Click for next page ( 32


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 31
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 Counts of AIDS cases are out-of-date indicators of the present state of the epidemic.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

OCR for page 31
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.

OCR for page 31
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.

OCR for page 31
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).

OCR for page 31
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.

OCR for page 31
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.

OCR for page 31
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).

OCR for page 31
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.)

OCR for page 31
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 HIVwhether or not they are actually infected with the virus.

OCR for page 31
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.

OCR for page 31
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

OCR for page 31
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

OCR for page 31
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.

OCR for page 31
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.

OCR for page 31
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(tx)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 . . . . . , , ~ , ~

OCR for page 31
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 resourcesboth 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

OCR for page 31
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

OCR for page 31
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.

OCR for page 31
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.

OCR for page 31
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. REFERENCES Andersen, R. A., Chen, M., Aday, L., and Cornelius, L. (1987) Health status and medical care utilization. Health Affairs 6:136-156. Brookmeyer, R., and Gail, M. H.. (1986) Minimum size of the acquired immunodefi- ciency syndrome (AIDS) epidemic in the United States. Lancet 2:1320-1322. Castro, K., Lieb, S., Jaffe, H., Narkunas, J., Calisher, C., Bush, T., Witte, J., and the Belle Glade Field-Study Group. (1988) Transmission of HIV in Belle Glade, Florida. Science 239:193-197. Centers for Disease Control (CDC). (1987a) Human immunodeficiency virus infection in the United States: A review of current knowledge. Morbidity and Mortality Weekly Report 36(Suppl. Sac: 1-48. Centers for Disease Control (CDC). (1987b) Human Immunodeficiency Virus Infections in the United States: Review of Current Knowledge and Plans for Expansion of HIV Surveillance Activities. Report to the Domestic Policy Council. Centers for Disease Control, Atlanta, Ga. November 30. Centers for Disease Control (CDC). (1987c) Revision of CDC surveillance case definition for AIDS. Morbidity and Mortality Weekly Report 36 (Suppl. lS):3S-15S. Centers for Disease Control (CDC). (1988a) Protocol for Estimating HIV Seropreva- lence in Patients with Confirmed or Suspected Tuberculosis Attending Tuber- culosis Clinics. CDC Protocol No. 839. Centers for Disease Control, Atlanta, Ga.

OCR for page 31
MONITORING THE EPIDEMIC | 71 Centers for Disease Control (CDC). (1988b) Protocol for Estimating HIV Seropreva- lence from Surveys in Clinics Which Serve Women of Reproductive Age. CDC Protocol No. 842. Centers for Disease Control, Atlanta, Ga. Centers for Disease Control (CDC). (1988c) Protocol: Sentinel Hospital Surveillance System for HIV Infection. REP 200-88-0623(P). Centers for Disease Control, Atlanta, Ga. Centers for Disease Control (CDC). (1988d) Survey of HIV Seroprevalence and Assess- ment of Associated Risk Behaviors in Patients Attending Sexually Transmitted Disease Clinics. CDC Protocol No. 843. Centers for Disease Control, Atlanta, Ga. Centers for Disease Control/National Institute on Drug Abuse (CDC/NIDA). (1988) Proposal for Monitoring HIV Seroprevalence in Intravenous Drug Users in Treat- ment. CDC Protocol No. 840. Centers for Disease Control, Atlanta, Ga. Centers for Disease Control/National Institutes of Health (CDC/NIH). (1988) HIV Seroprevalence Survey in Childbearing Women Utilizing Dried Blood Specimens Routinely Collected on Filter Paper for Neonatal Screening Programs (draft protocol). Centers for Disease Control, Atlanta, Ga. Cochran, W. G., Mosteller, F., and Tukey, J. W. (1953) Statistical problems of the Kinsey Report. Journal of the American Statistical Association 48:673-716. Des Jarlais, D. C., Friedman, S. R., and Stoneburner, R. L. (1988) HIV infection and intravenous drug use: Critical issues in transmission dynamics, infection outcomes, and prevention. Reviews of Infectious Diseases 10:155. Dondero, T. J., Pappaioanou, M., and Curran, J. W. (1988) Monitoring the levels and trends of HIV infection: The Public Health Service's HIV surveillance program. Public Health Reports 103:213-220. Pay, R. E., Turner, C. F., Klassen, A. D., and Gagnon, J. H. (In press) Prevalence and patterns of same-gender sexual contact among men. Science. Hardy, A. M., Starcher, E. T., II, Morgan, W. M., Druker, J., Kristal, A., Day, J. M., Kelly, C., Ewing, E., and Curran, J. W. (1987) Review of death certificates to assess completeness of AIDS case reporting. Public Health Reports 102:386-390. Hull, H. F., Bettinger, C. J., Gallaher, M. M., Keller, N. M., Wilson, J., and Mertz, G. J. (1988) Comparison of HIV-antibody prevalence in patients consenting to and declining HIV-antibody testing in an STD clinic. Journal of the American Medical Association 260:935-938. Institute of Medicine/National Academy of Sciences (IOM/NAS). (1986) Confronting AIDS: Directions for Public Health, Health Care, and Research. Washington, D.C.: National Academy Press. Institute of Medicine/National Academy of Sciences (IOM/NAS). (1988) Confronting AIDS: Update 1988. Washington, D.C.: National Academy Press. Kinsey, A. C., Pomeroy, W. B., and Martin, C. E. (1948) Sexual Behavior in the Human Male. Philadelphia: W. B. Saunders. Manton, K. G., and Singer, B. M. (1988) Forecasting the Impact of the AIDS Epidemic on Elderly Populations. Department of Epidemiology and Public Health, School of Medicine, Yale University. Peterman, T. A., Stoneburner, R. L., Allen, J. R., Jaffe, H. W., and Curran, J. W. (1988) Risk of human immunodeficiency virus transmission from heterosexual adults with transfusion-associated infections. Journal of the American Medical Association 259:55-58. Presidential Commission on the Human Immunodeficiency Virus Epidemic. (1988) Final Report of the Presidential Commission on the Human Immunodefi:ciency Virus Epidemic. Washington, D.C.: Government Printing Office.

OCR for page 31
72 ~ UNDERSTANDING THE SPREAD OF HIV Public Health Service. (1986) Coolfont report: Public Health Service plan for com- bating AIDS. Public Health Reports 101:341-349. Secretary's Task Force on Black and Minority Health. (1985) Report of the Secretary's Task Force on Black and Minority Health, Vol. 1, U.S. Department of Health and Human Services. Washington, D.C.: Government Printing Office. Terman, L. M. (1948) Kinsey's "Sexual Behavior in the Human Male": Some comments and criticisms. Psychological Bulletin 45:443-459. Wallis, W. A. (1948) Statistics of the Kinsey report. Journal of the American Statistical Association 44:463-484.