Modeling the Impact of PrEP Programs for Adolescent Sexual Minority Males Based on Empirical Estimates for the PrEP Continuum of Care

Abstract

Purpose: Pre-exposure prophylaxis (PrEP)—an effective and safe intervention to prevent HIV transmission—was recently approved by the Food and Drug Administration for use by adolescents. Informed by studies of sexual behavior and PrEP adherence, retention, and promotion, we model the potential impact of PrEP use among at-risk adolescent sexual minority males. Methods: We simulate an HIV epidemic among men who have sex with men (MSM) aged 13–39. We assume adult MSM ages 19–39 have had PrEP available for 3 years with 20% coverage among eligible MSM based on the Centers for Disease Control and Prevention guidelines. PrEP interventions for ages 16–18 are then simulated using adherence and retention profiles drawn from the ATN113 and Enhancing Preexposure Prophylaxis in Community studies across a range of uptake parameters (10%–100%). Partnerships across age groups were modeled using parameterizations from the RADAR study. We compare the percent of incident infections averted (impact), person-years on PrEP per infection averted (efficiency), and changes in prevalence over 10 years. Results: As compared to no PrEP use, baseline PrEP adherence and retention among adolescent sexual minority males drawn from the ATN113 and Enhancing Preexposure Prophylaxis in Community studies averted from 2.8% to 41.0% of HIV infections depending on the fraction of eligible adolescent sexual minority males that initiated PrEP at their annual health-care visit. Improved adherence and retention achieved with an array of focused interventions from real-world settings increased the percent of infections averted by as much as 26%–70%. Conclusions: Empirically demonstrated improvements in the PrEP continuum of care in response to existing interventions can substantially reduce incident HIV infections among adolescent sexual minority males.

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“…The ABNM combines an agent-based simulation approach with modeling of a sexual network structure and includes a number of processes that impact HIV transmission (described below). The sexual network structure was estimated using exponential random graph models;26 this approach is consistent with the methodology deployed in recent work across US urban areas 27–29. The ABNM presented here was implemented using the statnet30 suite of packages in the R programming language to simulate dynamic networks.…”

“…The sexual network structure was estimated using exponential random graph models; 26 this approach is consistent with the methodology deployed in recent work across US urban areas. [27][28][29] The ABNM presented here was implemented using the statnet 30 suite of packages in the R programming language to simulate dynamic networks. The ABM components were developed with the C ++ -based Repast HPC ABM toolkit.…”

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“…The extension EpiModelHIV R package was used to incorporate the relevant HIV-specific epidemiology for this study [ https://github.com/EpiModel/EpiModelHIV ]. Similar models have been used previously to model HIV and STI interventions and outcomes in other contexts [ 7 , 14 , 15 ]. Full details of the model and parameters are in the technical appendix (Supplemental Material 1 ), but we provide a brief overview here.…”

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“…Mathematical modeling has been used to evaluate the potential impact of diverse HIV interventions on HIV transmission, morbidity, mortality, and other outcomes 11–15 and to prioritize resource allocation. 16 The objective of this study was to model the potential impact of the HIV-1 nucleic acid testing, linkage, treatment, and PNS interventions, as delivered in the Tambua Mapema Plus (TMP) trial, on the Kenyan HIV epidemic.…”

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