HIV-1 Recent Infection Testing Algorithm With Antiretroviral Drug Detection to Improve Accuracy of Incidence Estimates.

Abstract

BACKGROUND\nHIV-1 incidence calculation currently includes recency classification by HIV-1 incidence assay and unsuppressed viral load (VL ≥ 1000 copies/mL) in a recent infection testing algorithm (RITA). However, persons with recent classification not virally suppressed and taking antiretroviral (ARV) medication may be misclassified.\n\n\nSETTING\nWe used data from 13 African household surveys to describe the impact of an ARV-adjusted RITA on HIV-1 incidence estimates.\n\n\nMETHODS\nHIV-seropositive samples were tested for recency using the HIV-1 Limiting Antigen (LAg)-Avidity enzyme immunoassay, HIV-1 viral load, ARVs used in each country, and ARV drug resistance. LAg-recent result was defined as normalized optical density values ≤1.5. We compared HIV-1 incidence estimates using 2 RITA: RITA1: LAg-recent + VL ≥ 1000 copies/mL and RITA2: RITA1 + undetectable ARV. We explored RITA2 with self-reported ARV use and with clinical history.\n\n\nRESULTS\nOverall, 357 adult HIV-positive participants were classified as having recent infection with RITA1. RITA2 reclassified 55 (15.4%) persons with detectable ARV as having long-term infection. Those with detectable ARV were significantly more likely to be aware of their HIV-positive status (84% vs. 10%) and had higher levels of drug resistance (74% vs. 26%) than those without detectable ARV. RITA2 incidence was lower than RITA1 incidence (range, 0%-30% decrease), resulting in decreased estimated new infections from 390,000 to 341,000 across the 13 countries. Incidence estimates were similar using detectable or self-reported ARV (R2 > 0.995).\n\n\nCONCLUSIONS\nIncluding ARV in RITA2 improved the accuracy of HIV-1 incidence estimates by removing participants with likely long-term HIV infection.