Determination of HIV status and identification of incident HIV infections in a large, community-randomized trial: HPTN 071 (PopART)

INTRODUCTION: The HPTN 071 (PopART) trial evaluated the impact of an HIV combination prevention package that included "universal testing and treatment" on HIV incidence in 21 communities in Zambia and South Africa during 2013-2018. The primary study endpoint was based on the results of laboratory-based HIV testing for> 48,000 participants who were followed for up to three years. This report evaluated the performance of HIV assays and algorithms used to determine HIV status and identify incident HIV infections in HPTN 071, and assessed the impact of errors on HIV incidence estimates. METHODS: HIV status was determined using a streamlined, algorithmic approach. A single HIV screening test was performed at centralized laboratories in Zambia and South Africa (all participants, all visits). Additional testing was performed at the HPTN Laboratory Center using antigen/antibody screening tests, a discriminatory test and an HIV RNA test. This testing was performed to investigate cases with discordant test results and confirm incident HIV infections. RESULTS: HIV testing identified 978 seroconverter cases. This included 28 cases where the participant had acute HIV infection at the first HIV-positive visit. Investigations of cases with discordant test results identified cases where there was a participant or sample error (mixups). Seroreverter cases (errors where status changed from HIV infected to HIV uninfected, 0.4% of all cases) were excluded from the primary endpoint analysis. Statistical analysis demonstrated that exclusion of those cases improved the accuracy of HIV incidence estimates. CONCLUSIONS: This report demonstrates that the streamlined, algorithmic approach effectively identified HIV infections in this large cluster-randomized trial. Longitudinal HIV testing (all participants, all visits) and quality control testing provided useful data on the frequency of errors and provided more accurate data for HIV incidence estimates