Date Published: October 9, 2018
Publisher: Public Library of Science
Author(s): Frits van Griensven, Philip A. Mock, Patchara Benjarattanaporn, Nakorn Premsri, Warunee Thienkrua, Keith Sabin, Anchalee Varangrat, Jinkao Zhao, Anupong Chitwarakorn, Wolfgang Hladik, Olalekan Uthman.
HIV incidence information is essential for epidemic monitoring and evaluating preventive interventions. However, reliable HIV incidence data is difficult to obtain, especially among marginalized populations, such as young men who have sex with men (YMSM). Here we evaluate the reliability of an alternative HIV incidence assessment method, behavioral imputation, as compared to serologically estimated HIV incidence. Recent HIV incidence among YMSM (aged 18 to 21 and 18 to 24 years) enrolled in a cohort study in Bangkok from 2006 to 2014 was estimated using two mid-point methods for seroconversion: 1) between age of first anal intercourse and first HIV-positive test (without previous HIV-negative test) (behavioral imputation) and 2) between the date of last negative and first positive HIV test (serological estimation). Serologically estimated HIV incidence was taken as the “gold standard” to evaluate between-method agreement. At baseline, 314 YMSM age 18 to 21 years accumulated 674 person-years (PY) of follow-up since first anal intercourse. Considering that 50 men had prevalent HIV infection, the behaviorally imputed HIV incidence was 7.4 per 100 PY. Of the remaining 264 HIV-negative men, 54 seroconverted for HIV infection during the study, accumulating 724 PY of follow-up and a serologically estimated HIV incidence of 7.5 per 100 PY. At baseline, 712 YMSM age 18 to 24 years (including 18 to 21-year-old men analyzed above) accumulated 2143 PY of follow-up since first anal intercourse. Considering that 151 men had prevalent HIV infection, the behaviorally imputed HIV incidence was 7.0 per 100 PY. Of the remaining 561 HIV-negative men, 125 seroconverted for HIV infection during the study, accumulating 1700 PY of follow-up and a serologically estimated HIV incidence of 7.4 per 100 PY. Behavioral imputation and serological estimation are in good agreement when estimating recent HIV incidence in YMSM.
More than thirty years into the HIV epidemic, simple, affordable and reliable methods to estimate recent HIV incidence in populations at risk are not available. Recently, this inadequacy has become particularly salient against the background of increasing HIV prevalence observed in young people, especially in young men who have sex with men (YMSM) . For socio-cultural and legal reasons, collection of repeated cross-sectional and prospective serological specimens at younger ages for HIV incidence monitoring is difficult. As a result, such specimens are rarely available, especially of those younger than 21 years of age. Cohort studies provide the best measures of risk and HIV incidence, while taking in account accrual and loss-to-follow-up. In addition, such studies allow causal inference and risk factor assessment for incident HIV infection. However, cohort studies are costly, labor and participant intensive, logistically difficult to implement and sustain, and require clinical infrastructure and an enabling environment. Since incident HIV infection is a relatively rare event, large sample-sizes are needed, while infection is known to occur more often in those not-enrolled or lost-to-follow-up. Nevertheless, cohort studies are essential in guiding and powering HIV intervention studies and in monitoring the overall course of the HIV epidemic. Because of these difficulties, HIV incidence estimates are usually derived from mathematical models [2, 3], or from laboratory methods using increasing and decreasing HIV immune responses to decide on recency of infection . Similarly, epidemic monitoring usually relies on cross-sectional data, such as HIV and AIDS case reports and behavioral and biological surveillance in key populations. While this information is important, uncertainty remains about recency of infection and time-order of events and often data are not age-disaggregated or those of younger ages are under-represented or ineligible. Methods for estimating HIV incidence from cross-sectional data, HIV prevalence surveys or service data have been proposed, including mathematical model-based approaches utilizing a single prevalence survey in near stable conditions [5–7]. Or more generally, incorporating historical data on changes in HIV prevalence and AIDS mortality , or from two prevalence surveys in the same population at two different time-points [9, 10]. A related approach is to create an artificial cohort from repeated HIV prevalence surveys along with mortality data to estimate HIV incidence while accounting for population dynamics . If mortality data are not available, the use of the incubation time distribution to AIDS and death may be used as a proxy for this information [11, 12]. Another method is to utilize information from linkable repeat HIV testing and counseling attendees to create an open cohort of persons at risk for HIV infection [13–15]. Recent enhancements to laboratory testing include antibody avidity evaluation and prior HIV testing history, CD4+ cell counts and HIV RNA viral load levels to account for false-recent HIV- positives [4, 16–18]. Some of these alternative methods have been compared for agreement [10, 15]. In daily practice and outside of controlled situations, the predictive value and external validity of available HIV incidence methods have been limited and their use unsuccessful.
Prior to enrollment, 314 YMSM age 18 to 21 years accumulated 674 PY of follow-up since first anal intercourse exposure. Considering that 50 men had prevalent HIV infection, the behaviorally imputed HIV incidence was 7.4 per 100 PY (95% CI: 5.4, 9.5) (Table 1). Of the remaining 264 HIV-negative YMSM of this age, 54 seroconverted for HIV infection during the study, accumulating 724 PY of follow-up and a serologically estimated HIV incidence of 7.5 per 100 PY (95% CI: 5.6, 9.7) (Table 1). Serologically and behaviorally imputed HIV incidence estimates were similar with an observed rate difference of 0.04 and not statistically significant (95% CI: -2.8, 2.9). Behaviorally imputed HIV incidence did not change after adjustment for self-reported date of HIV-positive testing (n = 3) prior to study entry. Prior to enrollment, 712 YMSM age 18 to 24 years (including men 18 to 21 years analyzed above) accumulated 2143
In this evaluation of serological versus behaviorally imputed estimations of HIV incidence in YMSM, reliability between the two methods was established. Concordance was found among YMSM 18 to 21 years as well as among those of 18 to 24 years old. This suggests that OA may be applied to a wider age-bracket than previously done [20, 21, 23]. Our study generated robust serologically and behaviorally imputed estimates of HIV incidence. It had eight times the number of HIV sero-conversions compared to the SFYMHS, in which behavioral imputation was originally implemented . Except for ascertainment of age at start of anal intercourse, commonly included as part of cross-sectional surveys among MSM, no additional data are required for behavioral imputation. This method may therefore provide a simple, cheap and reliable technique for monitoring recent HIV incidence in YMSM in settings where longitudinal data are not available.