• Andrea A Kim and Thomas Rehle.
• 1 Division of Global HIV and Tuberculosis, Center for Global Health, U.S. Centers for Disease Control and Prevention , Atlanta, Georgia .
• AIDS Res. Hum. Retroviruses. 2018 Oct 1; 34 (10): 863-866.

AbstractA recent infection testing algorithm (RITA) that includes a test for recent HIV infection and a viral load (VL) test is the recommended strategy to estimate national HIV incidence, reducing false-recent misclassification to <1%. The inclusion of information on exposure to antiretroviral therapy (ART), as a supplement to VL testing, could improve RITA performance by further lowering false-recent misclassification of true long-term infection. In 2012, Kenya and South Africa conducted national population-based surveys that collected information on HIV recency (i.e., HIV antibody seroconversion, on average, in the past 130 days) using the Limiting Antigen avidity (LAg-Avidity) enzyme immunoassay, HIV RNA levels, and ART exposure among HIV-infected respondents aged 15-49 years. In Kenya, ART exposure was defined as testing positive for one or more antiretroviral (ARV) drugs using high-performance liquid chromatography coupled with tandem mass spectrometry, and, if not ARV-positive, self-reporting a history of ART exposure. In South Africa, ART exposure was defined as testing ARV-positive. Two RITA strategies were compared: RITA #1 defined recent infection as testing LAg-Avidity-recent with unsuppressed VL (HIV RNA ≥1,000 copies/ml), and RITA #2 defined recent infection as testing LAg-Avidity-recent with unsuppressed VL and, if unsuppressed, having no ART exposure. RITA-derived incidence among persons aged 15-49 years in Kenya was 0.9% on RITA #1 and 0.8% on RITA #2. In South Africa, RITA-derived incidence was 2.2% on RITA #1 and 1.7% on RITA #2. Among specimens testing recent with unsuppressed VL in Kenya and South Africa, 16.0% and 19.7% had evidence of ART exposure, respectively. Although the performance of a VL- and ART-based RITA was encouraging, additional research is needed across HIV-1 subtypes and subpopulations to calibrate and validate this algorithm.

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