CROI 2017 Abstract e-Book

Abstract eBook

Poster and Themed Discussion Abstracts

14(p<0.0001). Attrition post-ART at 12 months overall was 25.7% (95%CI 25.6-25.9) and increased over time from 22.6%(95%CI 22.3-23.0) in 2005-06 to 30.6%(95%CI 30.1-31.1) in 2013-14(p<0.0001). Conclusion: Over 10 years of HIV care and treatment scale up in four countries, close to a million patients were enrolled in care and more than half started ART. Over time patients

were healthier at enrollment, attrition decreased among pre-ART patients and increased among those on ART. 1024 DISTRIBUTION OF HIV TRANSMISSION BY NETWORK AND CLINICAL FACTORS AMONG US MSM Johanna Chapin-Bardales 1 , Samuel Jenness 1 , Eli Rosenberg 1 , Patrick Sullivan 1 , Steven M. Goodreau 2 1 Emory Univ, Atlanta, GA, USA, 2 Univ of Washington, Seattle, WA, USA

Background: Men who have sex with men (MSM) continue to experience high HIV incidence in the United States. Sexual role, partnership types, infection stage, and care engagement strongly determine HIV transmission rates within serodiscordant MSM partnerships. Estimating the distribution of transmissions by these factors is critical to targeting prevention efforts. Previous studies to estimate the distribution of transmissions by these factors have yielded conflicting results and significant debate, likely due to heterogeneous populations and methods. We assessed all factors in one comprehensive US-based model in order to provide internally-consistent and actionable estimates. Methods: A mathematical model simulated HIV transmission dynamics within sexual partnership networks of US MSM over a 10-year period. Parameters were estimated from HIV cohorts in Atlanta and national behavioral and clinical literature. We estimated population attributable fractions (PAFs) and 95% credible intervals by network and behavioral factors within partnerships and clinical status of the infected partner. Results: Among all incident HIV infections, 42% occurred in main partnerships, 48% in casual partnerships, and 10% in one-time partnerships. Three-quarters (75%) of transmissions were to the receptive AI partner. One in five transmissions (21%) originated from an acute-stage partner, 60% from a non-AIDS chronic-stage partner, and 19% from a partner who progressed to AIDS. Nearly all infections resulted from AI with an infected partner who was undiagnosed (31%) or who was not retained in care (61%); few infections occurred during time on ART with partial (5%) or full (1%) viral suppression. Conclusion: Our model suggests two high-value targets for prevention: MSM in non-main partnerships and in partnerships in which the infected partner has fallen out of HIV care. Assessing risk behavior specific to partnership type remains necessary to tailoring the delivery of HIV prevention tools. Targeting strategies may emphasize PrEP for HIV- negative MSM in non-main partnerships as partners’ HIV status or care engagement may be unknown. Within main serodiscordant partnerships, strategies may include PrEP for the HIV-negative partner and support for the HIV-positive partner to remain effectively engaged in care. Because HIV-positive men not retained in care contribute the majority of ongoing HIV transmissions, efforts to engage these men individually and through their partnerships will be challenging but essential. 1025 HIV TRANSMISSION IN GENERALIZED, CONCENTRATED, AND MIXED EPIDEMICS IN WESTERN KENYA Anna Bershteyn 1 , Vibhuti Hate 2 , Daniel J. Klein 1 , Zindoga Mukandavire 3 , Graham F. Medley 3 , Wanjiru Mukoma 4 , Michael K. Kiragu 4 , Kristine Torjesen 5 , Nduku Kilonzo 6 , Katharine Kripke 7 , for the OPTIONS Consortium 1 Inst for Disease Modeling, Bellevue, WA, USA, 2 The George Washington Univ, Washington, DC, USA, 3 London Sch of Hygiene and Trop Med, London, United Kingdom, 4 LVCT Hlth, Nairobi, Kenya, 5 FHI 360, Durham, NC, USA, 6 Natl AIDS Control Council, Ministry of Hlth, Nairobi, Kenya, 7 Avenir Hlth, Washington, DC, USA Background: HIV prevention planning requires information about those at highest risk of acquiring and transmitting HIV. Kenya exhibits a range of subnational HIV epidemic patterns including highly concentrated, highly generalized, and mixed HIV epidemics. This analysis identifies transmission patterns in each of the six counties of the former Nyanza province based on overall epidemic trends as well as high-risk sub-populations such as female sex workers (FSW) and their clients. Methods: A literature review identified characteristics of FSW and their clients, defined here as “high” risk, and strata of the general population who were not FSW or clients but at increased risk of HIV infection, defined here as “medium” risk. Characteristics of FSW such as age, duration in sex work, population size based on a recent FSW enumeration, and number of clients were incorporated into an existing HIV microsimulation model, EMOD-HIV v2.5. Setting-specific data on fertility, mortality, traditional male circumcision and scale-up of voluntary male medical circumcision, HIV testing and treatment rates, and HIV treatment guidelines were incorporated and the model was fit to age and gender stratified HIV prevalence from four cluster-randomized surveys. Results: Kenya counties were placed on a spectrum of generalized, concentrated, low-level, or mixed epidemics according to overall HIV prevalence and the proportion of adult females who were FSW in 2012 (Figure 1a). In every county, incidence rates were highest among FSW and their clients, but the overall number of new infections was higher in the general population (Figure 1b). In Kisii, which exhibits the most concentrated epidemic in Nyanza, numbers of new infections were similar in medium risk and high risk (FSW and clients). In other counties, new infections in medium risk exceeded those in FSW and clients. Surprisingly, the number of transmissions originating frommedium risk exceeded those in high- and low-risk individuals in all counties, including Kisii. Conclusion: While FSW and their clients experience the highest HIV incidence, the largest contribution to HIV transmission in the Nyanza region comes frommore numerous “medium” risk individuals, defined as those at high risk of HIV infection in the general population, but not FSW or their clients. Broadly available and acceptable HIV prevention in the general population is needed to maximize the impact on the HIV epidemic.

Poster and Themed Discussion Abstracts

CROI 2017 442