CROI 2015 Program and Abstracts

Abstract Listing

Oral Abstracts

Conclusions: This is, to our knowledge, the first nation-wide evaluation examining the effect of ART on incidence. Our findings demonstrate a large preventive effect associated with ART coverage. As scale-up to new guidelines and targeted populations increase, the preventive effects of ART coverage will likely contribute to greater declines in population incidence. 158 Impact of Male Circumcision Scale-Up on Community-Level HIV Incidence in Rakai, Uganda Xiangrong Kong 1 ; Godfrey Kigozi 2 ; Fred Nalugoda 2 ; David Serwadda 3 ; Maria J.Wawer 1 ; Ronald H. Gray 1 On behalf of the Rakai Health Sciences Program 1 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, US; 2 Rakai Health Sciences Program, Entebbe, Uganda; 3 Makerere University College of Health Sciences, Kampala, Uganda Background: Randomized trials showmale circumcision (MC) reduces individual level risk of HIV acquisition by 50-60% in men, and MC has been scaled up in sub-Saharan Africa. We assessed the impact of MC coverage on community level HIV incidence among non-Muslimmen in Rakai, Uganda. Methods: The Rakai Community Cohort Study (RCCS) conducts ~ annual surveillance of consenting residents aged 15-49 in 43 rural communities consistently since 1999. Before 2003, MC was largely confined to Muslimmen. MC services to non-Muslims were provided through randomized trials during 2004-07 and were scaled up via a PEPFAR program since 2008. For each community, the non-Muslimmale population prevalence of MC and HIV incidence per 100 person years (py) was estimated before the MC trials (period 1: 1999 -2003), during the trials (period 2: 2004-07), and since the MC scale up (period 3: 2008-11). Incidence rate ratio (IRR) of community level (CL) HIV incidence associated with CL MC prevalence was estimated by Poisson log-linear regression. Adjusted IRR was also estimated adjusting for potential confounding due to potential population composition change over time (measured by the surrogate of time periods) and CL ART coverage among HIV+s. Results: In period 1, the mean CL HIV incidence among non-Muslimmen was 1.4/100pys (range 0-4.1/100pys); and mean CL MC prevalence was 4.1% (range 1-8%). ART was not available during this period. In period 2, the mean CL HIV incidence was 0.9/100pys (range 0-3.7/100pys), mean CL MC prevalence was 10.0% (range 0-30%), and the mean CL ART prevalence was 5.2% (range 0-13%). In period 3, the mean CL HIV incidence was 1.1/100pys (range 0-3.6/100pys), mean CL MC prevalence was 23.5% (range 0-45%), and mean ART prevalence was 17.9% (range 3-42%). For every 10% increase in CL MC prevalence among non-Muslims, the associated IRR of CL HIV incidence was 0.85 (p=0.006, 95% Confidence Interval [CI] 0.75-0.95). After adjusting for time period and CL ART prevalence, CL MC prevalence had an adjusted IRR of 0.81 (p =0.076, 95% CI 0.65-1.02). Conclusions: The MC program reached 23.5% coverage among non-Muslimmen in Rakai by 2011, with large variations across communities. A 10% increase in community level MC coverage was associated with a 15% (95%CI 5-25%) reduction in CL HIV incidence among non-Muslimmen, and this reduction of CL HIV risk was robust after adjusting for potential confounding due to time period and CL ART coverage. 159 Effects of Antiretroviral Treatment on Health Care Utilization in Rural South Africa Jan A. Hontelez 1 ; FrankTanser 2 ; Sake J. deVlas 1 ; Kevindra K. Naidu 2 ; Rob Baltussen 3 ; Deenan Pillay 2 ;Till Barnighausen 2 1 Erasmus University Medical Center, Nijmegen, Netherlands; 2 Africa Centre for Health and Population Studies, Somkhele, South Africa; 3 Radboud University Medical Centre, Nijmegen, Netherlands Background: The impact of the rapid scale-up of vertical antiretroviral treatment (ART) programs for HIV in sub-Saharan Africa on the overall health system is under intense debate. Some argue that HIV treatment programs are draining resources for the treatment of other diseases, while others have claimed that the investments through ART programs benefitted the health system. To establish the population-level impact of ART programs on health care utilization in the public-sector health system, we compare trends in health care utilization among HIV-infected people receiving and not receiving ART with HIV-uninfected people during a period of rapid ART scale-up. Methods: We used data from one of Africa’s largest population-based cohorts, the longitudinal surveillance conducted by the Wellcome Trust Africa Centre for Health and Population Studies, which annually elicits information on health care utilization from all surveillance participants over the period 2009-2012 (N=44,461). We determined trends in hospitalization, and public and private primary health care (PHC) clinic visits for HIV-infected and -uninfected people over the period 2009-2012, and regressed utilization rates by HIV and ART status over time, controlling for sex, age, time on ART, and area of living. Results: The proportion of people who reported to have visited a PHC clinic in the last 6 months increased significantly over the period 2009-2012, for both HIV-infected people not on ART (from 53% to 60%; p<0.001), and HIV-uninfected people (from 41% to 47%; p<0.001) (figure 1A). In contrast, the proportion of HIV-infected people not on ART visiting a private physician declined from 21% to 13% (p<0.001) (figure 1B) and hospitalization rates declined from 100 to 71 per 1000 PY (p<0.001) (Figure 1C). For HIV-uninfected people, the proportion visiting a private physician declined from 15% to 9%, and hospitalization rates declined from 78 to 44 per 1000 PY (p<0.001). All trends were sustained when controlling for potential confounders.

Oral Abstracts

Figure 1. Trend in age-standardized self-reported health care utilization by HIV and ART status over the years 2009 to 2012 in rural KwaZulu-Natal, South Africa. A. Proportion of people reporting to have visited a public PHC clinic in the last 6 months. B. Proportion of people reporting to have visited a private PHC clinic in the last 6 months. C. Self-reported hospitalization rates over the last 12 months

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CROI 2015