Tao, Guoyu*; Remafedi, Gary†
The objective of this study was to evaluate the cost-effectiveness of an HIV prevention intervention for gay and bisexual male adolescents. The intervention included individualized risk assessment and counseling, peer education, optional HIV testing, and referrals to needed services. From 1989 to 1994, 501 male volunteers, 13 to 21 years of age, who self-identified as gay/bisexual or as having had sex with men, completed preintervention and postintervention surveys to assess changes in HIV risk behavior. An HIV transmission model was constructed to project the HIV seroprevalence in the target population over a 10-year period from the self-reported number of partners for unprotected anal intercourse. Cost-effectiveness was analyzed from a societal perspective. Total costs of the intervention, including medical treatment costs saved, were projected to be $1.1 million U.S. for the 10-year period. The number of HIV infections averted and the quality-adjusted life years (QALYs) saved were projected to be 13 and 180, respectively. An incremental cost-effectiveness ratio was projected to be $6180 U.S. per QALY saved. The intervention was found to be cost-effective from the societal perspective. In addition, HIV prevalence in the target population was projected to be 6.1% without and 5.6% with intervention by the end of the 10-year period. This study highlights that an HIV prevention program can be cost-effective even if the effects on behavior are partial and short term.
The University of Minnesota Youth and AIDS Projects has been implementing an intensive, statewide HIV prevention intervention for gay and bisexual male adolescents since 1989. This intervention includes individual risk assessment and risk reduction counseling, peer education, optional HIV antibody testing and counseling, referral to medical and psychosocial services as needed, and longitudinal follow-up. A previous study, using a pretest and posttest design, has found that the intervention contributed to short-term risk reduction in HIV transmission, measured by reductions in the number of sex partners and the frequency of unprotected anal intercourse among the participants (1).
Short-term risk reduction can dynamically influence HIV prevalence by directly decreasing the probability of HIV transmission and by indirectly affecting subsequent HIV prevalence in the population. However, an issue of practical concern is cost-effectiveness, vitally important for decision makers to allocate limited preventive health care resources efficiently (2). Experts have noted that no economic evaluation of specific HIV prevention interventions for gay and bisexual adolescents has been made (3). In general, such economic evaluations are sparse because estimates of intervention-related behavioral changes and health outcomes (e.g., the number of HIV infections averted) are difficult to ascertain (4,5). The purpose of this study was to use economic evaluation techniques to determine the cost-effectiveness of the University of Minnesota Youth and AIDS Projects intervention program.
Standard methods of cost-effectiveness analysis were used in this study as described below. Three major analytic steps were taken: to frame the economic evaluation, to develop a mathematical model translating the observed behavioral effects into an estimate of the number of HIV infections averted, and to estimate the intervention-related parameters.
According to the recommendations of the U.S. Panel on Cost-Effectiveness in Health and Medicine (6), a thorough cost-effectiveness analysis should select an appropriate perspective, describe the intervention and its target population, choose a time frame that captures the major health and economic outcomes, select a discount rate, define the costs and health effects of the intervention, select appropriate alternatives for comparison, calculate incremental cost-effectiveness ratios, and run sensitivity analyses. We used a societal perspective, which incorporates all costs and health benefits, regardless of who incurs the costs and who obtains the benefits. The societal perspective was adopted for two important reasons. First, the U.S. Panel on Cost-Effectiveness in Health and Medicine recommended using this perspective in the reference case (6). Second, by controlling the spread of HIV infection, the intervention not only benefits gay and bisexual adolescents, but society in general.
Since 1989, the target population of the intervention has been 13-to 21-year-old men living in Minnesota who self-identified as gay or bisexual or who have had sex with men (1). The intervention includes individual risk assessment and risk reduction counseling, peer education, optional HIV antibody testing, referral to medical and psychosocial services as needed, and longitudinal follow-up. Participants have been recruited for the intervention through advertisements; outreach at social groups, community events, and entertainment venues; and referrals from professionals and prior participants. Among the first 139 adolescents enrolled in the intervention, the mean age was 19 years, and the average educational level was grade 12 (1). More than 70% of participants were employed at least part time. Seventy-five percent were white, 14% were African American, and 11% were various other ethnicities; almost half were raised in major metropolitan areas(>100,000 persons). Compared with the initial risk assessment, 60% fewer participants reported unprotected anal intercourse with recent partners a mean of 4.5 months after the intervention. The evaluation also revealed a 23% decrease in the frequency of anal intercourse and a 50% increase in the consistent use of condoms during follow-up. Substance abuse severity scores decreased by 13%; and use of amphetamines and amyl nitrite declined by 6% and 9%, respectively.
Because the intervention affects both the incidence and prevalence of HIV infection over time, we chose a 10-year time frame to capture relevant future effects. To project future outcomes, we used a 3% discount rate for both costs and benefits, based on the recommendations of the U.S. Panel on Cost-Effectiveness in Health and Medicine (6).
Expenses associated with the intervention and medical treatment for HIV/AIDS were included in the cost-effectiveness analyses. Quality-adjusted life years (QALYs) saved and the number of HIV infections averted were assessed separately. The effect of the intervention was compared to a "do-nothing" approach; and an incremental cost-effectiveness ratio was calculated to measure the performance of the intervention. The incremental cost-effectiveness ratio is defined as the ratio of the additional costs and effects obtained when one strategy is compared with another. In the analysis of incremental cost-effectiveness, health effects were expressed in units of QALY and costs in constant 1994 U.S. dollars. Sensitivity analysis was performed to explore the robustness of the base case result. In this context, the termbase case refers to the best available point estimates for all parameters.
To conduct the economic evaluation, mathematical modeling techniques were used to project the number of HIV infections averted. Various models of HIV transmission with different assumptions have been used in prior studies (7-14). Because changes in HIV prevalence within a community are mainly due to changes in people's behaviors and their likelihood of exposure to the virus (9,12,14-18), this study modeled HIV transmission on changes in numbers of risky partners and the projected quarterly prevalence of HIV infection in the target population. In this context, the term risky partners refers to partners in unprotected, receptive or insertive anal intercourse. In this study, eight parameters were required to create a predictive model. These parameters are listed in Table 1 with their definitions, symbols, estimated base case values, and the range of values used for sensitivity analyses.
| TABLE 1. Parameter definition, symbol, base case and range value, and reference |
Our model made five assumptions: without intervention, risky behaviors in the target population would not change over time; participants maintained less risky behavior for only 1 year before relapsing to the previous level of risk; partners were selected without regard to their HIV serostatus; age was equally distributed in the target population; and the size of the target population would remain constant during the 10-year period.
The procedures used to estimate the number of new infections in the target population, based on the reported prevalence of HIV infection and the number of risky partners, are described in Figure 1. The target population was classified into two groups: participants and nonparticipants. Both participants and nonparticipants were further classified into infected and uninfected subgroups.
| FIG. 1. The procedure used to estimate new HIV infection in the target population based on high-risk sexual behaviors and prior HIV prevalence. |
The total number of risky partners of persons in each subgroup depended on the size of the subgroup and the average number of risky partners per person in the subgroup. The number of new infections in the target population was calculated by multiplying the probability of HIV transmission per infected-uninfected risky partnership by the total number of infected-uninfected risky partnerships. The total number of infected-uninfected risky partnerships was calculated by multiplying the total number of risky partners of infected persons by the probability that their partners were uninfected. Based on the assumption that risky partners were selected without regard to HIV serostatus, the probability that risky partners of infected persons were uninfected was estimated by dividing the number of risky partners of uninfected persons by the total number of risky partners of both infected and uninfected persons.
To estimate change in HIV prevalence over time, it was necessary to consider the mortality of infected persons and aging in and out of the 13- to 21-year-old cohort. Because of the long clinical latency period of HIV infection, the number of deaths was expected to be much smaller than the number of infected persons who left the cohort because of increased age. Therefore, this study modeled aging, but not mortality. The total number of HIV infections at any time was considered to be the total number of previous infections, plus the projected number of new infections, minus the number of infected persons who left the target population because of age. When the total number of HIV infections in the target population was converted into the HIV prevalence, dynamic changes in HIV prevalence in the target population(with and without intervention) were derived by two formulas.
Dynamic change in HIV prevalence without intervention: Equation 1
| Equation 1 |
Dynamic change in HIV prevalence with intervention: Equation 2
| Equation 2 |
Data from the initial and follow-up interviews were used to estimate the behavioral effects of the intervention and the initial HIV prevalence in the target population. A total of 501 participants (~100/year) were recruited from 1989 to 1994. All participants received the intervention, and 376 (75%) completed the follow-up risk assessment within a mean of 4.5 months. The number of risky partners of infected nonparticipants, uninfected nonparticipants, infected participants, and uninfected participants was empirically derived from the initial and follow-up interviews (Table 1). Because of the small number of infected participants, the absolute number and range of risky partners of infected participants were assumed to be the same as those of uninfected participants at the base case.
The initial HIV prevalence in the target population was estimated to be 2%. The actual value was difficult to determine because not all participants had had their HIV status determined and because the HIV prevalence might have changed during the time period of the study. As previously reported, 45% of the total sample (226 of 501 persons) had been tested before enrollment in the intervention (25). Of those, 4% (8 of 226 persons) were positive, 91% were negative, and 6% did not know their results. Because the participants who had been tested were more likely to be involved in risky behaviors than those who had not been tested (25), the initial HIV prevalence might have ranged from 1.6% (8 of 501 persons) to 4% (8 of 226 persons).
HIV prevalence at the end of each year through the 10-year period was adjusted using the following procedure. Based on the assumption that age was equally distributed in the target population, the total number of HIV infections in the cohort was considered to be the sum of the number of HIV infections in the nine age groups from 13 to 21 years of age. The number of infected adolescents who leave the target population at the end of each year was estimated by the number of infections in the 21-year-old group, minus the number of infections in the 12-year-old group. The parameter to adjust HIV prevalence (µ) was empirically determined to be 0.15, assuming that HIV prevalence in the 21-year-old and the 12-year-old groups were 4% and 1%, respectively (19-21,25).
The probability of HIV transmission per infected-uninfected partnership([tau]) is known to vary with different sexual behaviors (anal, vaginal, or oral), the gender of the index case, the stage of infection, the duration of partnership, and the frequency of sexual acts (9-11,26-31). For example, this probability may range from 0.20 to 0.28 for male to female transmission, from 0.01 to 0.12 for female-to-male transmission, and from 0.041 to 0.153 for male-to-male transmission (11,29-31). The probability of HIV transmission also varies with the stage of infection, that is, it is expected to be higher both in the initial and late stages of illness than in the long middle asymptomatic period (26). This probability also varies with a couple's sexual practices, from 0.008 to 0.055 for all partnerships to 0.025 to 0.166 for gay couples who practice anal intercourse (22). In addition, the probability of HIV transmission during a single contact differed from an ongoing partnership (22). Although the theoretical probability of HIV transmission can vary widely under different conditions, empirical estimates of this probability for infected-uninfected partnerships among gay men consistently have been found to range from 0.025 to 0.105 (10,22). The value of 0.06 was selected at the base case, according to prior studies (10,22,23).
Gay and bisexual male adolescents who were recruited into the intervention were estimated to be 8% of the target population in major Minnesota metropolitan areas. This percentage was based on the fact that approximately 100 gay and bisexual male adolescents were recruited into intervention annually and that the total number of persons in the target population was approximately 1300. The target population was limited to the major Minnesota metropolitan areas for two reasons. First, although the eligible persons of the original project was all 13- to 21-year-old men who are self-identified as gay or bisexual or who have sex with men in Minnesota, 70% of whom lived in metropolitan areas(Area Resource File of 1991). Second, most participants were recruited from the major Minnesota metropolitan areas (1). The size of the target population was derived by multiplying the total number of 13- to 21- year-old male adolescents by the percentage who were gay and bisexual. The total number of 13- to 21-year-old male adolescents was estimated to be 121,000 in 4 metropolitan counties in Minnesota: Anoka, Dakota, Hennepin, and Ramsey (Area Resource File of 1991). A population-based survey of junior and senior high school students in the same State found that 1.1% of male adolescents self-identified as gay and bisexual (24).
The direct intervention costs in 1994 were estimated from financial records (Table 2). The annual intervention costs after 1994 were assumed to be the same as they were in 1994, and they were adjusted to 1994 dollars by a 3% discount rate. The medical treatment costs for HIV/AIDS in 1992 were derived from previous studies (32,33). The costs in 1992 dollars were translated to 1994 dollars by using the Consumer Price Index (34). In addition, a human capital approach was used to estimate the economical benefit of the intervention, that is, human capital gains in productivity as a result of HIV infections averted. The human capital gains were calculated by the current value of expected future lifetime earnings for 15- to 19-year-old persons minus productivity gains in the next 10 years with a 3% discount rate (35), because most HIV-seropositive persons were expected to work for 10 years after infection (36). The medical treatment costs and human capital gains are listed in Table 3.
| TABLE 2. Descriptions of cost paramters and their values |
| TABLE 3. Base case value and range for medical treatment costs saved, quality-adjusted life years (QALY), and human capital gains in productivity |
The number of HIV infections averted can be converted into the number of QALYs saved by dividing the life span of an HIV-infected person into several phases and weighting each phase with a reduction in quality of life (4,37-40). A previous study estimated that approximately 9.26 QALYs were saved for each infection prevented at a 5% discount rate (4). After adjusting for differences in mean age and discount rate, an estimated 16.9 QALYs was saved for each infection prevented (Table 3).
Under base case assumptions, the total cost of the intervention, including medical treatment costs saved, was projected to be $1.1 million U.S. for a 10-year period (Table 4). The number of HIV infections averted and QALYs saved were projected to be 13 and 180, respectively. The incremental cost-effectiveness ratio was projected to be $6180 U.S. per QALY saved. HIV seroprevalence in the target population by the end of 10-year period was projected to be 6.1% without, and 5.6% with, the intervention. From the human capital approach, the intervention is expected to yield approximately$10 million U.S. of net benefits to society.
| TABLE 4. Results of the base case and sensitivity analyses |
Under the base case situation, the cumulative number of HIV infections averted during the 10-year period is displayed in Figure 2. The rising rate of HIV infections averted reflects the dynamic effect of the intervention. The cumulative number of infections averted at the end of the 10-year period is greater than expected, that is, the finding determined by simply multiplying the size of the target population by the change in HIV prevalence attributable to the intervention (13 vs. 6.5). The reason is patients whose ages took them in and out of the 13- to 21-year-old cohort.
| FIG. 2. The cumulative number of HIV infections averted during a 10-year period. |
The results of sensitivity analyses are displayed in Table 4. They demonstrate that the incremental cost-effectiveness ratios are robust over a reasonable range of five parameter estimates: the initial HIV seroprevalence, adjustments for aging, the percentage of gay and bisexual adolescents who were recruited into the intervention, the annual direct intervention cost, and the discount rate. The sensitivity analyses also find the incremental cost-effectiveness ratio to be robust even if the following parameters were below the best estimates: the initial number of risky partners in the target population, the reduction in the number of risky partners of all participants, the reduction in the number of risky partners of infected participants, and the probability of HIV transmission per infected-uninfected partnership. Compared with the base case, the intervention would be even more cost-effective, if the initial number of risky partners of infected persons were greater than that of the uninfected.
The sensitivity analyses reveal that the intervention yields net benefits to society under most situations, based on the human capital approach. Further reduction in the number of risky partners of participants would not significantly reduce the HIV seroprevalence because only a relatively small percentage of all eligible gay and bisexual youth have been recruited into the intervention.
Although there is no universally accepted standard, recent studies have considered a program to be cost-effective if the incremental cost-effectiveness ratio is<$30,000 U.S. per QALY (37-40). Using this figure as the threshold value, the HIV intervention for gay and bisexual adolescents is cost-effective in the base case and most other situations. The analyses illustrate that HIV prevention programs can be cost-effective, even when the effects on behavior are partial and short-term.
It is likely that the actual benefits of the intervention exceeded our projections. First, the effects of the intervention on HIV prevalence after 10 years were not included in the analysis. Second, this analysis did not consider the observed benefits of the intervention on reducing the frequency of intercourse and increasing the frequency of condom use (1). Third, the model assumed that adolescents only engaged in risky behaviors with each other. Some of them were known to be involved in risky behaviors with men over 21 years of age (41). With the relatively higher prevalence of HIV infection in adults, the effects of the intervention could be greater than expected. Fourth, the numbers of risky partners of both infected and uninfected persons were assumed the same at the base case. However, some infected individuals may practice riskier behaviors than the uninfected persons (21). Sensitivity analysis demonstrated that the intervention would be even more cost-effective if infected adolescents engaged in riskier sexual practices. Finally, all participants were assumed to relapse to prior levels of risky behavior 1 year after the intervention. Some studies have found that participants in prevention programs maintained less risky behaviors for >1 year (42,43).
The results of this study are consistent with other cost-effectiveness analyses of prevention interventions. One previous study found that prevention would be cost-effective if >1 in 260 drug users changed his or her behavior to prevent a single new HIV infection (44). Two other programs, one for high-risk urban women and the other for adult men who have sex with men, have been found to be cost-effective (39,40). Another recent study indicated that the HIV screening in acute care settings was cost-effective, especially when the HIV screening program resulted in risk reduction (45).
The limitations of this study include the debatable effect of the intervention on behavioral change, the use of a simple model to estimate the number of HIV infections averted, and the need to impute key epidemiologic parameters. The limitations of the program evaluation have been previously discussed in detail (1). These included the use of a volunteer sample and a simple pretest and posttest design. The present study assumed that the reported behavioral changes were valid, attributable to the intervention, and generalizable to the larger target audience. However, sensitivity analyses help to allay these concerns. As shown in Table 4, the intervention remained cost-effective when participants' risk reduction varied within a reasonable range.
In this study, a simple model was used to estimate the number of HIV infections averted. For example, the closed two-compartment model used here assumes that adolescents only engaged in risky behaviors with each other (22). Hence, the model may lack some of the complexity of a dynamic HIV epidemic. Although a more complex probability model concerning each individual in a population might simulate the epidemic more precisely (46), the simpler model yields more conservative estimates of HIV infections averted, as discussed above.
The base case estimates rely on epidemiologic parameters that lack precise estimates. For example, no empiric data were available for the number of risky partners of infected participants. Also, the probability of HIV transmission in infected-uninfected partnerships was estimated to have a wide range, 0.025 to 0.105 (10,22,23). Sensitivity analyses were used to examine these parameters. As shown in Table 4, the intervention remained cost-effective over a reasonable range of key epidemiologic parameters.
When more data are available, a more complex model may be applied to depict the dynamic HIV epidemic and the incremental cost-effectiveness ratio of interventions. The cost-effectiveness of other HIV prevention interventions should be analyzed. With this information, decision makers will be better able to allocate limited resources to those HIV prevention interventions that produce the greatest benefits to society.
Acknowledgments: The authors appreciate the support and advice of William J. Kassler, Jon Christianson, Michael Finch, and William Foster. This work is partially supported by Maternal and Child Health Bureau grant P05053 and Minnesota Department of Health grant 12500-15492 to Gary Remafedi.
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Key Words: HIV transmission model; Cost-effectiveness; Intervention; Gay and bisexual adolescents; Quality-adjusted life years
