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1
Monitoring the Epidemic's Course
This chapter reviews the statistics and statistical systems that pro-
vide the nation with information about the current state and future
course of the AIDS epidemic.] To conduct this review, the committee
appointed a special pane] on statistical issues in AIDS research. The
material in this chapter constitutes the parent committee's finclings
after consideration of the technical panel's work.
The panel was asked to evaluate the adequacy of current statis-
tics (and those likely to be available in the near future) for assessing
the present state and monitoring the future course of the AIDS
epiclemic. Early on, the pane] conclucle(1 that a fully adequate moni-
toring system must go beyond the current system for reporting AIDS
cases and AIDS deaths. Rather, an adequate system of information
on the current state of the epidemic must provicle reliable monitoring
of the prevalence and incidence of HIV infection in the population.
Developing accurate statistical systems for monitoring HIV in-
fection is important for a number of reasons:
. Counts of AIDS cases are out-of-date indicators of the
present state of the epidemic. There is a Tong, asymp-
tomatic latency period between HIV infection and the
development of AIDS (in most persons). Consequently,
the statistics on new AIDS cases reflect old cases of HTV
infection. For example, most of the aclults who will be
1In this chapter, we focus on HIV and AIDS statistics. In Chapter 2, we discuss the
potential value of reliable statistics on other sexually transmitted diseases that should
(other things being equal) respond to the same behavioral changes that would reduce
the transmission of HIV.
31
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32 ~ UNDERSTANDING THE SPREAD OF HIV
counted as new AIDS cases in 1989 are likely to have
been infected with HIV prior to 1986.
. Persons whose life spans are significantly shortened by
HIV infection do not always manifest sufficient symbol
toms to be captured by the AIDS reporting system.
Thus, some persons crying of HIV-relatec! illnesses do not
qualify for inclusion in the statistics on AIDS deaths.2
HIV-infected persons without overt AIDS symptoms can
transmit the virus to others.
.
. The future magnitude of the AIDS epidemic will be
determined primarily by the current extent and future
spread of HIV infection in the population.
These considerations, and the fact that the AIDS reporting system is
functioning reasonably well (although not perfectly, as noted in the
following paragraphs), led the panel to concentrate its attention on
what is currently known about the prevalence ant! incidence of HIV
infection in the United States.
Notwithstanding this focus, the committee notes the need for
constant vigilance to ensure the efficient functioning of the AIDS case
reporting system. The time lag between the diagnosis of a case and
the reporting of it to the Centers for Disease Control (CDC) appears
to be increasing. At present, CDC estimates that only 85 to 90
percent of AIDS cases are reported within one year of diagnosis, and
2A review of death certificates in Boston, Chicago, New York, and Washington, D.C.,
during 1985 found that the reporting of AIDS cases (those meeting the 1985 surveillance
definition) was 89 percent complete; that is, in 89 percent of all AIDS deaths, the
decedent had already been included in the AIDS case registry. However, an additional
13 percent of deaths thought to be HIV related did not meet the CDC criteria for AIDS
diagnosis (Hardy et al., 1987~; that is, 13 percent of all deaths originally attributed to
AIDS, Pneumocpstis carinii, or Kaposi's sarcoma on the death certificate did not meet
the surveillance definition for AIDS but were judged "clinically suspicious" (p. 388)
because they had an opportunistic infection included in the surveillance definition but
the infection had not been confirmed by the required methods. It is also suspected that
such HIV-related deaths are responsible for an epidemic of non-AIDS deaths among
IV drug users in New York City. The eightfold increase in non-AIDS deaths (from
257 in 1978 to 1,607 in 1985) is presumed to be due to the fatal consequences of HIV
infection in cases that did not meet the surveillance definition for AIDS. Increases in
non-AIDS deaths among New York City IV drug users between 1981 and 1985 occurred
in the following HIV-related categories: pneumonia (not Pneumocystis carinii), from 15
to 193; tuberculosis, from 3 to 35; and endocarditis, from 4 to 64 (Des Jarlais et al.,
1988:155~.
Ultimately, some of these HIV-related deaths might be captured by the reporting system
through the use of the new HIV codes for classifying causes of death from death cer-
tificates. This assumes, of course, that the physician completing the certificate is aware
of the decedent's HIV status. In any event, even if this system were entirely reliable, it
would count people only at the point of death.
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MONITORING THE EPIDEMIC ~ 33
it is thought that this percentage is clecTining.3 Such a decline would!
be a reasonable consequence of the growing demands the epidemic is
making on the state and local public health departments that handle
AIDS surveillance and reporting. Indeed, the increasing delays noted
in the reporting of AIDS cases might be taken as direct evidence of
the stresses being placed on the personnel and institutions who must
cope with the epidemic. Additional resources appear to be needed
now (and more will probably need to be addec! incrementally in the
future) so that case reporting delays do not continue to increase.
The panel also identified a need for special methoclological stud-
ies to assess the reliability and validity of the categorization of AIDS
cases by mocle of transmission. Accurate data on transmission modes
are crucial because they identify the behaviors and populations that
must be targeted to control the spread of infection. Although some
careful work has been clone to explore the accuracy with which
such determinations are made, further research could provide much
valuable information. Given the difficulties in obtaining accurate in-
formation on sexual behavior (particularly in some subpopulations),
there is good reason to believe that some error and bias contaminate
the tabulation of AIDS cases by transmission mode. Methodological
studies to assess the magnitude and direction of such inaccuracies
could provide useful information that would air! in the interpretation
of the AIDS case data.4
PREVALENCE AND INCIDENCE OF
HIV INFECTION
Prevalence denotes that proportion of a population that is cur-
rently infected; it is usually expressed as cases per 1,000 or per
10,000, or it may be written as a percentage (e.g., 0.4 percent, or
4 cases per 1,000~. Incidence denotes the rate of occurrence of new
cases of infection per unit of time (e.g., per year). Thus, an incidence
of .03 per year in some population group means that new cases of
infection occurred in 3 percent of the initially uninfected members of
the group during the year in question. Incidence may be estimated
3The median reporting delay (i.e., the time from diagnosis to report) has, for exam-
ple, increased from 2 to 3 months in the past year (M. Morgan, Statistics and Data
Management Branch, AIDS Program, CDC, personal communication, September 26,
1988).
4These studies would be important to conduct even if they were to conclude that the
inaccuracies themselves were, in fact, inconsequential.
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34 ~ UNDERSTANDING THE SPREAD OF HIV
directly by tracking new cases (as can be done with AIDS) or indi-
rectly by observing changes in prevalence and adjusting for deaths
(as might be done with HIV).
In November 1987, CDC transmitted a report to the President
and his Domestic Policy Council that summarized in a clear, com-
prehensive fashion the state of present knowledge of HIV incidence
and prevalence (CDC, 1987b).5 The report performed a great service
in pulling together and organizing a massive amount of disparate in-
formation, much of which was unpublished. In summarizing current
knowledge, the report highlighter! the substantial gaps in our uncler-
standing of the HIV epidemic and made it quite clear that almost all
that is known about HIV incidence and prevalence comes from re-
search samples that have been recruited in a manner that precludes
generalizations to well-defined segments of the population. (Such
non-population-based samples are sometimes called "purposive" or
"convenience" samples.)
Uses of HIV Prevalence and Incidence Data
There are three important uses for reliable HIV prevalence and in-
cidence data. First, such ciata can be used to compare population
groups in terms of current HIV prevalence and, subsequently, to
target prevention services to those groups that are most in need.
Second, reliable HIV prevalence and incidence data can be helpful in
assessing the effects of prevention services ant! other interventions. A
third, less direct use of such data is in calibrating forecasting models.
These moclels in turn may allow us to better anticipate the future
course of the epidemic and the demands it will make on health care
and other social systems.
Prevalence Data
At present, data on the prevalence of HIV infection come principally
from two sources: (1) blood samples derived from programs testing
special populations (e.g., military applicants and blood donors) and
(2) testing of anonymous blood specimens from smaller studies of
convenience samples. Table 1-1 summarizes the seroprevalence data
from four testing programs, two large and two small. As the table
shows, there is some consistency across the estimates generated from
5The "Review of Current Knowledge" section of this report has been issued as a sup-
plement to the Morbidity and Mortality Weekly Report of December 18, 1987 (CDC,
1987a).
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MONITORING THE EPIDEMIC ~ 35
TABLE 1-1 HIV Seroprevalence Rates Among all Blood Donors,
Military Recruits, and Samples of Hospital Patients and
Job Corps Applicants
Number Percentage
Sample Tested Year Seropositive
Blood donors 12.6 million 1985-1987 0.02
1985 0.035
- 1987 0.012
Military recruits 1.25 million 1985-1987 0.15
Hospital patientsa 8,668 1986-1987 0.32
Job corps applicants 25,000 1987 0.33
Non-self-selected samples from the general population at four hospitals in the Midwest. The
actual prevalances ranged from 0.09 percent to 0.89 percent across hospitals. The prevalence
among military recruits in the same four cities (adjusted for age and sex) is 0.11 percent.
SOURCE: CDC (1987a).
three of these programs. In particular, testing of applicants for
military service, of patients in four Midwestern hospitals, ant! of
participants in the Job Corps program all produced HIV prevalence
estimates in the range of about 10 to 30 per 10,000. Estimates of HIV
prevalence among blood donors, however, were an order of magnitude
lower 1 to 3 per 10,000.
Despite the large number of persons screened in the four testing
programs shown in Table 1-1, the results are not representative of the
population. Military recruits, for example, come from particular age
and educational strata, and persons reporting homosexual behavior
or drug use are barred from enlistment. Such selection factors intro-
cluce large and numerically unknown biases; consequently, data from
the military screening program cannot be used to make inferences
about HIV infection in the national population.
Similarly, residential Job Corps entrants are drawn from the
disadvantages! 16- to 21-year-old population, and they overrepresent
racial and ethnic minorities. Hospital samples in turn have more
old ant! sick people than the general population, and this group
may be socioeconomically biased because the patterns of health care
utilization are correlates! with socioeconomic status (Andersen et
al., 1987; Secretary's Task Force on Black and Minority Health,
1985:194~.
The operation of biasing factors in these samples may be stron-
gest in the blood donor group because people who believe they are
at high risk for HIV infection have been asked not to donate blood.
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36 ~ UNDERSTANDING THE SPREAD OF HIV
Potential blood donors at Red Cross sites are interviewed for risk
factors, and they are given several opportunities to elect not to
donate their bloocl for use in transfusions. Thus, it is not surprising
that HIV prevalence among blood donors is much Tower than that in
other samples. The 10-fold Tower prevalence rate for blood donors
illustrates the problems that can arise when volunteer samples are
used to make inferences about the general population.
An example of the misunderstandings that may result from the
use of such samples is the reports in the popular medial that the
prevalence of infection detected! among military recruits in the United
States did not increase cluring the first 15 months of the military's
testing program. Although this result appears encouraging, it is ac-
tually quite clifficult to interpret because it is not known whether
the population of military recruits was stable over time. It is pos-
sible that potential military recruits who had engaged in high-risk
behaviors were discouraged from volunteering by publicity about the
mandatory HIV testing of recruits. A more subtle source of possible
bias may be the changes that often occur in the pool of military
applicants with respect to the mix of population subgroups in the
pool. These changes may be the result of a number of outside in-
fluences. For example, when the recruitment needs of the armed
forces are great, the minimum educational standards for enlistment
are relaxed. Similarly, when the economy fluctuates, the pool of
those seeking entry to the military services may enlarge or shrink.
Such changes have unknown effects on the HIV infection rates among
applicants in different years.
Monitoring Trends
It is sometimes asserted that, although available HIV prevalence data
are biased, they may be sufficient for following trends. Yet there are
good reasons to be skeptical of this assertion. First, there is usually
no assurance that the characteristics of the measurement techniques
used to determine HIV prevalence have been stable over time. Given
the great advances in basic knowledge ant! practical expertise in
AIDS research since 1981, it is likely that measurement techniques
have changed, although the magnitude of the differences generated
by such changes is not known. Unfortunately, when comparisons are
6See, for example, "AIDS Rate Remains Stable Among U.S. Military Recruits Since
Testing Started in 1985; Statistics Puzzle Experts," Washington Post, May 15, 1987:A1.
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MONITORING THE EPIDEMIC ~ 37
made across studies that lack well-defined protocols,7 differences in
measurement procedures are often impossible to recognize or con-
trol.8 Second, the populations being tested may not be stable over
time. The CDC report notes, for example, that HIV prevalence in
blood donors has decreased over time because people who tested
positive dropped out of the donor pool.
Incidence Data
Measures of HIV incidence are not generally available, but they would
be particularly valuable for tracking the epidemic's course, making
Tong-term projections about its future spread, and evaluating the
overall effectiveness of efforts to control AIDS. For example, reliable
data on the incidence of HIV infection would make it possible to
test the hypothesis that the incidence of new cases has peaked (or
is now peaking) in certain population groups. In this regard, the
committee notes that data included in the CDC report suggest that
incidence rates may be declining among gay men (see, in particular,
CDC [1987a:Table 12 and Figure 13~. It is unclear, however, how
much of this peaking results from the saturation with HIV infection
of small cohorts of gay men, particularly in instances in which the
cohorts were selectee! because of their high levels of sexual activity.
Variation in Estimated HIV Prevalence for
Selected Groups
The CDC report noted substantial differences in the estimated preva-
lence of HIV infection on the basis of the following:
. "risk factors" homosexual sex among men, IV drug
use, hemophilia, or heterosexual sex with persons at
risk;
. source of the sample bloocT donors, applicants for mil-
itary service, patients at clinics for sexually transmitted
diseases (STDs), newborns, and so forth;
geographic location; and
.
7This problem frequently arises when comparisons are made across different research
studies. However, data from screening programs that use highly standardized measure-
ment procedures and careful quality control of laboratory testing (e.g., in the armed
forces) are less vulnerable to this problem.
8The inability to recognize or control these differences also makes it impossible to re-
calibrate the prevalence estimates (i.e., by replicating the two measurement procedures
and observing the resulting variation in prevalence estimates).
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38 ~ UNDERSTANDING THE SPREAD OF HIV
. demographic factors in particular, sex, age, and race.
The differences in reported prevalence estimates ranged over two
orders of magnitude. It is unlikely that biases in the ciata could ac-
count for all of the observed differences. Furthermore, the reported
variations in HIV prevalence often mirrored differences in the num-
ber of reported AIDS cases, suggesting that the estimates may be
sufficiently accurate to provide a crude ranking of various groups in
terms of HIV prevalence.
Major groups for whom HTV prevalence and incidence data are
presented in the CDC report include homosexual and bisexual men,
{V drug users, hemophiliacs, -heterosexual partners of HTV-infected
persons (or persons in recognized risk groups), patients at general
care hospitals, tuberculosis patients, prostitutes, heterosexuals with-
out identifiable risk factors, and newborn infants and their mothers.
In adclition, by reporting the data according to locate, CDC provides
implicit information about variations in HTV prevalence across the
country. The rest of this section summarizes the ciata presented on
each of these groupings in the CDC report. The next section consid-
ers uncertainties that limit the usefulness of these data for making
inferences about the prevalence and incidence of HIV infection in the
overall population.
Homosexual and Bisexual Men. In 50 surveys and studies con-
ducted in 23 cities in 16 states, HIV prevalence rates ranged from
uncler 10 to 70 percent, with most of the estimates falling between
20 and 50 percent. Prevalence estimates were highest in San Ffan-
cisco, but the CDC report found that HIV was not concentrated in
any one region of the country. It should be noted that most of the
samples were drawn from patients at STD clinics, so the observed
rates probably overstate prevailing rates in the population of men
who have same-gender sexual contacts.
IV Drug Users. The prevalence of HIV infection among TV drug
users showed marked geographic variation ranging from 50 to 60
percent in New York City, northern New Jersey, and Puerto Rico
to less than 5 percent in areas distant from the East Coast. These
estimates were derived primarily from samples obtained at facilities
treating heroin addicts. (Some evidence suggests that {V drug users
who are not in treatment may be at greater risk of infection; see
Chapter 3.)
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MONITORING THE EPIDEMIC ~ 39
Hemophiliacs. Prevalence rates among hemophiliacs appear to
be uniformly clistributed across the United States. There are indi-
cations, however, that the likelihood of infection in a given sample
will be correlated with the type and severity of coagulation disorder:
reported HIV prevalence rates were 70 percent for hemophilia A and
35 percent for hemophilia B.
Heterosexual Partners of Persons with HIV Infection or at Rec-
ognized Risk. The prevalence rates for this group varied from under
10 to 60 percent in a limited number of studies. The reasons for
these large differences are unclear.9 Recent evidence suggests that
infectiousness increases with the deterioration of the immune sys-
tem. The relative efficiency of male-to-female and femaTe-to-maTe
transmission may also be important, but there are insufficient data
to assess this possibility. For heterosexual partners of high-risk per-
sons of unknown HIV status, HIV prevalence ranged from 0 to 11
percent.
Patients at General Care Hospitals. Non-self-selected samples of
8,668 blood specimens from the general population at four hospitals
in the Midwest gave an age- and sex-adjusted prevalence of 0.32
percent. The actual prevalences ranged from 0.09 to 0.89 percent.
(HIV prevalence among military applicants in the same four cities,
adjusted for agel° and sex, was 0.11 percent.)
Newborn Infants and Women of Reproductive Age. In a Mas-
sachusetts study, methods were developed to detect HIV infection in
women who have borne live infants.ll On the basis of 30,708 tests in
1986-1987, the weighted average prevalence was 0.21 percent (unad-
justed for the mother's age and race), varying from 0.80 percent at
inner-city hospitals to 0.09 percent at suburban and rural hospitals.
Female military applicants from Massachusetts had a crude preva-
lence of 0.13 percent (adjusted for age and race). As discussed later
9Subsequent to the publication of the CDC report, Peterman and coworkers (1988)
reported a study of 55 wives of HIV-infected men. Ten of these women seroconverted
during the course of the study. The women who seroconverted reported fewer instances
of unprotected intercourse than those who did not seroconvert, suggesting that other
factors in addition to exposure affect the probability of HIV transmission.
10It should be noted that adjustment of the military sample for age introduces consider-
able uncertainty because the age distribution of military recruits and military personnel
includes only a very small percentage of persons in older age groups.
1lThe risk of HIV transmission from an infected mother to her infant is estimated to
range from 30 to 50 percent. However, all infants of infected mothers carry maternal
antibodies to HIV—whether or not they are actually infected with the virus.
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40 ~ UNDERSTANDING THE SPREAD OF HIV
in this chapter, these prevalence estimates represent the population
of childbearing women and are unbiased in terms of self-selection or
exclusion related to HIV risk factors.
Prostitutes. HIV prevalence among female prostitutes ranged
from O to 45 percent, with the highest rates in large inner-city areas
in which drug use is common, such as New York City, Miami, and
Detroit. The prevalence of HIV infection was three to four times
higher in female prostitutes who were also drug users, and it was
twice as high in black and Hispanic prostitutes as in white and other
prostitutes. The geographic pattern of HTV infection in prostitutes
appeared to parallel the geographic distribution of AIDS among
women in general.
Tuberculosis Patients. HIV infection is thought to have caused
an increase in the number of persons with clinical tuberculosis (TB).
In one study that was not limited to self-selectec3 groups, 19 percent
of 276 TB patients in Dade County, Florida (which includes Miami)
tested positive for HIV. In four studies of TB patients at high risk,
the prevalence ranged from O to 50 percent.
Heterosexuals Without Known Risk Factors.l2 The prevalence of
HIV infection among heterosexually active persons in the absence
of known risk factors in either partner appears to be low. Two
small studies of seropositive military applicants found that 20 of 24
applicants in New York City who sought counseling actually had
recognized risk factors, and 11 of 12 applicants in Colorado had
risk factors (e.g., mate homosexual contacts). In addition, 30 of 33
seropositive mate active-duty military personnel revealed recognized
risk factors when interviewed. Among seropositive blood donors
interviewed in Los Angeles, Baltimore, and Atlanta, 153 of 186 donors
(82 percent) had risk factors; of those interviewed in New York City,
97 of 109 (89 percent) had risk factors. These data suggest that as
few as 15 percent of infected military applicants and blood clonors
acquired their infection heterosexually. This would imply that the
prevalence rate for heterosexually acquired HIV infection was 0.021
percent for military applicants (adjusted for age, sex, and race) and
0.006 percent for blood donors.
12''Without known risk factors" means without histories of IV drug use, male homo-
sexual contacts, sexual contact with persons known to be infected, or hemophilia or
transfusions prior to the adoption of universal blood donation screening.
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MONITORING THE EPIDEMIC ~ 41
Variation by Age. There were marked differences in the cumula-
tive AIDS incidence and available measurements of HIV prevalence
by age, sex, race, and ethnicity. For age, the available cross-sectional
data indicated a differential prevalence of HIV infection that rose
from the mid-teens to a peak in the early 30s, and then declined
in the 40s and 50s. In theory, such a pattern might arise from two
opposing age trends:
.
The young have been exposed to the risk of infection
for less cumulative time, which might tend to produce
Tower prevalence at younger ages.
. With increasing age, there may be decreased frequency
of behaviors that risk infection. For example, a 20-year-
oIc! is apt to be more sexually active, to have more
partners per year, an(l, perhaps, to be more likely to
use IV drugs than a 50-year-old. Some of these patterns
may be hard to verify. Nonetheless, to the clegree that
they apply, they suggest that, during the years since
AIDS appeared, the sexual activities of older persons
may have been, on average, less risky than those of their
younger contemporaries.
One implication that follows from these opposing trencis is that the
age distribution of persons infected with HIV might be quite different
in a region to which HIV came late (versus a region that was affected
earlier) because the tendency on the part of the young to accumulate
risky experience would exert less influence.
Variation by Gender. The cumulative prevalence of AIDS cases
(i.e., the total number of cases for each gender divided by the num-
ber of cases) was 13 times higher among men than among women.
However, the cited HIV prevalence rates varied widely; the maTe-
to-femaTe ratio of prevalence was 5.5:1 among military applicants
(adjusted by age and race), 4.6:1 among blood donors, 2.3:1 among
sentinel hospital patients, and the ratio apparently approaches 1:1
among IV drug users. In theory, the variation in these ratios should
reflect (1) the sex composition of the underlying risk groups plus (2)
the extent to which these risk groups may be incluclecT in the popu-
lation being considered. Considering the entire population, the 13:1
preponderance of men among AIDS cases reflects the fact that most
AIDS cases in the United States have occurred among men who have
sex with men anti among {V drug users. If, however, only women and
men who already belonged to one of the risk groups (e.g., {V drug
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62 ~ UNDERSTANDING THE SPREAD OF HIV
areas in which more specialized studies should be conducted to an-
swer questions of causality. This type of strategy would not be overly
difficult to implement after some experience is gained with the basic
neonatal survey.
ESTIMATES OF NATIONAL
HIV PREVALENCE AND INCIDENCE
There are three methods of estimating the current extent of HIV
infection in the United States.
1. Divide the population into groups or strata, and for
each stratum estimate both the size of the group and
its rate of seroprevaTence. Combine these estimates for
an estimated number of infected! persons in the stratum;
obtain a national total estimate by adding the estimates
for all strata.
2. Exploit the necessary mathematical connections among
three time series: A(t), the number of AIDS cases seen
by time t; H(t), the number of HIV infections that have
occurred (mostly unseen) by time t; and lax), the prob-
ability distribution for the "latency," the length of the
interval between acquiring HIV infection and being cli-
agnosed with AIDS.
3. Conduct a sample survey of the population of the United
States, collecting and testing blood specimens.
This section considers each of these methods in turn, calling
them (1) the components model, (2) the epidemiological model, and
(3) the sample survey method.
The Components Mode}
The components model was used to derive the most widely quoted
estimate of HIV prevalence in the United States (see Table 1-2),
which was presented in the Public Health Service's 1986 "Coolfont
Report" (Public Health Service, 1986~. That report concluded: "tB]y
extrapolating all available data, we estimate that there are between
1 and 1.5 million infected persons in those groups [IV drug users and
homosexual men] at present" (p. 343~. Although explicit calcula-
tions were not shown in the original document, the Coolfont report
inclicated that its authors estimates! that 2.5 million American men
between the ages of 16 an<155 are "exclusively homosexual" through-
out their lives and that 5-10 million more have some homosexual
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MONITORING THE EPIDEMIC ~ 63
TABLE 1-2 Estimates of the Number of Persons Infected with HIV in
the United States
Source Population Date Estimate
PHS Coolfont reporta IV drug users June 1986 1.25 millions
- and homosexual
men
CDC Domestic Policy
Council reports
IV drug users Nov. 1987 1.17 millions
and homosexual
men
aPublic Health Service (1986:341-348).
`'Estimated as the interval 1.0 million to l.S million; the midpoint of the interval is shown in
the table.
CCDC (1987b).
Estimated as the interval 945,000 to 1.41 million; the midpoint of the interval is shown in the
table.
contact.33 Similarly, they estimated (without explicit reference to a
source) that 750,000 Americans inject heroin or other drugs at least
once a week and that similar numbers inject drugs less frequently.
These estimates of population size were then multiplied by estimates
of the prevalence of HIV infection among these groups34 to generate
the widely quoted estimate that there are from 1-1.5 million infected
persons in these two groups. Changes in estimates of population size
and HIV prevalence lecT CDC (1987a) to revise its estimate for 1987
(see Table 1-2) to 945,000-1.41 million infected individuals.
Estimates derived using the components model are vulnerable to
errors of unknown magnitude in both multiplicands. For example,
the 1986 Coolfont estimate used data collected by Kinsey and col-
leagues (1948) in the 1940s to estimate the current number of mate
homosexuals in the United States. Even 30 years ago, the Kinsey
data were widely regarded as unreliable for making such estimates
because the research that produced them clid not use probability
sampling and because the respondents in the Kinsey studies were
disproportionately drawn from the Midwest and from the college-
educate<1 segment of the population (e.g., Terman, 1948; Wallis,
1948; Cochran et al., 1953~. Today, a further leap of faith is required
33The subsequent CDC report (1987a) provides the explicit breakdown used in the 1986
calculations.
34The prevalence rates used in these calculations were not published in the original
report (Public Health Service, 1986), but the report states that HIV prevalence estimates
range from 20-50 percent for homosexual men and from 10-50 percent for users of IV
drugs.
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64 ~ UNDERSTANDING THE SPREAD OF HIV
to assume that the relative size of the (self-reported) homosexual
population has not changed since the 1940s (see Chapter 2 ant! Fay
and colleagues tin press)). Furthermore, the committee notes that
estimates of the prevalence of HIV infection among homosexual men
were not derived from probability samples. Identical problems afflict
the estimates of HTV infection among IV drug users (see Spencer [in
this volumes.
The Epidemiological Mode]
The epiclemiological mode] depends on a necessary mathematical
relationship among these three time series:
A(`t), the (cumulative) number of AIDS cases that have ap-
peared by time t;
H(t), the (cumulative) number of cases of HIV infection that
have occurred (mostly unseen) by time t; and
lax), the probability35 that a person will be diagnosed with
AIDS after the passage of x years from time of infection
with HIV 36
Before discussing the mathematical relation, let us note what is
known about these series. First, from CDC statistics, A(t) is known
for the perioc! since 1981. The data are not quite exact because
revisions must and do occur. (For example, a major revision of the
AIDS case definition was adopted in 1987 iCDC, 1987c]~. Because
of reporting delays, the most recent portion is most susceptible to
revision. Second, almost nothing is known about H(t) because there
are such meager data about HIV prevalence.
~ )
Third, I(x) can be
Known only tor x trom U up to about 10 years, for there has been no
opportunity to see the relative frequency of latencies longer than 10
years. What is known about this latency distribution comes largely
from studies of hemophiliacs, transfusion recipients, and a few other
. .
35The function l(x) is a probability density function that ordinarily sums to 1.0 if in-
tegrated from O to infinity. However, because not all of those infected with HIV may
eventually be diagnosed with AIDS, the integral of lax) from O to infinity may be less
than 1.0.
36Implicit in this definition of lax) is the assumption that latencies (intervals between
time of infection and time of AIDS diagnosis) have had the same probability distribution
over time; thus, the definition tacitly assumes that changes in the ratio of men to women
among infected individuals or in the relative proportions of IV drug users, homosexuals,
and blood product recipients are all immaterial with respect to the distribution of la-
tencies. (With the exception of latencies for newborns, we are not aware of convincing
information that contradicts or supports these assumptions.) Also involved is the as-
sumption that diagnostic practices have not altered in a way that shortens or lengthens
latencies.
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MONITORING THE EPIDEMIC ~ 65
special groups. By assuming that lax) has a specific functional form,
such as that of the Weibull distribution, it is possible to extend our
estimate of lax) beyond x = 10 years.
The epidemiological mode] sets out to estimate the curve H(t)
by using A(t), which is approximately known, and lax), which is
somewhat known. The relation among these three series is
fit
A(t) = ~ H(t—x)l~x)dx.
O
(1)
Thus, if any two of A(t), H(t), and l(x) are known exactly, the other
can be calculated exactly. We do know A(t) more or less exactly and
I(x) can be estimated; thus, it is possible to produce an estimate of
H(t), the cumulative incidence of HIV infection up to time t. An
estimated solution of equation (1), then, consists of two estimated
series, H(t) and lax); the adequacy of this solution can be judged by
how closely the resulting A(t) (from the solution) corresponds with
the observed A(t). Unfortunately, quite different pairs of estimates
of H(t) an(1 I(x) provide equally good fits to A(t) but carry very
different values for the cumulative incidence H(t) and for the latency
distribution 1(x).
In practice, using equation (1) to estimate H(t) is fraught with
difficulties. In particular, I(x) is very small for the first two or three
years. Thus, as equation (1) shows, AIDS cases that have been
(liagnosed by, for example, 198S, are primarily a function of the
number of HIV infections through 1985. Therefore, even a perfectly
accurate count of the AIDS cases diagnosed through the previous
year provides little reliable information on new HIV infections during
the past three or four years. Because HIV incidence may be growing
rapidly and because it is not possible to estimate precisely the number
of new cases of HIV in the past few years, estimates of the cumulative
incidence H(t) could be far off the mark. This imprecision floes not
matter very much for predicting the number of new AIDS cases in
the short-run because such predictions do not depend heavily on the
incidence of HIV infection in the past few years (Brookmeyer and
Gail, 1986~. In terms of predicting current HIV prevalence, however,
and for estimating trends in prevalence over time, this imprecision
can be costly.
Clearly, the epidemiological and the components models ap-
proach the estimation of HIV prevalence quite differently. Each has
its problems, but they are of quite different kinds. Both produce
estimates of HIV prevalence of "about 1,000,000" meaning, within
the range of 0.5-2 million infected persons. Confidence in this rough
. . . . .
, , ~ , ~
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66 ~ UNDERSTANDING THE SPREAD OF HIV
estimate is strengthened by the fact that the uncertainties affecting
the two methods of estimation are quite different.
Sample Survey Method
The Public Health Service recently embarked on a developmental
program to test the feasibility of obtaining direct estimates of HIV
infection by means of a survey that Louis seek blood specimens (and
associated questionnaire data on risk) from a probability sample of
the national population. This undertaking is necessarily complex
and difficult, and it cannot be foreseen whether such a survey will
produce the desired estimates.
Among the most important of the attendant difficulties will be
ensuring a sufficiently high rate of response to the survey. Because
less than 1 percent of the population is thought to be infected with
HIV, nonresponse could have a debilitating impact if it were to
come disproportionately from population subgroups with elevated
prevalence rates. In that case, the estimates produced by such a
survey program could be seriously biased, even if the initial sample
of designated respondents were unbiased. (Turner anti Pay tin this
volume] explore in greater detail the complexities involved in such a
survey.)
The committee commends the exploratory spirit in which the
Public Health Service has begun the development of this survey, and
it applauds its strategy of using experiments to test whether or not
such a survey might provide useful direct estimates of prevalence
(and, ultimately, trends in prevalence). The outcome of these exper-
iments should play a decisive role in the ultimate decision of whether
to go forward with such a survey.
CONCI,USION
The committee believes that there is a pressing national need for
better statistical systems to monitor the spread of the AIDS epi-
demic anal, more particularly, the spread of its precursor, HIV in-
fection. The development of such systems will require time and
adequate resources—both in dollars and in appropriately trained sci-
entific staffs. If the nation is to have a better understanding of the
HIV/ATDS epidemic in 1999 than it has in 1989, the investment must
be made. Delays in committing resources to the development of these
systems would be false economy. Such a policy would only postpone
unavoidable expenditures while forcing scientists and policy makers
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MONITORING THE EPIDEMIC ~ 67
to continue to "make do" and work without accurate information on
the current magnitude and future course of the epidemic.
The development of a more reliable system for tracking the
spread of HIV infection is a prerequisite for mounting a fully effective
and efficient national response to AIDS. Without better information
on the incidence of new-HIV infections in the population, the nation
will lack adequate means to determine whether current strategies for
controlling the spread of HIV are working. Without better infor-
mation on the prevalence and spread of infection in the population,
it is difficult to prepare adequately for future demands for hospital
beds and other health care services. Without better data, it is easy
to anticipate encIless debates about whether the disease is spreading
"rapidly" or "slowly." To the extent that opposing sides in these de-
bates produce "evidence" from convenience samples, inconsistency
in conclusions is to be expected, and there is thus no basis for an
informative scientific debate.
What we require for more informative debates, for better plan-
ning for future health care needs, and for improved evaluation of
the effects of national AIDS-controT strategies are data derived from
research designs that can provide reasonably unbiased estimates of
the prevalence and incidence rates for HIV infection in well-defined
populations of substantive interest.
Attributes of an HIV Monitoring System
Such designs for monitoring HIV would have two characteristics that
set them apart from the procedures ordinarily used for tracking
epidemics. These attributes follow directly from the nature of the
disease under consideration. A passive reporting system is not ade-
quate to monitor the spread of a fatal infection that is asymptomatic
(for almost all infected individuals) for a long period of time. This
fact requires a conceptual departure from the way in which epidemic
diseases have traditionally been monitored. Traditionally, such dis-
eases have been classified as "reportable" by public health officials.
After such a determination, health care workers (physicans, testing
laboratories, etc.) were legally required to report all new cases of
the disease to the local department of public health. These reports,
when aggregated by federal disease control officials, provicled crucial
information for monitoring the course of many past epidemics. Part
of the reason for the success of this type of system followed from
the fact that many of these infections quickly caused symptoms that
required medical attention. The outcome (in a substantial fraction
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68 ~ UNDERSTANDING THE SPREAD OF HIV
of cases) was swift, anci the size of the public health problem posec!
by the spread of the infection coulcT be monitored by counting the
number of new cases reporter! to health authorities.
Unfortunately, a passive reporting system cloes not work as well
for diseases that in most infectec! incTivicluals are slow to require mecI-
ical attention. These- diseases clo not provide sufficient motivation
to the infectec! person to seek medical care quickly and thereby be
captured by the statistical reporting system; consequently, the sta-
tistical system must actively "ferret out" information on new cases.
This more active method of case gathering ancT reporting is the first
way in which an HIV monitoring system woulcI stiffer from more
traditional case-reporting systems.
A second difference is that an adequate measurement system
for HIV cannot rely exclusively on the routine functioning of the
meclical infrastructure to count infected persons. This requirement
has important institutional consequences because it manciates the
organization of surveillance outside of traditional meclical settings.
Other Uses of Data on HIV
This committee has listened with interest to arguments that popula-
tion-basec! estimates of HIV incidence ancT prevalence are unneces-
sary from a public health perspective. Rather, it has been suggested
that targetec! samples of convenience could suffice to provide "sen-
tinels" that could be used to guicle the nation's response to the AIDS
· -
eplc .emlc.
The committee recognizes that there may be public health uses
of prevalence data whose purposes can be server] by other methocI-
ologies. In reviewing the protocol for HIV testing of patients at TB
clinics, for example, the committee was initially perplexed by the
choice of blind testing; reasonable stanciarcis of medical treatment
would dictate routine HIV testing of all TB patients because pre-
liminary evidence suggests that stanciarcl antituberculosis therapy
should be moclifiecT for persons infected with HTV. After discussions
with CDC staff, the committee came to unclerstanc] that a major
purpose of the blinc! testing was to convince reluctant clinics to be-
gin routine HIV screening of TB patients. The evidence from the
blinct screening was intenclec! to stimulate local clinic staff to recog-
nize the extent of HIV prevalence in their clinic ancT to adopt the
Public Health Service's recommendation for routine HIV screening
of all TB patients.
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MONITORING THE EPIDEMIC ~ 69
In this case, there was a clear public health use for numerical
information on prevalence in particular clinics. That purpose could
be well served without attempting to estimate accurately the true
prevalence of HIV among all patients at TB clinics. While recog-
nizing this important public health use of such data, the committee
would observe that the stated objectives of this survey, as with other
components of the family of surveys program, were to determine HIV
prevalence and monitor trends in prevalence.37 These more demand-
ing objectives require a survey design appropriate to these tasks.
It is the opinion of this committee that the public health mandate
to monitor the spread of HIV requires that reliable statistical data
be gathered on HIV infection. Gathering such data necessitates the
use of methods that ensure (to the extent technically possible) that
the resultant estimates will reflect, with known margins of error, the
actual incidence and prevalence of infection in specific populations.
The committee concludes that it wouitd be a serious mistake for the
Public Health Service to continue to "make do" with estimates derived
from convenience samples.
The committee would also emphasize that much of the infor-
mation needled to understand and cope with the spread of HIV is
obtainable only with the consent of a person who may be harmed
if test result confidentiality is not maintained. Thus, maintaining
confidentiality serves not only fairness but also society's interest in
access to information to help combat the disease. Two steps can
help: (1) confidentiality can be buttressed with legal penalties in the
event of its breach, and (2) legal protection against discrimination
can be established for persons infected with HIV. In this regard,
the committee wishes to note that it endorses the approaches to
protecting confi(lentiaTity and opposing discrimination proposer! by
the Presidential Commission on the Human Immunodeficiency Virus
Epidemic (1988~.38
The Presiclential Commission has provided the President and
the American people with 35 specific recommendations on the steps
that should be taken to halt discrimination against persons with
HIV infection and AIDS and to guarantee the confidentiality of
37The protocol (CDC, 1988a:4) states: "The objectives of this survey are the following:
(1) to determine the prevalence of HIV antibodies among persons with confirmed or
suspected tuberculosis by age, sex, race, ethnicity, metropolitan area, TB clinic site,
country of origin, clinical status (confirmed or suspected TB), anatomic site of infection
(pulmonary, extrapulmonary, or both) and (in the non-blinded surveys) AIDS risk factor;
and (2) to monitor trends in infection levels over time. Implementation of a standard
protocol will facilitate comparison of data from different clinics."
38 See Chapter 9, Sections I and II.
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70 ~ UNDERSTANDING THE SPREAD OF HIV
information about individuals' HIV status. The committee believes
that the approaches recommended by the commission couIcT serve the
nation well by improving the climate in which future research ant!
interventions will be concluctecI.
Finally, the committee and its Panel on Statistical Issues in AIDS
Research wish to end this chapter by offering two observations: one
about the past and one about the future.
The Public Health Service has met an unexpected, challenging,
and complicated epidemic with vigor and ingenuity and has much to
be Proust of. Moreover, its achievements~have been accomplished in
the face of consiclerable adversity on a number of fronts physical,
diplomatic, political, and administrative. As always, however, the
past must give way to the future. The HIV/AIDS problem is not
going to disappear soon, if ever. Its most visible component, AIDS,
will surely increase for years to come. Now is the time to prepare
for the future, and good data will be indispensable in future efforts
to control this epidemic. No postponement shouic! be accepted in
implementing the clearly necessary steps to markedly improve the
data on this disease. CDC should be given the resources needled
to promptly initiate the appropriate steps to improve the nation's
HIV/AIDS information base.
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Representative terms from entire chapter:
hiv prevalence
