nation’s populace and Government
recognize HIV as a problem of major
importance.

Important physiologic differences include the
following:
•

HIV causes an incurable illness.

•

The natural history of untreated HIV infection
in most patients eventuates in death.

•

HIV infection is transmitted not only
sexually, but also by contact with infected
blood, most commonly in the context of
injection drug use.

•

All effective treatments for HIV require
lengthy, perhaps lifelong, medication
administration.

•

When antiretroviral medications (the
medications used to control HIV infection)

are used improperly, the virus has the
capacity to develop resistance quickly. This
resistance is genetically stable and can be
transmitted to new cases throughout the
community.88
•

Because HIV is incurable, patients cannot
move in and out of the infected pool of
individuals within a community. They are
either once and always infected or not yet
infected.

These differences complicate the mathematical
modeling of the epidemic in the community.
Whereas β is easily reduced to zero for the nonviral STDs through the use of curative antimicrobial agents, it is not clear that β can ever
be zero for an HIV-infected patient. Reliance,
therefore, on partially effective means such as
condom use, bleach disinfection of needles,
treatment of transmission cofactors (such as
other STDs), and antiretroviral treatment is
necessary to modulate the likelihood of transmission downward. In marked contrast to the
curable STDs, effective treatment of HIV has the
paradoxical effect of increasing D by prolonging
the life and thus the period of contagion of each
infected individual. Similarly, c may increase
with effective treatment as a result of an increased
sense of well-being and a societal view that HIV
is now a treatable illness. These harmful trends
are likely outweighed by a probable decrease in
communicability of infection from effectively
treated patients.
The final physiological difference of HIV infection listed above deserves emphasis. With the
curable STDs, individuals can move in and out of
the infected and uninfected populations many
times, whereas individuals from the HIVuninfected population can enter the HIV-infected
population but cannot exit it while still alive.
From a strictly mathematical standpoint, one can
counterbalance the effect of a single new gonorrhea infection in a prostitute by diagnosing and
curing a case of gonorrhea in another prostitute.
With HIV, however, there is no easy or inexpensive way of neutralizing the community
health impact of new cases of infection. It is

178
clearly less expensive in terms of both human
suffering and actual dollars to prevent new cases
of HIV than to manage them effectively. This
reality has led to public health policies that
concentrate not only on infected individuals but
also on the segment of the population that is not
yet infected, especially those who are at increased
risk.
Because the mathematical model employed in
the section on the nonviral STDs is rendered
cumbersome by the distinctive properties of the
HIV epidemic, the ensuing discussion will be
structured according to the four main categories
of HIV control interventions and will comment on
the merits and limitations of each within the
correctional setting: (1) HIV testing services, (2)
harm-reduction training, (3) treatment of HIV
disease, and (4) diagnosis and treatment of other
STDs.
HIV testing. HIV counseling and testing services
are a major component of HIV control efforts in
the Nation.89 In theory, the advantages of broad or
universal testing for this illness in prisoners are
great. The wide use of an inexpensive and highly
reliable test would identify those inmates infected
with HIV, allowing them the best possible
opportunity for early treatment and offering past,
present, and future partners a chance at early
diagnosis or avoidance of disease acquisition.
Testing pregnant inmates would allow for early
treatment of mothers while dramatically improving the outlook for their children.90 Inmates
testing negative for HIV antibodies could receive
reassurance about their infection status together
with aggressive harm-reduction counseling.
Reality diverges markedly from this ideal
scenario. Although most facilities offer HIV
counseling and testing services,91 they are
generally staffed only to process the small number
of prisoners requesting their services or referred
by physicians for specific reasons. Attendance at
testing sites is generally limited by the movement
constraints that govern all activities within jails
and prisons and by discrimination from staff
and other prisoners who are aware of testing
appointments. Prisoners considering testing may
defer it for a variety of reasons including

misunderstanding, lack of interest, inconvenience,
fear of positive test results, breaches in confidentiality, and possible discrimination if diagnosed
as HIV infected.92 Although the effects of discrimination are difficult to define in a quantitative
sense, inmates with HIV infection often suffer
from discrimination at the hands of correctional
officers and other inmates. Screening programs in
correctional facilities, particularly jails, function
at maximum efficiency when they are a part of the
intake process93 because inmates who are already
housed may be occupied with their daily routines,
legal proceedings, anticipated release dates, and
family visits and may not wish to disrupt these
activities with multihour excursions to counseling and testing sites. At Rikers Island, a jail with
an organized, full-time staff of HIV counselors/
testers, but without HIV testing services incorporated into the intake process, approximately twothirds of the most crucial, high-risk populations
(e.g., pregnant women, men who have sex with
men) complete their incarceration without having
had their HIV status determined.94 It is likely that
facilities that are less attuned to the problem of
HIV perform even more poorly. Unless existing
practices undergo a dramatic change, pregnant
prisoners in the United States will fail to meet the
Government’s goal of 95 percent prenatal HIV
testing for the year 200095 in a most dismal way.
This tragedy is compounded by the reality that
incarcerated pregnant women are arguably the
segment of the population in greatest need of
these diagnostic initiatives. On a more positive
note, correctional facilities in Maryland and
Wisconsin have achieved 47–83 percent testing
rates for new inmates after incorporating a
convenient counseling and testing session into the
intake procedure.96 These programs are a highly
cost-effective means of preventing new HIV
infections in the community, with one new case
of HIV infection averted for every five cases
newly diagnosed, according to CDC estimates.97
Reductions in new infections may be even greater
in settings such as jails and prisons where the core
group of supertransmitters is overrepresented.
Voluntary programs for prisoners should attempt
to assuage the main concerns that lead to test
refusal—fear of positive test results and lack of
confidentiality—and should strive to correct the

179
common misperception that prior negative HIV
test results, even those obtained more than 1 year
previously, render repeat testing unnecessary.98
These programs should not write off inmates who
refuse an initial attempt at testing because the
intake period is often a time characterized by
anger, frustration, and drug and alcohol
withdrawal. A number of studies in urban
populations have demonstrated that individuals
who refuse testing have a higher prevalence of
HIV infection than those who accept it.99 Ideally,
screening programs should maintain logs of
inmates who have refused testing and recontact
them periodically during their incarceration.
Prisoners who test HIV seropositive should be
referred for comprehensive care of their illness.
They should be screened for curable STDs and
treated (as indicated), and they should receive
harm-reduction counseling tailored to their
infection status. The success of such efforts in
curbing activities likely to result in HIV transmission has been documented in inner-city
populations.100 Inmates who test negative for HIV
should also receive aggressive counseling as well
as STD screening, because a troubling trend of
increased high-risk behavior in subjects receiving
knowledge of seronegativity has been observed.101
Inmates who refuse testing should, of course,
receive the same range of STD screening and
harm-reduction counseling as those accepting
testing. Within the context of the theoretic
mathematical model, R0= bDc, aggressive HIV
testing programs may directly reduce the level of
infectiousness (b) by encouraging condom usage
and safer needle habits and by referring patients
for effective antiretroviral treatment. The duration of infectiousness, D, may be reduced by
removing certain individuals from the infectious
pool by ending needle sharing or through sexual
abstinence. The average rate of new partner
acquisition, c, could also be reduced as a result of
effective harm-reduction counseling. Although
antiretroviral treatment is a strategy limited to
HIV-infected inmates, the rest of these benefits of
effective HIV testing programs apply to both
HIV-infected and HIV-uninfected prisoners.

Harm-reduction training. The health care
community faces a daunting task in attempting to
provide harm reduction training to inmates of
HIV-positive, HIV-negative, and unknown status.
The majority of correctional facilities in the
United States offer educational material
pertaining to HIV, ranging from printed
information to videotapes to individual and group
counseling sessions.102 The need for and efficacy
of such programs are much more difficult to
define than for HIV treatment programs. There
are, however, some instructive data available.
Two separate studies assessing knowledge levels
of prisoners utilizing a standardized questionnaire
in facilities in Maryland and Pennsylvania found
that the vast majority of participants knew that
HIV may be transmitted by sharing needles or
through sexual contact.103 The knowledge level of
prisoners equaled that of the general population.
There were, however, misperceptions concerning
the risk of contracting HIV through casual contact
and the risk of acquiring HIV during the period of
incarceration. The prisoners tended to exaggerate
the magnitude of these risks. Since levels of drugand sex-related risk behaviors prior to incarceration are very high, it is clear that a rudimentary
knowledge of routes of HIV transmission is
necessary but not sufficient for effective control
of HIV risk behaviors in this population. Harmreduction programs must attempt to reinforce
preexisting awareness of routes of transmission
and correct any misperceptions. Moreover, these
interventions must surpass awareness-level
programs and include risk-reduction skill building
(emphasizing self-empowerment for females).
They should consider the affective dimensions of
risk-reduction behavior change.104 Messages
imparted by peer counselors and respected
members of ethnic minority groups are
particularly effective.105 All programs must
recognize that many inmates on release confront
basic survival needs such as housing and food
requirements, as well as the very powerful
influence of addiction. Because of these many
factors, it is clear that progress in harm reduction
can occur only incrementally and it becomes
obvious why single-encounter educational
interventions have negligible influence. Although

180
few, if any, correctional facilities offer multisession harm-reduction programs to large portions
of their inmate populations, there is reason to
believe that they could be effective. Communitybased harm-reduction programs have been highly
successful in reducing sex- and drug-related risk
behaviors in indigent inner-city populations in
this country including prostitutes and active, outof-treatment IDUs.106 Programs such as these can
simultaneously influence multiple variables from
the theoretical model defining transmission of
HIV through the community. These simultaneous
effects would be expected to reduce HIV transmission exponentially.
Treatment of HIV infection. Newer antiretroviral medications and combinations have
revolutionized the treatment of HIV infection.
When used properly these medications can reduce
levels of virus in the bloodstream to undetectable
levels, improve the quality of life, and prolong
survival, perhaps indefinitely.107 When used
improperly, these complex regimens can promote
the development of drug-resistant viral strains that
can render the patient virtually untreatable and
can doom those individuals infected by the patient
with the mutated virus to an inexorable progression to AIDS and death.108 Jail and prison health
services have an ethical obligation to administer
antiretroviral medications as they would in the
outside community. According to current
recommendations, the vast majority of HIVinfected individuals should receive combination
antiretroviral therapy.109 The proper use of
antiretroviral medications is most likely achieved
under the supervision of providers with expertise
and experience in infectious diseases and HIV
management.110 Testing of T-lymphocyte subsets
and plasma viral load levels must be available in
order to assess the need for and response to
therapy. Provisions must be made for continuing
therapy without interruptions despite court
appearances, intrafacility and interfacility
transfers, punitive detentions, and release from
incarceration. These arrangements require close
coordination with the correctional administration
and the health care community in the surrounding
area. Without aggressive efforts to ensure
followup, high rates of interruption of care are
inevitable.111 Little is known about inmate interest

in such programs or the success of antiretroviral
therapy prescribed behind bars. In 1995, when
enthusiasm originated for combination antiretroviral therapy concurrent with the release of
lamivudine, the number of inmates on Rikers
Island in New York City receiving antiretroviral
therapy quickly tripled and has remained at the
higher level. Patients receiving such therapy on
Rikers Island demonstrated a rise in CD4
lymphocyte counts almost identical to that
reported in controlled trials, suggesting that
compliance in the jail was satisfactory.112 A study
of antiretroviral therapy in 217 prisoners in the
Connecticut correctional system in 1996 found
that among the 101 prisoners who were offered
antiretroviral therapy, 93 percent accepted and 84
percent of these inmates were compliant with
greater than 80 percent of their doses.113 The
belief was prevalent, however, that antiretroviral
medications were harmful if there were illicit
drugs in one’s system. Better antiretroviral
acceptance was associated with nonblack race
and trust in physicians, and better compliance
was associated with male gender and less
complex regimens. Both the New York City
and Connecticut State correctional systems have
experience and expertise in delivering care to
HIV-infected inmates and both employ full-time
infectious disease specialists to supervise HIV
care. These data suggest that effective antiretroviral therapy can be administered in correctional facilities, and that successes achieved in
systems where HIV prevalences are extremely
high could probably be matched at lesser expense
throughout the country. They also suggest that the
correctional facility may be an important site for
initiating antiretroviral therapy in this population
and that HIV management strategies should be
culturally appropriate for black prisoners,
especially women, and should strive to employ
the least complex medication regimens possible.
Several lines of evidence suggest that effective
antiretroviral therapy may decrease b, the
likelihood of HIV transmission per contact.
Reduced levels of HIV in seminal fluid parallel
those in plasma in treated patients, suggesting that
the exposure inoculum of contacts of treated
individuals is lower than that of the untreated.114
Studies of vertical transmission of HIV from
mothers to newborns have shown a direct

181
correlation between maternal viral load and
likelihood of transmission to the infant.115 Finally,
the likelihood of HIV acquisition by health care
workers experiencing needlestick injuries is
related to a number of parameters governing
exposure inocula, including end-stage AIDS in
the source patient, a status generally associated
with a high viral load.116 Administering effective
antiretroviral therapy may produce a number of
indirect benefits to the patients and their
communities by fostering ongoing relationships
with health care providers. Continued contact
with well-organized HIV clinics allows the
regular reinforcement of harm-reduction messages
and allows for social-service interventions that
address substance abuse, economic, and housing
issues in a legal and responsible way. Less
tangible benefits such as the development of a
sense of autonomy and self-determination among
clinic patients, participation in support groups,
and access to the most up-to-date information and
therapy are also important byproducts of a good
HIV treatment program. These effects may
translate into communitywide benefits by further
reducing b as a result of safer sexual and drug
habits, as well as decreasing c, the appropriately
averaged number of new contacts per unit time,
through the behavioral changes produced by
harm-reduction education.
Diagnosis and treatment of nonviral STDs. The
magnitude of the hidden epidemic117 of the
curable STDs in prisoners has been discussed in
prior sections. As mentioned earlier, these diseases, especially syphilis, gonorrhea, chlamydia,
and trichomoniasis, are important not only vis-avis their own morbidities, but also as cofactors
in the transmission and acquisition of HIV.118
Underdeveloped countries without resources to
commit to other aspects of HIV control have
achieved dramatic reductions in HIV rates by
instituting aggressive diagnostic and treatment
measures for these easily curable diseases.119 The
CDC has recently highlighted this strategy as a
key component of HIV control in this country.120
State correctional facilities are currently failing
to capitalize on this important public health
opportunity. Recommendations for better

utilization of screening and treatment programs
for the curable STDs are outlined in a prior
section.

Potential Interventions
HIV testing. Correctional facilities should
incorporate easy, convenient HIV testing into the
intake procedure for all inmates who are not
known to be HIV infected. Testing programs of
this magnitude are accomplished efficiently and
affordably in the U.S. military (approximately
$2.50 per test),121 attesting to their feasibility.
Because pretest counseling sessions and drawing
blood are labor intensive, larger facilities should
consider innovative approaches such as videotape
counseling sessions and fingerstick blood, urine,
or oral samples as testing substrate. Logs of
inmates who refuse testing on intake should be
maintained and these inmates should be recontacted periodically during their incarceration.
Efforts such as these should be particularly
strenuous when they involve critically important
populations such as pregnant women, prostitutes,
active IDUs, and men who have sex with other
men. Results of HIV tests should be confidential
and should be available in a timely fashion.
Facilities should coordinate with local health
departments to ensure delivery of test results
to inmates who have been released from
incarceration prior to test completion.
Harm-reduction training. All correctional
facilities should offer programs with content
aimed at fostering harm-reduction skills including
condom usage and safer injection practices. At a
minimum this can be accomplished with culturally
appropriate printed materials and videotapes.
Programs likely to have greater impact utilizing a
multisession format, peer counselors, and
communications from respected members of the
community should be focused on groups of
inmates at highest risk of acquiring HIV infection
or of transmitting it to others (e.g., inmates with
active STDs, prostitutes, active IDUs). Innovative
approaches such as programs to promote inmates
to the status of peer counselors after satisfactory
completion of curricula should be encouraged.
Funding bodies should authorize studies of the

182
short- and long-term effects of aggressive versus
“standard” harm-reduction interventions in
correctional facilities to evaluate the economic
feasibility of more widespread programs.
Treatment of HIV disease. Prisoners with HIV
infection should receive comprehensive therapy
for the illness. This must include access to
standard diagnostic testing (including T-cell
subsets and plasma viral load measurement) and
all antiretroviral medications. Many regimens
must be taken on a strict schedule and require
dosing on an empty stomach or after a full meal.
Some require free access to fluids. Facilities must
demonstrate flexibility in their generally rigid
meal schedules to accommodate the requirements
of HIV-infected inmates. Furthermore, antiretroviral medications must not be subject to confiscation during searches. Studies have shown that
the outcomes of HIV-infected patients are better
when they are cared for by providers with
expertise in managing HIV infection.122 All
facilities housing HIV-infected individuals should
have access to consultation with an infectiousdiseases or HIV specialist. Facilities with large
numbers of HIV-infected inmates should arrange
for such consultation onsite.
Diagnosis and treatment of the nonviral STDs.
Recommendations may be found in an earlier
section of this paper.

Tuberculosis
Overview
In contrast to other diseases discussed in this
document, the problem of tuberculosis (TB) in
correctional facilities has long been recognized by
the medical establishment, is the subject of
comprehensive guidelines by the major governmental health agencies,123 and has been at the
center of numerous court cases involving
prisoners’ rights.124 Tuberculosis is unique among
the diseases discussed in this paper in that it is
transmitted via an airborne route. The destructive
potential of a single inmate spreading disease in a
poorly ventilated facility by coughing, sneezing,
laughing, and talking is large. Similarly, the
potential of highly contagious prisoners to

transmit disease to numerous individuals in the
community after release from incarceration is
large, particularly if the postrelease destination is
a congregate housing facility such as a homeless
shelter, hospice, hospital, or crack house. A recent
report that 35 percent of new TB cases in a large
urban center in 1992 were attributable to one
individual who infected others in a neighborhood
bar starkly illustrates the need to control every
single contagious case.125
The pathophysiology of TB is distinct enough
from the other diseases to warrant a separate,
detailed discussion. Mycobacterium tuberculosis
is the organism that causes TB. When a patient
with TB coughs or otherwise emits the organism
into the air, it attains a form called a droplet
nucleus that can remain airborne for many hours
and is the proper size to reach deep into the
airways and establish a new infection in an
individual who inspires it. When this occurs, the
organism has the opportunity to multiply in the
lung and disseminate through the body unchecked
for several weeks until a meaningful immune
response develops and contains (but does not
eliminate) the infection. This process is asymptomatic and generally results in the conversion of
the TB skin test, also called the tuberculin test,
Mantoux test, or purified protein derivative (ppd),
from negative to positive. The medical term
referring to this scenario is tuberculosis infection.
Patients with TB infection are not contagious to
others, but are at some risk of developing
symptomatic, progressive disease referred to as
active tuberculosis. Certain factors are associated
with a high risk of progression from TB infection
to active TB. These include recent infection with
the organism (especially within the first 1–2
years), HIV infection or other forms of immunosuppression, diabetes, and a history of
gastrectomy. Many studies have shown that a 6to 12-month course of single-drug therapy with
isoniazid dramatically reduces the risk of
progression to active TB.126 Such treatment is
called tuberculosis preventive therapy. Although
active TB can develop almost anywhere in the
body, the most common site is the lung. Patients
with active TB generally have symptoms and
signs such as cough, sputum production, weight

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loss, night sweats, and fever. At this stage of
disease, most patients have a positive tuberculin
test and an abnormal chest roentgenogram.
Definitive diagnosis rests upon obtaining sputum
(or other anatomic material if the site of disease is
not the lung) for Kinyoun, fluorochrome, or acid
fast bacilli (AFB) staining, Genprobe, and
mycobacterial culture and susceptibility testing.
Kinyoun, fluorochrome, or AFB staining are
simple, rapid, inexpensive techniques that take
advantage of properties of the Mycobacterium
tuberculosis cell wall to detect the organism on
direct microscopic examination of the sputum or
other biologic material. A positive stain is very
suspicious for active TB and generally mandates
separation or isolation from other individuals as
well as antituberculous therapy. Patients with
enough organisms to detect on direct microscopic
examination of the sputum are considered highly
contagious. The diagnosis of TB cannot rest
entirely on sputum smears, however, because
occasional patients with positive smears have
diseases other than active TB and many patients
with active TB have negative smears. The
Genprobe assay is a rapid, fairly expensive test,
licensed for use on smear-positive specimens,
that employs genetic means to verify that
organisms detected on the Kinyoun, fluorochrome, or AFB stains are Mycobacterium
tuberculosis. A negative Genprobe test on a
positive smear specimen casts doubt on the
diagnosis of active TB. This technology represents a significant advance by speeding the
positive diagnosis of active TB from a period of
weeks or months to a single day. Ultimately, the
definitive diagnosis of active TB rests upon the
growth of the organism in culture. Testing of
the organism for resistance to antimicrobial
agents is also accomplished through the culture
technique. Although recent advances have made
culture identification and resistance testing of the
organism faster, these processes generally take
at least several weeks to complete.
Tuberculosis control in a community is a complex
matter and depends mainly on two strategies.
First, and most important, is the rapid isolation
and effective treatment until cure of all patients
with active TB. The second goal is preventing the

progression to active TB in individuals who have
TB infection.
The isolation and treatment of all patients with
active TB requires an organized, proactive, and
thoughtful approach containing the following
elements:
Screening. All new entrants into a community
(whether a nation, hospital workforce, or
correctional facility) should be screened for active
TB. The least expensive system of screening
consists of a review of symptoms and a tuberculin
test. Individuals with positive findings on either
test would undergo further screening. A more
expensive approach that would be less apt to miss
cases of active TB would require universal chest
roentgenography of all new entrants. A middle
ground between these two approaches is also
possible (i.e., roentgenographic screening of all
individuals in high-risk groups such as HIVinfected patients, immigrants from countries with
high rates of active TB, or IDUs). Screening
programs should not be limited to new entrants
into communities. Long-term members of
communities where TB is endemic or epidemic
require similar screening tests on a periodic basis,
generally every 6–12 months. Finally, more
aggressive screening and treatment must be
directed at individuals who have had close contact
with a patient with active TB. Such screening is
often referred to as contact investigation.
Isolation. Individuals with a constellation of
findings upon screening that are suggestive of
active TB must be promptly isolated until they
are deemed noninfectious. Adequate isolation
involves placing the patient into a solitary room
with negative pressure and frequent air exchanges.
Negative pressure refers to air pressure within
the patient’s room. It must be negative to the
outside corridor to prevent the escape of airborne
bacteria into common areas. Air exchanges refer
to the movement of air out of the patient’s room
to the outside of the building (or to elsewhere in
the building after the air has passed through a
high-efficiency particulate air [HEPA] filter).
Ultraviolet light may also be a useful adjunct in
inactivating airborne Mycobacterium tuberculosis

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in a variety of settings. Depending on the rate of
TB in a particular facility, it may be necessary to
maintain isolation rooms onsite, or it may be
appropriate to transfer all patients requiring
isolation to local hospitals. The duration of
isolation is based on the clinical judgment of the
patient’s care providers, and timely release from
isolation depends heavily on the turnaround time
of sputum specimens submitted for microscopic
examination.
Treatment. The vast majority of patients with
active TB are curable with a 6- to 12-month
course of medications. The obvious benefit to the
patient of such treatment is complemented by the
societal benefit of quickly rendering the patient
noninfectious to others. The most important
lesson learned from the TB resurgence of the late
1980s is the critical role that directly observed
therapy plays in achieving acceptable rates of
medication completion. Directly observed therapy
requires that a trained observer watch the patient
ingest each and every dose of medication
prescribed until the course of treatment is
completed. Large studies have demonstrated the
dramatic success of directly observed therapy
programs in several urban centers.127 All patients
with active TB should be encouraged to enroll in
a directly observed therapy program, and in some
settings it should be mandatory.
The second arm of TB control in a community,
TB prevention in patients at risk, is in certain
respects a lesser challenge and in certain respects
greater. It is easier in that patients do not require
expensive isolation rooms, extensive diagnostic
testing, and complex treatment regimens. It is
more difficult, however, in that TB preventive
therapy is indicated for far more individuals, and
often patients who are free of symptoms are
reluctant to commit themselves to 6–12 months of
therapy to mitigate a theoretic risk. The challenge,
therefore, has been to foster a communitywide
understanding of the importance of TB preventive
therapy, and to encourage patient commitment to
long-term medication compliance using such
innovative approaches as voucher systems and
directly observed preventive therapy.

Epidemiology
Tuberculosis has been recognized throughout
the centuries as one of the most feared and destructive scourges known to mankind. Rates of
TB have declined throughout most of this century
as a result of better living and housing conditions
and with the later advent of effective medical
therapy. The United States began compiling
national TB reporting statistics in 1953. After 32
consecutive years of declines, the incidence of TB
rose in 1985. Although the reasons for this
observation were multiple, the HIV epidemic in
the United States was a main contributor to the
upsurge.128 Since 1992, when Federal funding of
State and local TB control programs increased
dramatically, the national incidence of TB has
again fallen to historically low levels.129
Even as the Nation enjoyed declines in TB
incidence between the 1950s and the early
1980s as a consequence of antimycobacterial
pharmacotherapy and decreased urban squalor,
high rates of TB in correctional facilities were
recognized.130 The association between residence
in correctional facilities and TB is an old one. A
study of 512 New York City inmates in the early
1900s found 15 (2.9 percent) to have active TB
and noted, “The finding of cases of this kind in
congested barrack rooms accentuates the necessity for a careful examination of all inmates.”131
The authors suggested that, as a routine, sputum
“should be submitted to microscopic examination
if there is cough with expectoration and the physical examination of the chest leads to suspicion
that tuberculosis may be present.”132 The public
health law of New York State in 1902, in discussing the housing requirements of juvenile
delinquents, ordered that, “The beds in every
dormitory in such institution shall be separated
by a passageway of not less than 2 feet in width,
and so arranged that under each the air shall
freely circulate and there shall be adequate
ventilation. . . . The physician of the institution
shall immediately notify in writing the local board
of health and the board of managers or directors
of the institution of any violation of any provision
of this section.”133 It is clear that the fundamental
elements of screening, environmental control, and

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public health agency involvement in TB control in
correctional facilities have existed, at least in
New York City, for the past century.
With the resurgence of TB in the mid-1980s came
a recognition that jails and prisons were serving
as hotbeds of TB transmission, leading to studies
that have better defined the epidemiology of TB
in correctional institutions. A large-scale survey
in 1984 and 1985 of TB cases in 29 States found
that the incidence of active TB in correctional
facilities was 3.9 times greater (95 percent
confidence intervals, 3.35–4.49) than the rate
in the surrounding communities.134 This disparity was observed in high-, medium-, and lowincidence States. In the New York State correctional system, the incidence of TB increased
sevenfold between 1976 and 1986.135 In 1994,
4.6 percent of the incident cases of TB nationally
were diagnosed in the correctional setting.136 In
New York City, the national epicenter of TB, 3.5
percent of individuals diagnosed with TB were
incarcerated at the time of or within 1 year before
diagnosis.137 In 1997, 768 inmates were treated for
active TB, and 7.8 percent of inmates nationally
were diagnosed with TB infection (tuberculin
test positive).138 Over the past decade, numerous outbreaks of TB have been reported in
correctional facilities across the country.139 The
role of the correctional facility as a breeding
ground for TB has been a familiar topic in the
mainstream medical, public health, and lay
press.140
One other important epidemiologic trend that
deserves mention is the emergence of multi-drugresistant tuberculosis as a common phenomenon
in the late 1980s. Multi-drug-resistant TB is
caused by strains of Mycobacterium tuberculosis
that are resistant to both isoniazid and rifampin
(the two best agents for the treatment of active
disease) and is characterized by the necessity for
lengthy, expensive, toxic treatment regimens and
high rates of mortality. This daunting problem
originated from poor patient compliance with
standard treatment regimens that were prescribed
without supervision or observation.141 Not surprisingly, correctional facilities played a major
role in the growth of the multi-drug-resistant TB

epidemic.142 Directly observed therapy programs
have recorded dramatic success in recent years in
controlling this disease.143 While case rates of TB
(including multi-drug-resistant TB) nationally, in
cities, and in jails and prisons have dropped in
response to increased funding of public control
programs, at least one noted authority has predicted future resurgences because of a lack of
governmental foresight leading to diminished
rather than redoubled efforts to stamp out the
disease.144

Potential interventions
Efforts to control the spread of TB both inside
and through the bars of correctional facilities
should focus on those parameters mentioned in
prior discussions—reducing the likelihood of
disease transmission per contact (b), the duration
of infectivity (D), and the mean number of new
contacts per unit of time (c).
Reducing the likelihood of disease transmission
per contact. The prisoner population can be
divided conceptually into three groups: A small
number of inmates with active TB who can spread
their disease to others, a larger number of inmates
with TB infection but without active TB who are
at risk for progression of disease to an active
state, and a majority of inmates who have neither
and are susceptible contacts of contagious
patients. Even with highly efficient screening
programs, it is inevitable that congregate housing
prior to screening, failure of screening procedures
to detect all cases of active TB, or the progression
of TB infection to active TB during the term of
incarceration will lead to some exposures of
susceptible individuals. Certain common sense
measures can mitigate the risk of transmission
from contagious patients to susceptible individuals (b). First, areas within jails and prisons
that contain large numbers of prisoners for
substantial time intervals (especially housing
dormitories and mess halls) should be well
ventilated. Areas that are likely to contain patients
with undiagnosed active TB, such as initial intake
areas and sick-call clinics, should have adequate
ventilation and should consider such additional
measures as HEPA filtration and microbicidal

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ultraviolet radiation. Dormitories and infirmaries
housing inmates with suppressed immune systems, such as AIDS patients, should be particularly stringent in screening current and prospective admissions for active TB because the pace
of TB spread through immunosuppressed populations may be extremely rapid.145 Finally,
correctional staff throughout all facilities should
be attuned to the problem of TB and should be on
the alert for inmates with persistent coughs,
sputum production, fever, and weight loss.
Inmates who are coughing should be encouraged
to wear a mask or at least to cover their coughs
with their hands or with tissues until medical
evaluation is complete.
Reducing the duration of infectiousness. Three
methods are available to reduce the duration of
infectiousness (D) of active TB cases. First is
timely diagnosis of disease. Authoritative
recommendations for screening of prisoners for
TB infection and active TB are available to the
interested reader.146 All facilities should have
a formal program of TB screening of new
admissions and housed prisoners with new
symptoms, as well as periodic evaluation of all
housed prisoners. The elements of the program
should be history and physical examination by a
qualified health care provider, tuberculin skin
testing, chest roentgenography, and cross-check
with the local health department for evidence of a
TB diagnosis. Each facility should, in cooperation
with local public health agencies, modulate the
intensity of these screening tools in accordance
with the epidemiology of TB in the surrounding
community. A large survey of TB screening
practices in correctional facilities in 1994 found
that 98 percent of State and Federal systems and
66 percent of city and county systems screened
incoming inmates for TB infection. Ninety
percent of State and Federal systems and 41
percent of city and county systems screened
prisoners annually.147 Although these statistics are
improved over those of the past, higher rates of
compliance with these screening procedures,
particularly in city and county systems, are an
important goal.

The second effective method for reducing the
duration of infectivity is airborne isolation.
Guidelines for appropriate isolation of patients
with proven or suspected active TB are readily
available to the interested reader.148 All correctional facilities should have access to appropriate
isolation rooms either onsite or at local hospitals.
Patients should remain in isolation until they are
deemed to be noninfectious by their medical
provider. The duration of isolation may range
from several days for inmates who turn out not to
have active TB, to several weeks for patients with
uncomplicated active TB, to several months or
more for patients with multi-drug-resistant TB.
Any legal proceedings that cannot await the
completion of the isolation process should be
conducted within the confines of the isolation
facility; patients with suspected or proven active
TB who may be infectious should not attend
courtroom proceedings. In 1994, 61 percent of
State and Federal systems reported that they
housed patients with suspected or confirmed
active TB in appropriate airborne isolation rooms
onsite and 59 percent reported that they housed
such patients in community hospital isolation
rooms (some systems housed inmates both onsite
and in local hospitals).149 Forty-eight percent of
city and county systems housed patients in
appropriate isolation rooms onsite and 52 percent
sent patients to community hospitals for isolation
(some systems housed inmates both onsite and in
local hospitals).150 These statistics were dramatically better than in 1992, but more than 25 percent of the systems still reported inappropriate
isolation practices for patients with suspected or
proven active TB, most commonly involving
placement in single rooms without air exchanges
or negative pressure. Approximately 75 percent of
the systems reported appropriate practices surrounding sputum smear examination and discontinuation of airborne isolation. It is both unethical
and illegal to subject prisoners to exposure to
confirmed or suspected active TB. Therefore,
every facility must have a responsible plan to
provide acceptable isolation for individuals who
may have contagious disease.

187
The final method for reducing duration of
infectivity is prompt and effective treatment.
Studies suggest that patients without drugresistant TB are rapidly rendered noninfectious by
appropriate medical therapy.151 All treatment for
active TB in correctional facilities should be
administered under direct observation.152 Cases
presenting diagnostic or therapeutic dilemmas,
such as drug-resistant cases, should be managed
under the supervision of a practitioner with
expertise in this field. Case management should
be closely coordinated with the local health
department and provisions for followup in the
community must be arranged for all inmates who
may be released during their course of treatment.
In 1994, 94 percent of State and Federal systems
and 90 percent of city and county systems
reported that they employed directly observed
therapy for all inmates receiving treatment for
active TB.153
Reducing the mean number of new contacts
per unit of time. Many of the measures outlined
in the section entitled “Reducing the likelihood of
disease transmission per contact” also serve to
reduce the mean number of new contacts per unit
of time. The occasional inmate who penetrates
into the general population despite existing
screening practices will do the least public health
damage in a facility that is not overcrowded and
where progressive symptoms and signs of
diseases lead an attuned correctional staff to
evaluate and isolate the prisoner in a timely
manner.
Miscellaneous. Several other ingredients are
required for TB control in correctional facilities.
First is TB preventive therapy for inmates with
TB infection. The CDC recommends that all
preventive therapy for TB within jails and prisons
be directly observed.154 Given a national mean
prevalence of TB infection at time of intake of
4.3–8.9 percent, many hundreds of thousands of
inmates per year would be candidates for directly
observed preventive therapy. Since few, if any,
facilities have the personnel to administer such
programs, compliance with these recommendations has been inconsistent. One pilot program of
directly observed preventive therapy in the Seattle

jail system with aggressive community followup
yielded disappointing results.155 An earlier study
in the New York City system demonstrated that
the best predictors of compliance with preventive
therapy were a higher level of understanding
of the disease process and ease of access to
medication.156 TB preventive therapy is a key
strategy in preventing new cases of active TB
from emerging in a community and innovative
approaches are needed in order to optimize the
use of this powerful public health tool.
Additionally, every correctional facility must
have the ability to conduct thorough contact
investigations when cases of active TB occur in
the general inmate population. Because newly
infected patients are at high risk of progression to
active TB, contacts of active TB cases must be
evaluated and screened for signs of new infection
according to established protocols.157 Some
groups, such as HIV-infected patients, are at such
high risk that empiric TB preventive therapy
should begin at the earliest possible opportunity
after exposure.158 The ability to conduct thorough
contact investigations depends on the correctional
facility’s ability to identify other inmates who
shared airspace with the infected individual at the
time of contagion and on the organized efforts of
personnel designated to complete this task.
Employees of the facility may also require
screening.
Finally, all TB control activities in jails and
prisons should be performed in concert with local
health departments. Access to health department
registries are invaluable in identifying TB patients
who may fail to report their diagnosis at the time
of intake.159 These agencies may also assist in
completing the community components of contact
investigations, ensuring followup of inmates after
release, and tracking epidemiologic trends
pertaining to TB, both inside and outside the
facility.

Hepatitis B and C
Overview/epidemiology
The problems of hepatitis B and C in correctional
facilities have received relatively little attention.

188
In the era antedating current recommendations for
universal vaccination of children, approximately
300,000 new cases of hepatitis B occurred per
year, mostly in young adults, resulting in 10,000
hospitalizations and 300 deaths from fulminant
disease annually. Approximately 25,000 of each
year’s new cases develop chronic disease with the
virus, accounting for a national chronic carrier
population approaching 1 million individuals
and for approximately 5,000 deaths annually
attributable to consequences of chronic infection
(approximately 4,000 from cirrhosis and 1,000
from hepatocellular carcinoma).160 While the
epidemiology of hepatitis B in the United States
will undergo dramatic changes as a result of
universal vaccination of children, the virus will
remain an important pathogen for the foreseeable
future.
Hepatitis C is receiving increasing attention from
the medical and lay community. In the 10 years
since the discovery and identification of the
pathogen, it has become clear that hepatitis C is
the most common chronic bloodborne viral
infection in the United States.161 Approximately
3.9 million individuals in the Nation have been
infected with this virus. In contrast to hepatitis B,
the majority of these people remain chronically
infected. Complications of hepatitis C infection
account for an estimated 25,000 deaths annually,
or approximately 1 percent of all deaths.162
Although hepatitis B and C are two distinct
diseases their routes of transmission are similar.
Both viruses may be acquired through exposure to
contaminated blood products especially during
injection drug use and historically during
transfusion. Rates of transfusion-associated
hepatitis B and C have dropped dramatically since
routine testing of all blood products was begun.163
Infants are at high risk for hepatitis B acquisition
if their mothers are actively infected and vertical
transmission of hepatitis C also occurs. Sexual
transmission is another important route for
hepatitis B, less so for hepatitis C. In general,
patients with active or chronic hepatitis B are
more likely to transmit their infection to
susceptible contacts than patients with hepatitis
C. This transmission advantage is, however,

counterbalanced by the longer average duration of
infectivity of individuals who acquire hepatitis C
infection and the lack of a means (i.e., vaccine) to
promote protective immunity in those uninfected
with hepatitis C.
Despite significant advances in the treatment of
viral hepatitis, there is no consistently effective
regimen available to cure either disease. Regimens offering some hope of cure are lengthy,
expensive, and fairly toxic.
Although viral hepatitis in the correctional setting
is becoming the focus of renewed attention, it is
by no means a new problem. It has a colorful
history dating back to the decades preceding the
identification of the viral causes of serum
hepatitis. Forty years ago, in the early days of
transfusion medicine, units of blood were
generally obtained from one of two sources,
family and friends of the patient requiring
transfusion or professional donors.164 Professional
donors were paid small fees to donate blood and
were often drawn from the most indigent segments of society including alcoholics and drug
addicts. Another common category of professional donor was the prisoner, and prison blood
donation was an important part of the transfusion
blood supply into the 1970s.165 Because no
serologic tests for viral hepatitis were available,
screening was limited to donor-supplied reports of
prior hepatitis or jaundice. In commenting on this
donor pool, one authority stated, “The purchase of
blood at low rates attracts many alcoholics or
other unfortunates who return every 8 or 10
weeks and who know that they will not get the
money if they answer ‘Yes’ to questions not only
about jaundice but malaria and other infectious
diseases.”166 A study of transfusion recipients in
Chicago between 1946 and 1956 found a rate of
serum hepatitis of 0.3 percent in patients who
received 1 unit of blood from a family member
compared to 3.2 percent in patients who received
one unit of blood from a prisoner donor.167 By the
late 1950s it was clear not only that the incarcerated population had a high prevalence of
contagious, bloodborne hepatitis, but also that
the correctional facilities themselves were
serving as amplifiers of disease through the

189
routes of intrafacility injection drug use; use of
nondisposable, nonsterile needles for medicinal
purposes; use of nonsterilized dental equipment;
and tattooing.168 Over the ensuing decades, the
practice of obtaining blood donations from
prisoners fell out of favor. During the era of
modern diagnostic testing for viral hepatitis, there
have been sporadic reports detailing prevalences
of hepatitis B and C in jail and prison populations.
High rates of hepatitis B and C in IDUs and in
the socioeconomically disadvantaged have, not
surprisingly, resulted in a disproportionate burden
of disease in prisoners. Numerous series from
around the country have consistently shown
prevalences of these diseases in correctional
facilities at least several times higher than in the
general U.S. population.169 These observations
have led to recommendations for more aggressive
screening of prisoners and a consideration of
more intensive vaccination efforts.170
Few recent studies are available to define the
current epidemiology of hepatitis B and C in
correctional facilities and most of these data have
been presented in abstract form, not in peerreviewed medical journals. Two large surveys
conducted during the 1990s found a seroprevalence of acute or chronic hepatitis B
infection of 1.8 percent in the New York State
correctional system171 and 2.2 percent in the
California correctional system.172 An unpublished
study in the early 1990s of 1,271 patients on
Rikers Island in New York City who were
initiating TB therapy or prophylaxis, initiating
antiretroviral therapy, or had abnormal liver
function tests demonstrated an 8 percent prevalence of chronic hepatitis B.173 These rates are
an order of magnitude greater than those of the
general population.174 Mathematical modeling
of hepatitis C rates in prisoners and releasees
based on serosurveys of prisoners and IDUs in
a report by Hammett, Harmon, and Rhodes
estimated that 17.0–18.6 percent of prisoners
and releasees in 1996 and 1997 were infected
with hepatitis C, translating into populations of
303,000–332,000 prisoners and 1.3–1.4 million
releasees infected with hepatitis C. These
investigators suggested that an astounding 29–32
percent of all persons with hepatitis C in the

Nation passed through a correctional facility in
1996.175

Potential interventions
As pathogens that are transmitted by both the
bloodborne and sexual routes, strategies to curb
the transmission of hepatitis B and C are very
similar to those employed for HIV. These
strategies must rely on interventions that decrease
the likelihood of transmission of infection from
an infected person to an uninfected person, the
duration of infectiousness, and the average
number of contacts with uninfected individuals
during a unit of time.
Reducing the likelihood of disease transmission
per contact. Methods to reduce the likelihood of
transmission (b) include harm-reduction messages
identical to those employed for HIV. An additional educational component is needed, however,
to inform prisoners that viral hepatitis is a serious
threat separate from that of HIV and that safer
needle sharing and sexual practices are necessary
even when all involved have tested negative for
HIV. Public health agencies support the
institution of widespread testing for hepatitis B
and C in inmates.176 Such testing programs are
justifiable on the premise that individuals who are
identified as infected may receive intensified
harm-reduction counseling and curb their highrisk behaviors. In turn, b could be reduced
through safer injection and sexual practices.
Furthermore, better and earlier diagnosis of
hepatitis B and C may allow for successful
treatment of certain prisoners with antiviral
agents. Such treatment, while far from uniformly
effective, may offer some hope of reducing viral
burden and hence transmissibility and may lead to
actual cure in a minority of patients.177 Prisoners
receiving antiviral treatment for hepatitis B or C
must be managed by a physician with expertise in
this area, generally a gastroenterologist or an
infectious-diseases specialist. Finally, screening
prisoners will identify a population of high-risk
individuals who are not yet infected with hepatitis
B or C. For these prisoners, educational messages
may provide useful strategies for avoiding
infection in the future, including safer injection
and sexual behaviors, as well as the possibility of

190
hepatitis B vaccination for prisoners who are both
hepatitis B surface antigen and antibody negative.
As with HIV, these interventions are able to affect
multiple parameters determining disease transmission in a community simultaneously and the
beneficial effects of behavior modification aimed
at avoiding hepatitis transmission would, by
extension, augment efforts to decrease HIV
transmission and vice versa.
Reducing the duration of infectiousness.
Cessation of injection drug use and sexual contact
with uninfected partners as a result of harmreduction training could effectively reduce the
duration of infectiousness (D) in a subset of
patients. Cure of disease by antiviral therapies
could also serve to reduce the mean duration of
infectiousness. The effect of such treatments on
hepatitis transmission in the community may
become more profound as new and better
therapeutic options emerge.
Reducing the mean number of susceptible new
contacts per unit of time. Harm-reduction
counseling and behavior modification techniques
together with social and legal remedies may lead
to reductions in numbers of susceptible contacts
per infected individual (c). These issues have
already been discussed in greater detail in the
section on HIV infection. In the case of hepatitis
B, however, vaccination offers another route to
decrease c. The number of susceptible contacts
exposed per unit time can be reduced effectively
by increasing the rate of hepatitis B immunity in
the population. In the decades to come, there is
hope that universal pediatric vaccination will
increase herd immunity in the United States to a
point that disease transmission and long-term
sequelae become uncommon.178 In the meantime,
although the disease continues to thrive among
those subsets of the adult population that tend to
reside in correctional facilities,179 much benefit
can be derived from and much expense and illness
averted by the use of aggressive, targeted hepatitis
B vaccination in adults. A number of high-risk
groups, including prisoners, have been suggested
as potential target populations.180 The idea of
mass vaccination of prisoners is attractive. An
extremely safe and effective vaccination could
protect large numbers of prisoners from a serious

health threat. Immunization of all inmates is
probably not the proper approach, however. Up to
80 percent of prisoners in some facilities may
show serologic evidence of prior hepatitis B
infection181 and therefore would not benefit from
vaccination. A complete vaccination series
requires 3 injections administered over 6 months.
Prisoners who are incarcerated for less than 6
months, especially in jail systems, are unlikely to
properly complete the series once released. These
two realities, combined with the fairly high cost
of the hepatitis B vaccine, necessitate a more
selective approach to hepatitis B vaccination in
prisoners. Screening for serologic markers of
hepatitis B infection and vaccination in short-term
stay facilities in which mean lengths of stay are
often on the order of several days would be fairly
senseless because few prisoners would remain to
complete the vaccination or even to receive their
serologic test results. If, however, a subset of the
prisoner population could be identified with likely
durations of incarceration exceeding 6 months,
members of this group would be good candidates
for hepatitis B surface antigen and antibody
testing and for vaccination if these markers were
absent. In prisons, where lengths of stay are
longer and better defined, a program of universal
hepatitis B screening and vaccination of uninfected, nonimmune individuals would doubtless
save thousands of preventable new cases of
hepatitis B each year. Methods of vaccine
administration that could lessen the cost and
perhaps the duration of the series are under
investigation182 and offer the hope of broader
hepatitis B vaccination in correctional facilities
in the future.
In summary, jails and prisons should be targets
for intensified education about the dangers of
hepatitis B and C and about methods available to
decrease the rates of transmission and acquisition.
Broad-based screening for hepatitis B and C are
recommended, as is vaccination of all uninfected,
nonimmune prisoners against hepatitis B. These
efforts should not be applied wastefully, however,
and their applicability to a given facility depends
primarily on the mean length of stay of inmates.
Certainly, these programs should be universal or
near universal in prison systems where lengths
of stay are longer and better defined. Finally,

191
facilities must offer antiviral treatments supervised by appropriate subspecialty trained
physicians to prisoners with hepatitis B and C
who are deemed to be candidates. As therapies
become more effective and better accepted, the
need for these resources in correctional facilities
will increase.

Conclusions
The burden of infectious diseases in correctional
facilities in this country is staggering. The
likelihood of active infection with a variety of
serious pathogens among prisoners is many times
higher than in the surrounding communities. In
studies that have analyzed the proportion of cases
of significant infectious diseases inside versus
outside the bars of the facilities, the results have
proven that prisoners and releasees can be major
driving forces behind epidemics. Although
correctional facilities have achieved some
measure of success nationally in controlling TB
and syphilis (in specific regions), overall efforts
to control other infections, such as HIV, have
been dismally ineffective. To implement
appropriate screening, treatment, and prevention
programs for the infections discussed in this
document is expensive, but not nearly as
expensive as a failure to do so. The problem of
infectious diseases among prisoners represents
not only a daunting challenge but also an
extraordinary opportunity for the private and
public health of this Nation.

Notes
1. Gilliard, D.K., and A.J. Beck, Prisoners in 1997,
Bureau of Justice Statistics Bulletin, Washington, DC:
U.S. Department of Justice, Bureau of Justice
Statistics, August 1998, NCJ 170014.
2. Centers for Disease Control and Prevention,
“Assessment of Sexually Transmitted Disease Services in City and County Jails—United States, 1997,”
Morbidity and Mortality Weekly Report 47(21)(1998):
429–431.
3. Gilliard, D.K., and A.J. Beck, Prisoners in 1997
(see note 1).
4. Ibid.

5. Stead, W.W., “Undetected Tuberculosis in Prison:
Sources of Infection for Community at Large,” Journal
of the American Medical Association 240(23)(1978):
2544–2547.
6. Centers for Disease Control and Prevention,
“Assessment of Sexually Transmitted Disease Services
in City and County Jails—United States, 1997” (see
note 2); Stead, W.W., “Undetected Tuberculosis in
Prison: Sources of Infection for Community at Large”
(see note 5); Glaser, J.B., and R.B. Greifinger, “Correctional Health Care: A Public Health Opportunity,”
Sexually Transmitted Diseases 25(6): 308–309;
Hammett, T.M., R. Widom, J. Epstein, M. Gross, S.
Sifre, and T. Enos, 1994 Update: HIV/AIDS and
Sexually Transmitted Diseases in Correctional
Facilities, Issues and Practices, Washington, DC: U.S.
Department of Justice, National Institute of Justice and
Centers for Disease Control and Prevention, National
Center for HIV, STD, and TB Prevention, December
1995, NCJ 156832; Cohen, D., R. Scribner, J. Clark,
and D. Cory, “The Potential Role of Custody Facilities in Controlling Sexually Transmitted Diseases,”
American Journal of Public Health 82(4)(1997):
552–556; Skolnick, A.A., “Look Behind Bars for Key
to Control of STDs,” Journal of the American Medical
Association 279(2)(1998): 97–98; Glaser, J.B.,
“Sexually Transmitted Diseases in the Incarcerated: An
Underexploited Public Health Opportunity,” Sexually
Transmitted Diseases 25(6)(1998): 308–309.
7. Anderson, R.M., and R.M. May, eds., Infectious
Diseases of Humans: Dynamics and Control, Oxford:
Oxford University Press, 1995; Garnett, G.P., and
R.M. Anderson, “Sexually Transmitted Diseases
and Sexual Behavior: Insights From Mathematical
Models,” Journal of Infectious Diseases 174(1996):
S150–S161; Shiboski, S., and N.S. Padian,
“Population- and Individual-Based Approaches to
the Design and Analysis of Epidemiologic Studies of
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Diseases 174(1996): S188–S200.
8. Garnett, G.P., and R.M. Anderson, “Sexually
Transmitted Diseases and Sexual Behavior: Insights
From Mathematical Models” (see note 7).
9. Anderson, R.M., and R.M. May, “Social Heterogeneity and Sexually Transmitted Diseases,” in
Infectious Diseases of Humans: Dynamics and
Control, R.M. Anderson and R.M. May, eds.,
Oxford: Oxford University Press, 1992: 228–303.

192
10. Garnett, G.P., and R.M. Anderson, “Sexually
Transmitted Diseases and Sexual Behavior: Insights
From Mathematical Models” (see note 7); Thomas,
J.C., and M.J. Tucker, “The Development and Use of
the Concept of a Sexually Transmitted Disease Core,”
Journal of Infectious Diseases 174(1996): S134–S143;
Yorke, J.A., H.W. Hethcote, and A. Nold, “Dynamics
and Control of the Transmission of Gonorrhea,”
Sexually Transmitted Diseases 5(2)(1978): 51–56.
11. Clottey, C., and G. Dallabetta, “Sexually
Transmitted Diseases and Human Immunodeficiency
Virus: Epidemiologic Synergy?” Infectious Disease
Clinics North America 7(4)(1993): 753–770.
12. Hammett, T.M., R. Widom, J. Epstein, M. Gross,
S. Sifre, and T. Enos, 1994 Update: HIV/AIDS and
Sexually Transmitted Diseases in Correctional
Facilities (see note 6).
13. Hammett, T.M., P. Harmon, and W. Rhodes, “The
Burden of Infectious Disease Among Inmates and
Releasees From Correctional Facilities,” paper
prepared for the National Commission on Correctional
Health Care, Chicago, IL, May 2000. (Copy in this
volume.)
14. Centers for Disease Control and Prevention,
“Syphilis Screening Among Women Arrestees at the
Cook County Jail—Chicago, 1996,” Morbidity and
Mortality Weekly Report 47(21)(1998): 432–433.
15. Skolnick, A.A., “Look Behind Bars for Key to
Control of STDs” (see note 6).
16. Blank, S., D.D. McDonnell, S.R. Rubin, J.J. Neal,
M.W. Brome, M.B. Masterson, and J.R. Greenspan,
“New Approaches to Syphilis Control: Finding
Opportunities for Syphilis Treatment and Congenital
Syphilis Prevention in a Women’s Correctional
Setting,” Sexually Transmitted Diseases 24(9)(1997):
218–228.
17. Shuter, J., D. Bell, D. Graham, K.A. Holbrook,
and E.Y. Bellin, “Rates of and Risk Factors for
Trichnomoniasis Among Pregnant Inmates in New
York City,” Sexually Transmitted Diseases
25(6)(1998): 303–307.
18. Edlin, B.R., K.L. Irwin, S. Faruque, C.B. McCoy,
C. Word, Y. Serrano, J.A. Inciardi, B.P. Bowser,
R.F. Schilling, and S.D. Holmberg, “Intersecting
Epidemics—Crack Cocaine Use and HIV Infection

Among Inner-City Young Adults: Multicenter Crack
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England Journal of Medicine 331(21)(1994):
1422–1427.
19. Coles, F.B., S.S. Hipp, G.S. Silberstein, and J.H.
Chen, “Congenital Syphilis Surveillance in Upstate
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20. Blank, S., D.D. McDonnell, S.R. Rubin, J.J. Neal,
M.W. Brome, M.B. Masterson, and J.R. Greenspan,
“New Approaches to Syphilis Control: Finding
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21. Ngugi, E.N., D. Wilson, J. Sebstad, F.A. Plummer,
and S. Moses, “Focused Peer-Meditated Educational
Programs Among Female Sex Workers to Reduce
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S240–S247.
22. Centers for Disease Control and Prevention,
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Cook County Jail—Chicago, 1996” (see note 14).
23. Blank, S., D.D. McDonnell, S.R. Rubin, J.J. Neal,
M.W. Brome, M.B. Masterson, and J.R. Greenspan,
“New Approaches to Syphilis Control: Finding
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24. Centers for Disease Control and Prevention,
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Potential Role of Custody Facilities in Controlling
Sexually Transmitted Diseases” (see note 6).

193
27. Kiviat, N.B., J.A. Paavonen, P. Wolner-Hanssen,
C. Critchlow, W.E. Stamm, J. Douglas, D.A.
Eschenbach, L.A. Corey, and K.K. Holmes, “Histopathology of Endocervical Infection Caused by
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28. Stary, A., S.F. Ching, L. Teodorowicz, and H. Lee,
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S. Sifre, and T. Enos, 1994 Update: HIV/AIDS and
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30. Hammett, T.M., P. Harmon, and W. Rhodes, “The
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31. Puisis, M., W.C. Levine, and K.J. Mertz,
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32. Ibid.
33. Holmes, M.D., S.M. Safyer, N.A. Bickell, S.H.
Vermund, P.A. Hanff, and R.S. Philips, “Chlamydial
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34. Homes, K.K., D.W. Johnson, P.A. Kvale, C.W.
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35. Ibid.
36. Yorke, J.A., H.W. Hethcote, and A. Nold,
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37. Centers for Disease Control and Prevention,
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46(9)(1997): 193–198; McCormack, W.M., and M.F.
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Dolin, eds., New York: Churchill Livingstone, 1995:
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43. Hammett, T.M., P. Harmon, and W. Rhodes, “The
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56. Glaser, J.B., “Sexually Transmitted Diseases in the
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49. Kiviat, N.B., J.A. Paavonen, P. Wolner-Hanssen,
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81. Ibid.
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86. Hammett, T.M., R. Widom, J. Epstein, M. Gross,
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117. Eng, T.R., and W.T. Butler, eds., The Hidden
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132. Ibid.
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137. New York City Department of Health, Health of
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147. Wilcock, K., T.M. Hammett, R. Widom, and J.
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152. U.S. Department of Health and Human Services,
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162. Ibid.

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163. Ibid.
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166. Allen, J.G., D. Dawson, W.A. Sayman, et al.,
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170. Centers for Disease Control and Prevention,
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173. E.Y. Bellin, unpublished observation.

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176. Centers for Disease Control and Prevention,
“Recommendations for Prevention and Control of
Hepatitis C Virus (HCV) Infection and HCV-Related
Chronic Disease” (see note 161); Centers for Disease
Control, “Hepatitis B Virus: A Comprehensive
Strategy for Eliminating Transmission in the United
States Through Universal Childhood Vaccination:
Recommendations of the Immunization Practice
Advisory Committee (ACIP)” (see note 170); ACP
Task Force on Adult Immunization and Infectious
Diseases Society of America, Guide for Adult
Immunization (see note 170).

180. Centers for Disease Control, “Hepatitis B Virus:
A Comprehensive Strategy for Eliminating Transmission in the United States Through Universal
Childhood Vaccination: Recommendations of the
Immunization Practice Advisory Committee (ACIP)”
(see note 170); ACP Task Force on Adult Immunization and Infectious Diseases Society of America,
Guide for Adult Immunization (see note 170).

177. Centers for Disease Control and Prevention,
“Recommendations for Prevention and Control of
Hepatitis C Virus (HCV) Infection and HCV-Related
Chronic Disease” (see note 161); Omata, M. “Treatment of Chronic Hepatitis B Infection,” New England
Journal of Medicine 339(2)(1998): 114–115.

182. Jaiswal, S.P., M.V. Asolkar, R. Vijayvargiya, and
D.S. Chitnis, “Immunogenicity of Low Dose Hepatitis
B Vaccine by the Intradermal Route and Persistence of
Anti-HBs After Three Years,” Indian Journal of
Medical Research 102(1995): 129–133; Contractor,
Q.Q., S.N. Marathe, V.V. Parab, and V.V. Kale,
“Accelerated, Low-Dose, Intradermal Hepatitis B
Vaccine,” Indian Journal of Gastroenterology
16(1)(1997): 37.

178. Centers for Disease Control, “Hepatitis B Virus:
A Comprehensive Strategy for Eliminating Transmission in the United States Through Universal

181. ACP Task Force on Adult Immunization and
Infectious Diseases Society of America, Guide for
Adult Immunization (see note 170).

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Appendix A: NCCHC/NIJ Project
Participants, Author/Experts,
Consultants
Steering Committee

Chronic Disease Panel

B. Jaye Anno, Ph.D., CCHP-A
Consultants in Correctional Care
Santa Fe, New Mexico

Authors

R. Scott Chavez, M.P.A., PA-C, CCHP
National Commission on Correctional Health Care
Chicago, Illinois
Cheryl Crawford, M.P.A., J.D.
National Institute of Justice
Washington, D.C.
Andrew Goldberg, M.A.
National Institute of Justice
Washington, D.C.
Robert Greifinger, M.D.
National Commission on Correctional Health Care
Dobbs Ferry, New York
Edward Harrison, M.M., CCHP
National Commission on Correctional Health Care
Chicago, Illinois
John Miles, M.P.A.
Centers for Disease Control and Prevention
Atlanta, Georgia
Marilyn Moses, M.S.
National Institute of Justice
Washington, D.C.
Laura Winterfield, Ph.D.
National Institute of Justice
Washington, D.C.

Carlton Hornung, Ph.D., M.P.H.
University of Louisville
Louisville, Kentucky
Clyde Schechter, M.D.
Mt. Sinai School of Medicine
New York, New York
Donna Tomlinson, M.D., M.Sc.
Beth Israel Hospital
New York, New York

Panel Members
Hazel Dean-Gaitor, Sc.D., M.P.H.
Centers for Disease Control and Prevention
Atlanta, Georgia
Lori de Ravello, M.P.H.
Centers for Disease Control and Prevention
Atlanta, Georgia
Rod Gottula, M.D.
University of Colorado Health Science Center
Denver, Colorado
Lambert King, M.D., Ph.D.
St. Vincent’s Medical Center
New York, New York
Maureen Mangotich, M.D.
Pfizer Health Solutions
Santa Monica, California

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W. Paul McKinney, M.D.
University of Louisville
Louisville, Kentucky
Joseph Paris, M.D., Ph.D., CCHP
Georgia Department of Corrections
Atlanta, Georgia
Michael Puisis, D.O.
Addus HealthCare's Correctional Division
Evanston, Illinois
Dianne Rechtine, M.D., CCHP-A
Florida Reception Center
Orlando, Florida
Ron Shansky, M.D., M.P.H.
Correctional Medicine Consultant
Chicago, Illinois

Communicable Disease Panel
Authors
Theodore Hammett, Ph.D.
Abt Associates
Cambridge, Massachusetts
Julie Kraut, Ph.D.
Centers for Disease Control and Prevention
Atlanta, Georgia
Rob Lyerla, Ph.D.
Centers for Disease Control and Prevention
Atlanta, Georgia
Jonathan Shuter, M.D.
Consultant
New Rochelle, New York
Zachary Taylor, M.D., M.S.
Centers for Disease Control and Prevention
Atlanta, Georgia
Beena Varghese, Ph.D.
Centers for Disease Control and Prevention
Atlanta, Georgia

Panel Members
Frederick Altice, M.D.
Yale University School of Medicine
New Haven, Connecticut
Eran Bellin, M.D.
Montefiore Medical Center
Bronx, New York
John Clark, M.D., M.P.H., CCHP-A
Los Angeles County Sheriff's Department.
Los Angeles, California
Phyllis Cruise, B.A.
Texas Department of Health
Austin, Texas
Hazel Dean-Gaitor, Sc.D., M.P.H.
Centers for Disease Control and Prevention
Atlanta, Georgia
Anne Degroot, M.D.
Brown University
Providence, Rhode Island
Theodore Hammett, Ph.D.
Abt Associates
Cambridge, Massachusetts
T. Stephen Jones, M.D.
Centers for Disease Control and Prevention
Atlanta, Georgia
Newton Kendig, M.D.
Federal Bureau of Prisons
Washington, D.C.
Fred Martich, B.S.
Centers for Disease Control and Prevention
Atlanta, Georgia
Eric Mast, M.D., M.P.H.
Centers for Disease Control and Prevention
Atlanta, Georgia
Margaret Oxtoby, M.D.
New York State Department of Health
Albany, New York

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Betty Rider, M.A., M.S.
North Carolina Department of Corrections
Durham, North Carolina

Elissa Benedek, M.D.
University of Michigan Medical Center
Ann Arbor, Michigan

George Schmid, M.D., M.Sc.
Centers for Disease Control and Prevention
Atlanta, Georgia

Tom Conklin, M.D., CCHP-A
Hampden County Correctional Facility
Ludlow, Massachusetts

Anne Spaulding, M.D.
Rhode Island Department of Corrections
Cranston, Rhode Island

Juarlyn Gaiter, Ph.D.
Centers for Disease Control and Prevention
Atlanta, Georgia

Steven Szebenyi, M.D., FACP
Blue Shield of Northeastern New York
Albany, New York

Martin Horn, M.A.
Pennsylvania Department of Corrections
Camp Hill, Pennsylvania

David Thomas, M.D., J.D.
Florida Department of Corrections
Tallahassee, Florida

Holly Hills, Ph.D.
The GAINS Center
Tampa, Florida

Rich Voigt, M.A.
Centers for Disease Control and Prevention
Atlanta, Georgia

Pradan Nathan, M.D.
Texas Department of Criminal Justice
Huntsville, Texas

Mental Illness Panel

Hal Smith
Central New York Psychiatric Institute
Marcy, New York

Author
Bonita Veysey, Ph.D.
Rutgers University School of Criminal Justice
Newark, New Jersey

Panel Members
Tim Akers, Ph.D.
Centers for Disease Control and Prevention
Atlanta, Georgia
Carl C. Bell, M.D., FAPA, CCHP, FAC Psych.
Community Mental Health Council & Foundation, Inc.
Chicago, Illinois

Henry Steadman, Ph.D.
The National GAINS Center
Delmar, New York
Linda Teplin, Ph.D.
Northwestern University Medical School
Chicago, Illinois
Henry C. Weinstein, M.D., J.D., CCHP
New York University Medical Center
New York, New York

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Appendix B: Biographies of
Contributors
FREDERICK L. ALTICE, M.D., is associate professor of medicine, AIDS Program, at Yale University
School of Medicine. He is also director of the HIV in Prisons Program in the State of Connecticut and the
Community Health Care Van Project. A graduate of Emory University, he is a researcher, writer, and
lecturer who is active in the American Public Health Association, the Infectious Disease Society of
America, and the Society for Correctional Physicians. He is also one of the founders of HEPP News
(HIV Education Prison Project), a forum for correctional problem solving. He has written numerous
articles and papers. His chapters “Overview of HIV Care” and “Use of Antiretroviral Agents in the
Treatment of HIV” in the 1998 publication Clinical Practice in Correctional Medicine were cited for
distinction. He served as a member of the NCCHC–NIJ expert panel on communicable disease.
B. JAYE ANNO, Ph.D., CCHP–A, is a criminologist specializing in correctional health administration
and compliance with national correctional health care standards. She operates a correctional health care
consulting firm. Dr. Anno is an experienced researcher, lecturer, and author in correctional health care.
She is the principal author of the major reference book for the field, Prison Health Care: Guidelines
for the Management of an Adequate Delivery System, and has written numerous other articles and reports
on correctional health care topics. She is a past editor of the Journal on Correctional Health Care, and
writes a column, “Q & A on NCCHC Standards,” for the quarterly newspaper CORRECTCARE. Dr.
Anno received the Distinguished Service Award of the American Correctional Health Services Association and the NCCHC’s Award of Merit. In 1999, she received the “Award of Excellence in Correctional Health Care Communications” from the National Commission on Correctional Health Care. She
served on the steering committee of the NCCHC–NIJ project on The Health Status of Soon-To-BeReleased Inmates.
CARL C. BELL, M.D., FAPA, CCHP, FAC Psych, is president and chief executive officer, Community Health Council & Foundation, Inc, and a Clinical professor of psychiatry and public health,
University of Illinois. He is coprincipal investigator of the Chicago African-American Youth Health
Behavior Project, Health Research and Policy Center. He is a collaborator of the Chicago HIV Prevention and Adolescent Mental Health Project (CHAMP) and a coprincipal investigator of the Informed
Consent in Urban AIDS and Mental Health Research Project, University of Illinois Department of
Psychiatry. He is a founding and member and past board chairman of the National Commission on
Correctional Health Care. During his 30 years of psychiatric practice, Dr. Bell has published more than
200 articles on mental health issues. He is author of many publications, including Getting Rid of Rats:
Perspectives of a Black Community Psychiatrist and coauthor of Suicide and Homicide Among
Adolescents. He was a member of the Violence Against Women Advisory Council appointed by Janet
Reno, Attorney General, and Donna Shalala, Secretary, Department of Health and Human Services,
from 1995 to 2000. He served as a member of the NCCHC–NIJ expert panel on mental illness.
ERAN BELLIN, M.D., is the director of the Montefiore Medical Center Department of Outcomes
Analysis and Decision Support and an associate professor of epidemiology and social medicine at the
Albert Einstein College of Medicine. From 1974 to 1977, Dr. Bellin directed the Montefiore Rikers
Island Health Program, which provided ongoing medical care for approximately 100,000 inmates. He

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served as director of infectious disease services on Rikers from 1989 to 1994, developing the plans for,
and serving as consultant to, the 140-bed negative pressure respiratory isolation facility built in the jail.
His case control study published in 1993 in the Journal of the American Medical Association demonstrated the risk of clinical tuberculosis from incarceration in the New York City jail. He served as a
member of the NCCHC–NIJ expert panel on communicable disease.
ELISSA P. BENEDEK, M.D., is clinical professor of psychiatry at the University of Michigan Medical
Center. She is past president of the American Psychiatric Association (1990–91). She served as director
of research and training at the Center for Forensic Psychiatry in Ann Arbor, Michigan, for 25 years. The
center trains psychiatric fellows to work in correctional psychiatry and forensic psychiatry. Her research
interest focuses on violence and violent behavior in child, adolescent, and adult populations. She served
as a member of the NCCHC–NIJ expert panel on mental illness.
R. SCOTT CHAVEZ, M.P.A., PA–C, CCHP, is vice president for the National Commission on
Correctional Health Care and served as project coordinator for the NCCHC–NIJ The Health Status on
Soon-To-Be-Released Inmates project. Mr. Chavez’s responsibilities with NCCHC include technical
assistance on health care standards, quality improvement, risk management, and organizational development in correctional health care systems. Mr. Chavez is principal investigator for a CDC grant to the
NCCHC on “Hepatitis Curricula for Correctional Officers and Inmates.” He has authored chapters on
physician assistant utilization in corrections for Health Care Management Issues in Corrections and
Physician Assistant: A Guide to Clinical Practice. He has a master’s in public administration from the
University of Nebraska, Omaha, and is a Ph.D. candidate at the Health Services Division of Walden
University. His dissertation is on the differences, trends, and predictors of quality health care in public
and private correctional health care systems.
JOHN H. CLARK, M.D., M.P.H., CCHP–A, is the chief medical officer for the Los Angeles County
Sheriff’s Department. Dr. Clark graduated from Meharry Medical College in 1971 and trained at the
University of Southern California Medical Center and Martin Luther King Jr., General Hospital in Los
Angeles, California. He received a master’s in health services and hospital administration from the
University of California–Los Angeles. His professional activities include the American Correctional
Health Services Association (Past President), American Jail Association (Board of Directors), and he is
a Certified Correctional Health Professional–Advanced. Dr. Clark has published on a variety of topics
in the correctional health profession including managing tuberculosis, paraplegics, inmate selfmedication programs, and developing HIV disease policies for the correctional environment. He has
lectured nationally and has served as a consultant and expert witness dealing with civil rights litigation
related to correctional health care issues. He served as a member of the NCCHC–NIJ expert panel on
communicable disease.
THOMAS J. CONKLIN, M.D., CCHP–A, is director of health services at the Hampden County
Correctional Center in Ludlow, Massachusetts. He has developed a public health model of care for
corrections that effectively stresses assessment, effective treatment, education, prevention, and continuity
of care by referring inmates to their neighborhood health centers following discharge. Dr. Conklin is
board certified in psychiatry and is certified in administration by the American Psychiatric Association.
Dr. Conklin was the first chairman of the department of psychology and neurology in the Touro
Infirmary in New Orleans, Louisiana. He is a fellow of the American Psychiatric Association. He also
has numerous publications and presentations focusing on health care in hospitals and in corrections. He
served as a member of the NCCHC–NIJ expert panel on mental illness.

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CHERYL CRAWFORD, M.P.A., J.D., is Deputy Director, Office of Development and Communications, National Institute of Justice (NIJ). NIJ was established by Congress to develop and disseminate
knowledge that will reduce crime, enhance public safety, and improve the administration of justice. She
coordinates project management and integrative services for three divisions (Communications, Development, and International) in NIJ’s Office of Development & Communications. From 1987 to 1998, Ms.
Crawford managed NIJ’s correctional health care research and dissemination portfolio. She has spoken
and written extensively on correctional health care issues, including the impact of HIV/AIDS and TB in
corrections and the costs of correctional health care. She manages the Reentry Partnership Initiative, a
multiagency, multisite effort focused on transitioning offenders from prison to community; this effort
includes health components. She received her B.A. in criminal justice from the University of Wisconsin–
Platteville and her master’s in public administration and J.D. from the University of Wisconsin–Madison.
Ms. Crawford served as a member of the steering committee of the NCCHC–NIJ project on The Health
Status of Soon-To-Be-Released Inmates.
PHYLLIS E. CRUISE, B.A., received her B.A. in education in psychology from Southern Illinois
University. She has been employed at Centers for Disease Control and Prevention since 1978. She is
the senior public health advisor assigned to the Texas Department of Health Tuberculosis Elimination
Division. Ms. Cruise developed and implemented the Texas legislation that mandates TB screening for
staff and inmates. Ms. Cruise supervises the project that monitors the mandated screening activities, and
includes contact, followup, tracking and continuity of care of inmates and staff with active TB disease or
who have been exposed to active tuberculosis. Ms. Cruise is the author of Prevention and Control of
Tuberculosis in Correctional Facilities—Recommendations of the Advisory Council for the Elimination
of Tuberculosis. She has appeared as an expert panel member and developed national satellite programs,
training seminars, and videos addressing issues affecting the control of tuberculosis in correctional
facilities. She has also provided consultation to local, State, and Federal correctional agencies. She
served as a member of the NCCHC–NIJ expert panel on communicable disease.
HAZEL D. DEAN-GAITOR, Sc.D., M.P.H., earned her B.S. in biology from Spelman College and her
M.P.H. and Sc.D. from Tulane University School of Public Health and Tropical Medicine. She is an
epidemiologist at the Centers for Disease Control and Prevention (CDC) in the National Center for HIV,
STD, and TB Prevention. She is responsible for formulating, implementing, and evaluating CDC’s
national HIV/AIDS surveillance system among racial and ethnic minorities and special populations (e.g.,
incarcerated persons). She conducts complex statistical and epidemiological analyses of racial and ethnic
minorities and special populations collected through this surveillance system. She serves as the
HIV/AIDS Surveillance Branch’s primary technical resource on surveillance of racial and ethnic
minorities and special populations. Dr. Dean-Gaitor represents the CDC on the United States Department
of Health and Human Services Crisis Response Team to Combat HIV/AIDS in Racial and Ethnic
Minority Populations and the NCCHC–NIJ expert panels on communicable and chronic disease. She has
written or contributed to numerous reports, papers and presentations on HIV/AIDS, with special
emphasis on persons reported from correctional settings, trends among foreign-born persons with AIDS,
and AIDS in bisexual minority men.
ANNE DE GROOT, M.D., is the head of the TB/HIV research laboratory at the International Health
Institute, where she and colleagues are working on the development of HIV and TB vaccines. She
received her B.A. from Smith College in 1978 and her M.D. from the University of Chicago. She trained
in internal medicine at the New England Medical Center in vaccine research, and received her specialized
training in infectious diseases at the New England Medical Center. She is a faculty member of the Brown
University School of Medicine. Dr. De Groot has provided HIV care to incarcerated individuals at a
number of different corrections institutions since 1989. She founded and directed the HIV clinic at the

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Massachusetts Correctional Institution at Framingham. She also served on the Governor’s AIDS Task
Force. Dr. De Groot has been working on developing a standard of care for HIV-infected and at-risk
incarcerated women. She founded and cochairs the HIV Education Prison Project (HEPP) at the Brown
University AIDS Program, which publishes a monthly newsletter on HIV management in prisons and
jails that reaches more than 2,000 correctional HIV professionals. She served as a member of the
NCCHC–NIJ expert panel on communicable disease.
LORI DE RAVELLO, M.P.H., has more than 9 years of experience in international and domestic
public health program operations and management. Since 1996, she has worked as a public health advisor in the Division of Reproductive Health, National Center for Chronic Disease Prevention and
Health Promotion at the Centers for Disease Control and Prevention in Atlanta, Georgia. Her duties
include that of project officer for an HIV-prevention training intervention in U.S. reproductive health
settings, primary investigator for a retrospective research study looking at the reproductive health status
of pregnant inmates in the State of Georgia, and chair of the Cross-Center Corrections Work Group.
She has a bachelor’s degree in international relations/Latin American studies from the University of
New Mexico and a master’s degree in international public health with a concentration in administration
and management from the University of Alabama at Birmingham. She served as a U.S. Peace Corps
volunteer in Honduras from 1990 to 1991. Ms. de Ravello served as a member of the NCCHC–NIJ
expert panel on chronic disease.
PETER FINN, M.A., is a research associate at Abt Associates Inc. He received his B.A. in history from
Harvard College and M.A. in history from the University of California at Berkeley. The U.S. Department
of Justice, National Institute of Justice (NIJ), has published his series of reports on life skills programs
for prison and jail inmates and job placement programs for ex-offenders. In 2000, NIJ published his
book, Addressing Correctional Officer Stress: Programs and Strategies, a companion report to his study,
Developing a Law Enforcement Stress Program for Officers and Their Families, also published by NIJ.
Mr. Finn was part of the research team that visited prisons and interviewing health care administrators
and providers as part of Abt Associates’ comprehensive assessment of prison health services in Washington State. He served as technical writer for the NCCHC–NIJ The Health Status of Soon-To-BeReleased Inmates project.
JUARLYN L. GAITER, Ph.D., is a supervisory behavioral scientist in the Behavioral Intervention
Research Branch at the Center for Disease Control and Prevention. She received her master’s and Ph.D.
in experimental child psychology from Brown University and certification as a clinical psychologist at
the George Washington University. Dr. Gaiter initiated and established the first HIV/AIDS Prevention
research project for prison populations at the CDC. She has written and coauthored articles in this area
and has held a number of research and management positions during her 10-year career in public health.
Her research interests focus on maternal and child health, faith, health and healing, pediatric and
developmental psychology, and the effects of racism on health outcomes for African-Americans. She
served as a member of the NCCHC–NIJ expert panel on mental illness.
ANDREW L. GOLDBERG, M.A., is a social science analyst in the Office of Research and Evaluation
at the National Institute of Justice. He received his B.A. from Drew University in political science in
1990 and his M.A. from the University at Albany (NY) in criminal justice in 1992. At NIJ, Mr. Goldberg’s
areas of focus include correctional health care, sentencing, and adjudication research projects. He served
as a member of the steering committee of the NCCHC–NIJ The Health Status of Soon-To-Be-Released
Inmates project.

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RODERIC GOTTULA, M.D., is an assistant professor in the Department of Family Medicine at the
University of Colorado Health Sciences Center. He is immediate past president of the Society of
Correctional Physicians. He received his M.D. at the University of Nebraska College of Medicine in
1975, and completed his family medicine residency at Iowa Lutheran Hospital in Des Moines, Iowa, in
1978. From 1991 to 1995, Dr. Gottula served as the medical director for the Colorado Department of
Corrections. He has remained active in the area of health care and criminal justice. He has lectured at
national and local conferences on criminal justice and health care. He served as a member of the
NCCHC–NIJ expert panel on chronic disease.
ROBERT B. GREIFINGER, M.D., is a medical management consultant. His work focuses on the
design, management, quality improvement, and utilization management systems in managed care
organizations and correctional health care systems. He has extensive experience in the development and
management of complex community and institutional health care programs, and demonstrated strengths
in leadership, negotiation, communication, and the bridging of clinical and public policy interests. His
clients include managed care organizations and state and local correctional systems. He has a variety of
assignments as a court-appointed expert to investigate and design remedies for ailing correctional health
care systems. Dr. Greifinger has published extensively in the area of correctional health care. He is a
frequent speaker on public policy, communicable disease control and quality management in corrections.
He works closely with the National Committee for Quality Assurance (NCQA) and sits on a variety of
national health care advisory committees. Through NCCHC, Dr. Greifinger is the principal investigator
for the NIJ-funded project on The Health Status of Soon-To-Be-Released Inmates.
THEODORE M. HAMMETT, Ph.D., is a vice president at Abt Associates Inc., a leading policy
research firm with headquarters in Cambridge, Massachusetts. Dr. Hammett’s work has focused on
public health, corrections, and criminal justice. Since 1985, he has directed a series of nine national
studies of HIV/AIDS, STDs, and TB in correctional facilities under the joint sponsorship of NIJ and the
Centers for Disease Control and Prevention (CDC). He is coprincipal investigator of the evaluation and
program support center for seven grants to States for enhancement of HIV prevention, treatment, and
continuity of care in correctional settings. He is also directing an evaluation of the Hampden County
(Massachusetts) Correctional Center’s public health model of correctional health care. Dr. Hammett has
spoken before national and international conferences, testified before the National Commission on AIDS,
and participated in an invited consultation on HIV/AIDS in Prisons at the World Health Organization in
Geneva. He has published many books, articles, and reports on HIV/AIDS, TB, and STDs as they affect
criminal justice agencies, inmates, and drug-involved populations. Dr. Hammett served as a member of
the NCCHC–NIJ expert panel on communicable disease.
EDWARD A. HARRISON, M.M., CCHP, is president of the National Commission on Correctional
Health Care, overseeing a not-for-profit organization that develops programs and policies aimed at
improving the delivery and quality of health services in detention and correctional facilities throughout
the United States. He has spoken and written extensively on public health and correctional health care
matters, addressing State legislatures, county commissioners, the United States Congress, and public and
private local, State, and national agencies. In advocating higher quality correctional medical services, Mr.
Harrison has focused the NCCHC’s resources on improved standards for health services delivery, more
educational opportunities and better recognition for correctional health care professionals, increased
quality assessment and improvement programs for the field, and greater research and better understanding of all aspects of correctional health care. He earned his master’s of management from Northwestern
University’s J.L. Kellogg Graduate School of Management. Mr. Harrison served as a member of the
steering committee for the NCCHC–NIJ project on The Health Status of Soon-To-Be-Released Inmates.

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HOLLY A. HILLS, Ph.D., is an associate professor in the department of community mental health at the
Louis de la Parte Florida Mental Health Institute, University of South Florida (USF). She is a licensed
clinical psychologist who received her Ph.D. in clinical and health psychology from the University of
Florida. Since joining the USF faculty in 1990, Dr. Hills has conducted research and supervised clinical
work that focused on individuals with comorbid mental illness and substance use disorders. Over much
of the past decade she has worked with the Florida Department of Corrections as a lead consultant in the
development and evaluation of prison-based residential treatment programs for male and female inmates
with co-occurring disorders. Dr. Hills has been a collaborator and consultant on the national GAINS
Center project, a Federal partnership that promotes improved services for people with co-occurring
disorders in the justice system. Her recent efforts include being awarded funds by the Center for
Substance Abuse Treatment (CSAT) as a coinvestigator to develop a practice and research collaborative
(PRC) in the Tampa Bay area. This initiative seeks to improve collaboration among researchers,
practitioners, policymakers, and criminal justice personnel who work with substance-involved individuals
in the justice system. Dr. Hills served as a member of the NCCHC–NIJ expert panel on mental illness.
MARTIN F. HORN, M.A., is the former Pennsylvania Secretary of Corrections since his nomination
by Governor Tom Ridge in February 1995. He has 30 years of varied corrections experience, having
served as a parole officer, senior parole officer, director of parole operations and executive director and
chief operating officer for the New York State Division of Parole. He also was assistant professor of
criminal justice at State University College at Utica, N.Y. Mr. Horn served as director of temporary
release, assistant commissioner, and prison superintendent for the New York Department of Correctional
Services. He earned a bachelor’s in government from Franklin and Marshall College in Lancaster,
Pennsylvania, and a master’s in criminal justice from John Jay College, City University of New York.
He serves as vice chairman of the Law Enforcement and Corrections Technology Advisory Committee,
and is a member of the American Correctional Association, the Association of State Corrections Administrators and the Pennsylvania Prison Wardens Association. Mr. Horn served as a member of the
NCCHC–NIJ expert panel on mental illness.
CARLTON A. HORNUNG, Ph.D., M.P.H., is professor of medicine, director of the Center for
Epidemiology and Clinical Investigation, and director of the Clinical Research, Epidemiology, and
Statistics Training Program at the University of Louisville School of Medicine. Dr. Hornung completed
his bachelor’s at the State University of New York at Buffalo, his master’s and Ph.D. degrees at the
Maxwell Graduate School of Syracuse University, and his postdoctoral and master’s of public health
training at the Johns Hopkins University. Before moving to the University of Louisville in 1997, Dr.
Hornung was professor of medicine and adjunct professor of epidemiology and biostatistics at the
University of South Carolina. He has served as visiting professor of medicine at the University of
Medicine and Pharmacy in Cluj-Napoca, Romania, and as member of the Romanian National Advisory
Committee on Cardiovascular Disease. His research interests focus on atherosclerotic vascular disease.
He was a vanguard investigator for the NIH Antihypertensive, Lipid Lowering to Prevent Heart Attack
Trial (ALLHAT) and a coinvestigator in the New Approaches to Coronary Intervention (NACI) Registry.
He has authored or coauthored more than 70 peer-reviewed publications and more than 200 abstracts.
Dr. Hornung served as a member of the NCCHC–NIJ expert panel on chronic disease.
T. STEPHEN JONES, M.D., M.P.H., has been the associate director for science of the Centers for
Disease Control and Prevention (CDC), Division of HIV/AIDS Prevention—Intervention Research and
Support since 1997 and has been the special assistant for substance abuse and HIV prevention in the
Division of HIV/AIDS Prevention since 1990. He has worked on HIV prevention related to drug injection
since 1987, with major interests in HIV serologic studies of injection drug users (IDUs), HIV counseling
and testing in drug treatment programs, evaluation of syringe exchange programs, and making sterile
injection equipment more available to IDUs. From 1979 to 1987, he worked on CDC international health

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programs promoting childhood immunization in Latin America and child survival programs in Africa. He
participated in the World Health Organization’s smallpox eradication programs in India, Bangladesh, and
Somalia. He received his M.D. from Columbia University, and his M.P.H. at the University of Michigan.
Dr. Jones served as a member of the NCCHC–NIJ expert panel on communicable disease.
CAPTAIN NEWTON KENDIG, M.D., Medical Director, Federal Bureau of Prisons (BOP), began his
career with the Bureau of Prisons as the chief physician and the chief of infectious diseases at the Central
Office in 1996. Before transferring to the BOP, Captain Kendig was the medical director of the Maryland
Division of Corrections from 1991 to 1996. He completed his internship/residency in internal medicine at
the University of Rochester Strong Memorial Hospital in Rochester, New York, in 1986. He completed
his fellowship in infectious diseases at Johns Hopkins University in Baltimore, Maryland, and was a
clinical associate of the U.S. Public Health Service at the National Institute of Aging, National Institutes
of Health, Baltimore, Maryland. Captain Kendig has received numerous awards, including Outstanding
Service Medal 1998, Outstanding Unit Citation 1998, Commendation Medal 1997, Unit Commendation
1997, and Alpha Omega Alpha Honor Society 1983. Captain Kendig served as a member of the
NCCHC–NIJ expert panel on communicable disease.
LAMBERT N. KING, M.D., Ph.D., is the medical director and senior vice president for medical and
academic affairs of St. Vincent’s Hospital and Medical Center of New York. He is also vice dean and
professor of clinical community and preventive medicine at New York Medical College. Dr. King
received his B.A. in the honors program from the University of Kentucky where he was elected to Phi
Beta Kappa. Dr. King received his M.D. and Ph.D. in experimental pathology from the University of
Chicago in 1971. He completed a residency in internal medicine at Cook County Hospital in 1974 and is
a Diplomate of the American Board of Internal Medicine. He is a Fellow of The New York Academy of
Medicine. Dr. King has made numerous presentations and published extensively concerning health care
delivery needs and systems in jails and prisons. He contributed to the identification of B19 parvovirus as
a treatable cause of aplastic anemia in patients with HIV infection. Dr. King has been a consultant or
director for numerous advisory boards and committees and has served as a member of a court-appointed
physician panel and as special master reviewing the medical care provided at Menard Correction Center
in Illinois. He has served as cochairman of the New York State AIDS Center Liaison Committee since
1988 and the New York AIDS Center Advisory Committee since 1997. Dr. King served as a member of
the NCCHC–NIJ expert panel on chronic disease.
JULIE R. KRAUT, Ph.D., is a prevention effectiveness postdoctoral fellow at the Centers for Disease
Control and Prevention. She received her Ph.D. in economics from Pennsylvania State University in
1998. She is based in a health services research and evaluation group in the Division of Sexually
Transmitted Diseases (STD) Prevention. During her tenure at CDC, she has conducted economic and
demographic analyses of access to care and health care utilization issues, and taught economic analysis
methods including cost-benefit, cost-effectiveness, and cost-utility analysis methods. Dr. Kraut was a
facilitator for the preconference skill-builder at the Prevention ’99 Conference and for the Prevention
Effectiveness Methods Course taught at CDC. Dr. Kraut presented at the 1999 Population Association of
America Meeting and did a poster presentation at the 1999 International Society for Sexually
Transmitted Diseases Research Meeting. Her work on estimating the costs and benefits of various
screening and treatment strategies for STDs in incarcerated populations resulted in her serving as a
consultant to the NCCHC–NIJ expert panel on communicable disease.
ROBERT LYERLA, Ph.D., is an epidemiologist in the Hepatitis Branch, Division of Viral and Rickettsial Diseases at the Centers for Disease Control and Prevention. He received his B.S. in biochemistry
from Bradley University, and his Ph.D. in Statistics from Southern Illinois University. He is a former
member of the CDC’s Epidemic Intelligence Service, Class of 1995, serving in Russia (diphtheria

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epidemic), Copenhagen, and Madrid as well as with the Atlanta Olympic Games Health Staff. His
research focuses on hepatitis in dialysis units, among injecting drug users, incarcerated individuals,
and other high-risk groups. He is an officer in the Commissioned Corps of the United States Public
Health Service. Dr. Lyerla served as a member of the NCCHC–NIJ expert panel on communicable
disease.
MAUREEN MANGOTICH, M.D., M.P.H., is a medical director for Pfizer Health Solutions (PHS).
She works on clinical content development for a proprietary disease management application and other
custom development projects and provides clinical sales and implementation support for PHS disease
management programs. Before joining Pfizer, Dr. Mangotich developed procedure-based appropriateness
guidelines at Value Health Sciences (now Protocare Sciences). Her medical management experience
includes positions at Health Alliance Plan (associate medical director for quality improvement) and
Aetna Health Plans (corporate medical director for provider quality). She frequently lectures on quality
improvement in health care. She has been a National Committee for Quality Assurance (NCQA) surveyor
since 1991, is a member of the NCQA Review Oversight Committee (ROC), and serves on the planning
committee and faculty for NCQA’s Credentialing and Delegation conferences. Dr. Mangotich is a boardcertified general internist who completed her internal medicine residency and a master’s in public health
at University of California, Los Angeles. She received her M.D. from the University of Arizona. She
served as a member of the NCCHC–NIJ expert panel on chronic disease.
FRED A. MARTICH has been the deputy chief of the Behavioral Interventions and Research Branch,
Division of STD Prevention, Centers for Disease Control and Prevention in Atlanta, Georgia, since
October 1998. He has served as chairman of CDC’s Cross Centers Correctional Work Group and is a
member of the Planning Committee for this group. Before this position, he was deputy chief of HIV
Prevention Operations for 2 years. Before that, he served as project officer for STD/HIV prevention with
State health departments and community-based organizations for 10 years. He worked in STD prevention
field assignments with CDC for 23 years in Ohio, Chicago, Wisconsin, and Alabama. He received his
B.S. from Duquesne University in Pittsburgh, Pennsylvania, and attended graduate studies in public
administration at Oshkosh University in Oshkosh, Wisconsin. He served as a member of the
NCCHC–NIJ expert panel on communicable disease.
ERIC E. MAST, M.D., M.P.H., is chief of the Surveillance Unit and acting chief of the Prevention
Research Unit in the Hepatitis Branch at the Centers for Disease Control and Prevention. He received his
A.B. in Biology at the University of Illinois in Urbana, his M.D. at the University of Illinois in Chicago/
Peoria, and his M.P.H at the Harvard School of Public Health. His postgraduate training included a
pediatric residency at the University of Wisconsin and a preventive medicine residency at the Centers for
Disease Control and Prevention (CDC). From 1985 to 1987, he was medical program director for Save
the Children in UmRuwaba, Sudan. He joined the CDC in 1987 as an epidemic intelligence service
officer and he has worked in the Hepatitis Branch since 1990. He has published numerous articles on the
epidemiology and prevention of viral hepatitis. Dr. Mast served as a member of the NCCHC–NIJ expert
panel on communicable disease.
W. PAUL MCKINNEY, MD, is the V.V. Cooke Professor of Medicine and chief of the Division of
General Internal Medicine and Geriatrics, Department of Medicine, at the University of Louisville. He is
also the director of the Center for Health Services and Policy Research and acting director of the Institute
for Public Health Research at that institution. Dr. McKinney completed his M.D. at the University of
Texas/Southwestern Medical School at Dallas and his internship and residency at the University of
Minnesota, Minneapolis-St. Paul. From 1996 through 1999, he was editor of the SGIM Forum, the
national newsletter for the Society of General Internal Medicine, and served as an ex officio member
of its council. In 1999, he also served as a U.S. Public Health Service Primary Care Policy Fellow

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representing SGIM. He has active interests in health services research and research involving medical
informatics, clinical epidemiology, and preventive services delivery. Since 1998, Dr. McKinney has been
a liaison member of the Advisory Committee on Immunization Practices of the Centers for Disease
Control and Prevention. He served as a member of the NCCHC–NIJ expert panel on chronic disease.
JOHN R. MILES, B.A., M.P.A., is the Special Assistant for Corrections and Substance Abuse, Office
of the Director, National Center for HIV/AIDS, STD and TB Prevention. His assignments as a public
health advisor with CDC span a career of 33 years and have included diverse public health program
development and management experiences from grassroots community crossroads to the large urban
centers of Chicago and New York City. Before his assignment with CDC in Atlanta, he spent 12 years
with the New York City Department of Health as Program Coordinator of STD Control, AIDS Program
Director, and Assistant Director and Director of the Bureau of STD Control. As Special Assistant for
Corrections and Substance Abuse, he works to develop and strengthen effective intra-agency
collaborations between the Department of Health and Human Services and Department of Justice
agencies, and national, State, and local organizations to effect policies that will improve access and
continuity of care for HIV, STD, and TB among drug users and incarcerated populations. Mr. Miles
received his master’s of public administration from Baruch College, City University of New York, and a
B.A. from the University of Kansas. He served on the steering committee of the NCCHC– NIJ project on
The Health Status of Soon-To-Be-Released Inmates.
MARILYN C. MOSES, M.S., has been a social science program analyst with the National Institute
of Justice (NIJ) since June 1991. Ms. Moses has been the NIJ program manager for The Health Status of
Soon-To-Be-Released Inmates project. Ms. Moses has a bachelor’s in paralegal studies from the
University of Maryland and a master’s in criminal justice from the University of Baltimore. She is
working on a second master’s in publication design. Ms. Moses specializes in correctional health care,
female offenders, children of incarcerated parents, correctional industry enhancement, the development
of public-private criminal justice partnerships, correctional training and education, offender job training
and placement, offender reentry, mental health in corrections, correctional officer stress, and rural crime
and policing and has published widely in these areas. Ms. Moses was cited as one of the “Best in the
Business” by the American Correctional Association for her work on behalf of children of incarcerated
parents. She is the creator and editor for Civic Research Institute's Offender Employment Report—a firstof-its-kind publication that is published six times per year. She served on the steering committee of the
NCCHC–NIJ project on The Health Status of Soon-To-Be-Released Inmates.
PRADAN A. NATHAN, M.D., is the associate division director for health services at the Texas
Department of Criminal Justice. He received his medical degree from Madurai University Medical
College in India. He completed residencies in psychiatry at the National Institute of Mental Health and
Neurosciences in India and the Texas Research Institute of Mental Sciences at Houston, Texas, and he
completed a fellowship in forensic psychiatry at University Hospitals, Cleveland, Ohio. Dr. Nathan has
worked in court psychiatric clinics, community mental health centers and state hospital systems, and
private practice. He has been associated with the Texas Department of Criminal Justice as a unit psychiatrist, a regional psychiatrist, and a clinical director of a 550-bed psychiatric inpatient unit. He is an
instructor in institutional and correctional health, Departments of Preventive Medicine and Community
Health at University of Texas Medical Branch at Galveston. He is board certified in general psychiatry
and forensic psychiatry by the American Board of Psychiatry and Neurology. Dr. Nathan served as a
member of the NCCHC–NIJ expert panel on mental illness.
MARGARET J. OXTOBY, M.D., is director of the Bureau of Tuberculosis Control at the New York
State Department of Health. Since coming to the TB Program in 1993, she has worked closely with the
New York State Department of Correctional Services in developing effective TB prevention and control

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activities in the state prison system. She received her B.A. from Harvard University and her M.D. from
Case Western Reserve University. She completed a pediatric residency at Duke University and a preventive medicine residency at the Centers for Disease Control and Prevention, where she worked as a
medical epidemiologist focusing first on bacterial diseases and later on pediatric AIDS. Dr. Oxtoby
served as a member of the NCCHC–NIJ expert panel on communicable disease.
JOSEPH E. PARIS, Ph.D., M.D., CCHP, obtained his M.D. from Boston University and is board
certified in internal medicine. He began his career in correctional medicine in 1985 in the Florida
Department of Corrections. In 1995, he came to the Georgia Department of Corrections in Atlanta and
became statewide medical director. Dr. Paris is a founding member and the 1999–2000 President of the
Society of Correctional Physicians. He is a past president of the Florida Chapter of the American
Correctional Health Services Association (ACHSA), a Certified Correctional Health Professional, and
the author of more than 50 specialized correctional publications or national presentations, including three
chapters in Clinical Practice in Correctional Medicine. He organized and hosted the 1999 ACHSA
Multidisciplinary Conference in Atlanta, Georgia. Dr. Paris served as a member of the NCCHC–NIJ
expert panel on chronic disease.
MICHAEL PUISIS, D.O., is corporate medical director for Addus HealthCare’s Correctional Division.
He is the editor of Clinical Practice in Correctional Medicine. He participated on the task force for
standards revision for the 1996 NCCHC jail standards and served on the committee to revise the correctional health care standards for the American Public Health Association. Dr. Puisis served as a member
of the advisory board for the evaluation of the Centers for Disease Control and Prevention guidelines for
TB control in jails in 1999. Dr. Puisis served as a member of the NCCHC–NIJ expert panel on chronic
disease.
DIANNE RECHTINE, M.D., CCHP–A, is a medical executive director for the Florida Department of
Corrections. Her duties include managing the health care for approximately 15,000 offenders housed in
several major institutions. Dr. Rechtine received her undergraduate and medical education at West
Virginia University. She is a Fellow of the American Academy of Family Physicians and practiced in
southwest Florida before coming to work for the prison system 14 years ago. She has been a physician
surveyor for the National Commission on Correctional Health Care for several years and serves on their
Surveyor Advisory Committee. She has served as a member of the Standards Revision Committee for the
American Correctional Association. Dr. Rechtine is a charter member of the Society of Correctional
Physicians and serves as chairman of the Council of Chapters of the American Correctional Health
Services Association. She is certified as a Correctional Health Professional and has achieved Advanced
status. She is chairman of the Florida Department of Corrections Continuing Medical Education, was
chairman of the Committee for Chronic Care, and has been a faculty member of the Mini-Residency
Program for Correctional HIV since its inception. Dr. Rechtine served as a member of the NCCHC–NIJ
expert panel on chronic disease.
BETTY RIDER, M.A., M.S., is director of managed care services for the North Carolina Division of
Prisons Health Services Section. Her correctional health care experience includes senior management
positions with major national managed care companies providing health care to correctional facilities and
the uniformed services. In 1999, Ms. Rider served on the joint CDC–National Tuberculosis Center task
force that developed new guidelines for TB education/training in corrections. She is an associate editor
of HEPP News, a national journal published by the Brown University School of Medicine’s Correctional
HIV Program. She has presented and published extensively on correctional managed care issues,
pharmacoeconomics of antiretroviral therapies, and correctional health care delivery systems. Ms. Rider
received an M.S. in healthcare administration from Trinity University, an M.A. in counseling psychology
from Eastern Kentucky University, and a B.A. in social science/economics from Trinity University. She

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is a member of the American Correctional Association, the American Correctional Health Services
Association, the American College of Health Care Executives, and the Healthcare Financial Management
Association. She is a member of the National Minority HIV Council’s advisory board and served as a
member of the joint NCCHC–NIJ communicable disease expert panel on The Health Status of Soon-ToBe-Released Inmates.
CLYDE B. SCHECHTER, M.A., M.D., is director of medical education and associate professor in the
Department of Community and Preventive Medicine at Mount Sinai School of Medicine in New York
City. He received his B.A and M.A. in mathematics and his M.D. from Columbia University. He is board
certified in internal medicine, general preventive medicine, and public health and has published extensively on simulation modeling of screening and treatment of chronic diseases including hypertension,
tuberculosis, and cervical cancer. His research interests focus on mathematical models of health processes,
and cost-effectiveness analysis, particularly as applied to population screening. He has served on the
editorial boards of Medical Decision Making and the Mount Sinai Journal of Medicine, and is a regular
reviewer of research grants submitted to the National Board of Medical Examiners. He has been a
consultant to many corporations on aspects of health benefit management. Dr. Schechter served as an
expert consultant to the NCCHC–NIJ expert panel on chronic disease.
GEORGE P. SCHMID, M.D., M.Sc., is assistant branch chief for Science, Program Development, and
Support Branch, Division of STD Prevention, Center for HIV, STD, and TB Prevention, Centers for
Disease Control and Prevention (CDC). He is a subspecialist in infectious diseases, with training in
internal medicine and family medicine, and has a M.Sc. in Health Services Management from the London
School of Hygiene and Tropical Medicine. Dr. Schmid has spent 20 years at CDC, the past 16 in the
Division of STD Prevention. He has considerable experience in the epidemiologic, clinical, laboratory,
programmatic and economic aspects of STD prevention. His position centers on the transfer of research
findings into clinical practice. He is the coordinating editor of the STD Collaborative Review Group
within the Cochrane Collaboration; section editor on sexual health, Clinical Evidence; and chairman,
CDC Institutional Review Board for Emergency Response. Dr. Schmid served as a member of the
NCCHC–NIJ expert panel on communicable disease.
RONALD M. SHANSKY, M.D., M.P.H., is a consultant in correctional medicine and the Federal
court-appointed receiver for medical and mental health services for the Washington, D.C., jail.
He received his B.S. in philosophy at the University of Wisconsin and his M.D. from the Medical
College of Wisconsin. He has obtained a master’s in public health and is Board certified in internal
medicine and quality assurance. He has been a surveyor for the JCAHO and is a board member of the
National Commission on Correctional Health Care (NCCHC). Dr. Shansky is a Fellow of the Society of
Correctional Physicians and was the first recipient of the Society’s Armond Start Award for Excellence
in Correctional Medicine. He is an associate editor and contributor to the textbook The Clinical Practice
of Correctional Medicine. He served as a member of the NCCHC–NIJ expert panel on chronic disease.
JONATHAN SHUTER, M.D., is the director of clinical research in the AIDS Center of Montefiore
Medical Center. He received his M.D. from Boston University School of Medicine. He is a member of
the Division of Infectious Diseases in the Department of Medicine at Montefiore Medical Center and is
an assistant professor of internal medicine at the Albert Einstein College of Medicine. Dr. Shuter was
the director of infectious diseases for Rikers Island Health Services between 1994 and 1997. He has
published a number of articles pertaining to tuberculosis, sexually transmitted diseases, and HIV
infection in the correctional setting. In 1998–99, Dr. Shuter served as an expert consultant to the
NCCHC–NIJ expert panel on communicable disease.

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HAL SMITH is the executive director and chief executive officer of Central New York Psychiatric
Center and its satellite mental health clinics that provide a comprehensive system of mental health
services to the New York State and local correctional systems. He is associate professor of administrative
psychiatry at the SUNY Upstate Health Science Center and adjunct professor of law at the Syracuse
University College of Law. He was director of forensic services for the New York State Office of Mental
Health and has held a variety of clinical and administrative positions in forensic and correctional mental
health settings. He provides mental health/criminal justice consultation services. He was appointed to the
NCCHC–NIJ expert panel on mental illness.
ANNE SPAULDING, M.D., graduated from Brown University and Medical College of Virginia. After
a residency at Brown, she moved on to a fellowship in infectious diseases at the University of Massachusetts Medical Center, Worcester, Massachusetts, where she pursued bench research in flaviviruses.
She is now on the staff at Rhode Island Hospital and attends in an HIV clinic. She is a clinical assistant
professor at Brown University School of Medicine. She also serves as the medical program director for
the Rhode Island Department of Corrections. Dr. Spaulding is president-elect of the Society of Correctional Physicians. Dr. Spaulding served as a member of the NCCHC–NIJ expert panel on communicable
disease.
HENRY T. STEADMAN, Ph.D., is president of Policy Research Associates, Inc. Previously Dr.
Steadman ran a nationally known research bureau for 17 years for the New York State Office of Mental
Health. His work has resulted in 6 books, over 100 articles in a wide range of professional journals, 18
chapters, and many reports. Dr. Steadman’s major research focus is persons with co-occurring disorders
in the justice system, violence risk assessment, homelessness and mental illness, and women and cooccurring disorders. Dr. Steadman received his B.A. and M.A. in sociology from Boston College and his
Ph.D. in sociology from the University of North Carolina at Chapel Hill. In 1987, Dr. Steadman received
the Amicus Award from the American Academy of Psychiatry and the Law. He also received the Philippe
Pinel Award from the International Academy of Law and Mental Health in 1988, the Saleem A. Shah
Award in 1994 from the State Mental Health Forensic Directors, the 1998 Distinguished Contribution to
Forensic Psychology from the American Academy of Forensic Psychology, and the 1999 Isaac Ray
Award from the American Psychiatric Association for his outstanding contributions to the psychiatric
aspects of jurisprudence. Dr. Steadman served as a member of the NCCHC–NIJ expert panel on mental
illness.
STEVEN SZEBENYI, M.D., is the former head of the Division of HIV Medicine and professor in the
Department of Medicine at Albany Medical College in Albany, New York. He was also director of the
AIDS Treatment Center at Albany Medical Center Hospital and medical director of the correctional
health program at Albany Medical Center. He was extensively involved with HIV/AIDS education
programs for correctional health practitioners, including a nationally broadcast videoconference series,
an HIV fellowship program, a telemedicine project and frequent lecturing. Dr. Szebenyi was a member of
the New York State Department of Health AIDS Institute Medical Care Criteria Committee and the New
York State Department of Correctional Services HIV Practice Guidelines Committee. He is medical
director for Blue Shield of Northeastern New York in Albany, NY. He served as a member of the
NCCHC–NIJ expert panel on communicable disease.
ZACHARY TAYLOR, M.D., M.S., is chief of the Prevention Effectiveness Section, Division of
Tuberculosis Elimination, National Center for HIV, STD, and TB Prevention, Centers for Disease
Control and Prevention. He received his B.S. in chemistry at LaGrange College, his M.S. at the
University of Maryland at Baltimore, and his M.D. at the Medical College of Georgia. His research
interests focus on the cost-effectiveness of screening for tuberculosis and evaluation of tuberculosis

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control programs. Dr. Taylor served as a member of the NCCHC–NIJ expert panel on communicable
disease.
LINDA A. TEPLIN, Ph.D., is professor of psychiatry and director of the Psycho-legal Studies Program
at Northwestern University Medical School. She received her Ph.D. from Northwestern University in
1975. She has done research on the criminalization of the mentally ill, epidemiologic characteristics of
jail detainees, and correlates of violence. Her honors include the American Psychological Association’s
career award for “Distinguished Contributions to Research in Public Policy” (1992), the MERIT Award
from the National Institute of Mental Health (1995), and the Young Scientist Award from the National
Alliance for the Mentally Ill (1990). Dr. Teplin is conducting two studies: the Northwestern Juvenile
Project and the Northwestern Victimization Project. The Northwestern Juvenile Project is a longitudinal
study of a sample of 1,800 youth who previously had been subjects in a study of juvenile detainees. The
project examines the changing alcohol, drug, and mental health service needs of these high-risk youth,
their use of services, and the behaviors that put them at increased risk for violence, IV drug use, and
HIV/AIDS. The Northwestern Victimization Project is a unique study of criminal victimization patterns
among severely mentally ill persons who live in the community. Both studies are funded by a consortium
of Federal agencies and private foundations. Dr. Teplin served as a member of the NCCHC–NIJ expert
panel on mental illness.
DAVID L. THOMAS, M.D., J.D., began his correctional career as an institutional physician, later as a
regional physician and the Chief of Clinical Services, and is now the Director of Health Services, all
within the Florida Department of Corrections. From 1984 until 1994, he was a member of the Florida
House of Representatives and served as the Republican Whip for 6 years. Dr. Thomas is a Vietnam
veteran who achieved the rank of Permanent Captain (Acting Major) in the U.S. Army and was awarded
the Bronze Star. Dr. Thomas has published two novels on drug smuggling in Florida and the Gulf Coast,
and has been lead author on several publications in peer-reviewed medical journals. Dr. Thomas served
as a member of the NCCHC–NIJ communicable disease expert panel.
DONNA TOMLINSON, M.D., M.Sc., is a research fellow in preventive cardiology at Beth Israel
Medical Center in New York. She graduated from St. George’s University, School of Medicine in 1996.
She completed a preventive medicine residency at Mount Sinai Medical Center and received her M.Sc. in
community medicine from Mount Sinai School of Medicine in 1999. She is board certified in general
preventive medicine and public health. Her clinical interest is in the prevention of cardiovascular disease
through lifestyle modifications. Her research interests are in simulation modeling and cost-benefit
analysis. Dr. Tomlinson served as a consultant on the NCCHC–NIJ expert panel on chronic disease.
BEENA VARGHESE, Ph.D., is a health economist with the Division of HIV/AIDS Prevention at the
Centers for Disease Control and Prevention. She is also member of the International Health Economic
Association and Cochrane Economics Methods Group. She received her M.S. in agriculture economics
from North Dakota State University in 1993 and her Ph.D. in health economics from the University of
Memphis in l997. In 1997–98, she was a short-term consultant for UNAIDS, Geneva, and the Ministry of
Health, Kazakhstan. She has presented her work at various national and international conferences. Her
research interests include decision analysis, cost-effectiveness and prevention effectiveness methods. Dr.
Varghese served as a consultant to the NCCHC–NIJ expert panel on communicable disease.
BONITA M. VEYSEY, Ph.D., is an assistant professor in the Rutgers University School of Criminal
Justice and the director of the Center for Justice and Mental Health Research. Dr. Veysey worked as a
researcher in mental health services and corrections policies for 15 years before joining the Rutgers
faculty. She served as both the associate director and the director of the Women’s Core of the National

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GAINS Center for Persons with Co-occurring Disorders in the Criminal Justice System. She has participated in several national advisory groups on issues relating to the supervision and treatment of offenders’
mental illnesses. Her research interests include interactions between the mental health and criminal
justice systems, correctional supervision of female offenders, and public health risks as they relate to
continuity of care. She received her doctorate in sociology from the State University of New York at
Albany in 1993. Dr. Veysey served as a consultant to the NCCHC–NIJ expert panel on mental illness.
RICH VOIGT, M.A., is assistant to the branch chief, Division of STD Prevention, Centers for Disease
Control and Prevention. He received his M.A. in sociology at Wichita State University, Wichita, Kansas.
His program interests focus on providing technical assistance for implementing early health screening
and treatment services for incarcerated people. He served as a member of the NCCHC–NIJ expert panel
on communicable disease.
HENRY C. WEINSTEIN, M.D., is the director of the program in Psychiatry and the Law at New York
University Medical Center and the Bellevue Hospital Center. For more than 20 years, he was the director
of the Forensic Psychiatry Service (the psychiatric prison ward) at Bellevue. He represents the American
Psychiatric Association on the Board of Directors of the National Commission on Correctional Health
Care and is the president of the Caucus of Psychiatrists Practicing in Criminal Justice Settings. He
chaired the APA Task Force that has recently revised the APA Guidelines on Psychiatric Services in Jails
and Prisons. Dr. Weinstein served as a member of the NCCHC–NIJ expert panel on mental illness.
LAURA WINTERFIELD, Ph.D., joined the Office of Research and Evaluation of the National Institute
of Justice in August 1997, where she managed the drug treatment portfolio and developed researcherpractitioner partnerships. She has been Division Director for the Justice Systems Divisions since midl999. From 1984 to 1993, she worked at the Vera Institute researching career criminals, evaluating
prosecutorial and court-based innovations, and assessing the appropriateness and effectiveness of New
York City's alternative-to-incarceration programs. From 1993 to 1997, she worked at the New York City
Criminal Justice Agency. She developed a release-on-recognizance prediction tool for adult court
arraignment judges and predictive tools for identifying offenders most likely to receive a sanction within
the range targeted for an alternative disposition. She has been actively involved in all aspects of criminal
justice research since the early 1970s, including courts, field services, alternatives to incarceration, and
treatment approaches. Her areas of expertise include delinquency and crime prevention, the development
of prediction models for criminal justice decisionmaking, estimating the impacts of diversion programs
on incarceration, and evaluation research. She received her Ph.D. in sociology from the University of
Colorado. Dr. Winterfield served on the steering committee of the NCCHC–NIJ project on The Health
Status of Soon-To-Be-Released Inmates.

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Appendix C: Information About the
National Commission on Correctional
Health Care and Its Position Statements
The National Commission on Correctional Health
Care (NCCHC) is a not-for-profit, 501(c)(3)
organization committed to improving the quality
of care in our nation’s jails, prisons, and juvenile
detention and confinement facilities. NCCHC is
supported by national organizations listed below
representing the fields of health, law, and
corrections.
In the early 1970s, the American Medical
Association (AMA) studied the conditions in
jails. Finding inadequate, disorganized health
services and a lack of national standards to guide
correctional institutions, the AMA in
collaboration with other organizations established
a program that eventually, in the early 1980s,
became the National Commission on Correctional
Health Care. NCCHC’s early mission was to
evaluate, formulate policy, and develop programs
for a floundering area clearly in need of
assistance.
Today, NCCHC’s leadership in setting standards
for health services and improving health care in
correctional facilities is widely recognized.
NCCHC’s Standards for Health Services are
written in separate volumes for prisons, jails, and
juvenile confinement facilities. The Standards
represent NCCHC’s recommended requirements
for the management of a correctional health
services system, covering the general areas of
care and treatment, health records, administration,
personnel, and medical and legal issues. The
Standards have helped the Nation’s correctional
and detention facilities improve the health of their
inmates, staff, and the communities to which they

return; increase the efficiency of their health
services delivery; and strengthen their
organizational effectiveness.
As well as establishing standards, each year
NCCHC sponsors correctional health care’s major
educational and scientific conferences. Each fall,
the annual National Conference on Correctional
Health Care draws physicians, nurses, psychologists, scientists, and other health care providers
and researchers to learn about contemporary
practices and issues in the field of correctional
health care. Each spring, the Clinical Updates
conference provides the latest information on
infectious and chronic disease research and
treatments, as well as other timely clinical issues
in correctional health care.
With a network of nationally recognized experts
in health care administration and delivery, NCCHC
offers an accreditation program for correctional
facilities that meet NCCHC standards, provides
technical assistance and quality improvement
reviews on correctional health care management
and policy issues, and develops and publishes
research on the correctional health care field. In
addition, NCCHC operates the national certification program for correctional health professionals,
sponsors other educational and training programs,
and publishes numerous support texts.
The members of the NCCHC volunteer Board of
Directors set policies and guide the organization’s
program efforts. Each is appointed to the board by
one of 34 supporting organizations.

222
American Academy of Child & Adolescent
Psychiatry
Louis Kraus, M.D.
American Academy of Pediatrics
James W.M. Owens, M.D., M.P.H., CCHP
American Academy of Physician Assistants
Peter C. Ober, PA-C, J.D., CCHP
American Academy of Psychiatry & the Law
Charles A. Meyer, Jr., M.D., CCHP-A
American Association of Physician Specialists
Jere G. Sutton, D.O.
American Association of Public Health
Physicians
Jonathan B. Weisbuch, M.D., M.P.H.
American Bar Association
Susan L. Kay, J.D.
American College of Emergency Physicians
William Haeck, M.D., CCHP
American College of Healthcare Executives
Eugene A. Migliaccio, Dr.P.H., CCHP
American College of Neuropsychiatrists
Bernard Feigelman, D.O.
American College of Physicians
John M. Robertson, M.D., M.P.H.
American Correctional Health Services
Association
JoRene Kerns, B.S.N., CCHP
American Counseling Association
Nancy B. White, L.P.C., M.A.C.
American Dental Association
Thomas E. Shields, II, D.D.S., CCHP
American Diabetes Association
Samuel Eichold, II B.S., M.D.

American Dietetic Association
Jenny Roper, M.S., R.D.
American Jail Association
Beverley Wilber
American Medical Association
Alvin J. Thompson, M.D., M.A.C.P., CCHP
American Nurses Association
Kleanthe Caruso, R.N., M.S.N., CCHP
American Osteopathic Association
George J. Pramstaller, D.O., CCHP
American Pharmaceutical Association
Robert L. Hilton, R.Ph., CCHP
American Psychiatric Association
Henry C. Weinstein, M.D., CCHP
American Psychological Association
Thomas J. Fagan, Ph.D.
American Public Health Association
Robert Cohen, M.D.
American Society of Addiction Medicine
H. Blair Carlson, M.D., CCHP
John Howard Association
Charles A. Fasano
National Association of County and City Health
Officials
Douglas A. Mack, M.D.
National Association of Counties
Kenneth J. Kuipers, Ph.D.
National District Attorneys Association
The Honorable Richard A. Devine
National Juvenile Detention Association
David W. Roush, Ph.D.

223
National Medical Association
Carl C. Bell, M.D., CCHP

Drug Testing of Correctional Staff
Health Care Funding for Incarcerated Youth

National Sheriffs’ Association
Sheriff Richard L. Warren

Health Services to Adolescents in Adult Facilities

Society for Adolescent Medicine
Ronald Feinstein, M.D.

Licensed Health Care Providers in Correctional
Institutions

Society of Correctional Physicians
Ronald M. Shansky, M.D.

Management of Hepatitis B in Correctional
Facilities

In addition to the standards, NCCHC periodically
adopts position statements that address issues of
importance in the management of health care in
corrections. The following are available as of the
date of this publication.

Management of Hepatitis C in Correctional
Facilities

Automated External Defibrillators in Correctional
Settings

Management of HIV in Correctional Facilities
Management of Tuberculosis in Correctional
Facilities
Mental Health Services in Correctional Settings

Charging Inmates a Fee for Health Care Services
Competency for Execution
Continuity of Care
Correctional Health Care and the Prevention
of Violence
DNA Analysis

Telemedicine Technology in Correctional
Facilities
Third Party Reimbursement for Correctional
Health Care
Women’s Health Care in Correctional Settings

National Commission on Correctional Health Care
1300 West Belmont Avenue
Chicago, Illinois 60657–3240
phone: (773) 880–1460
fax: (773) 880–2424
e-mail: ncchc@ncchc.org
www.ncchc.org

 

 

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