ObjectiveâAssays for classifying HIV infections as ârecentâ or ânon-recentâ for incidencesurveillance fail to simultaneously achieve large mean durations of ârecentâ infection (MDRIs) andlow âfalse-recentâ rates (FRRs), particularly in virally suppressed persons. The potential foroptimizing recent infection testing algorithms (RITAs), by introducing viral load criteria andtuning thresholds used to dichotomize quantitative measures, is explored.DesignâThe Consortium for the Evaluation and Performance of HIV Incidence Assayscharacterized over 2000 possible RITAs constructed from seven assays (LAg, BED, Less-sensitiveVitros, Vitros Avidity, BioRad Avidity, Architect Avidity and Geenius) applied to 2500 diversespecimens.MethodsâMDRIs were estimated using regression, and FRRs as observed ârecentâ proportions,in various specimen sets. Context-specific FRRs were estimated for hypothetical scenarios. FRRswere made directly comparable by constructing RITAs with the same MDRI through the tuning ofthresholds. RITA utility was summarized by the precision of incidence estimation.ResultsâAll assays produce high FRRs amongst treated subjects and elite controllers(10%-80%). Viral load testing reduces FRRs, but diminishes MDRIs. Context-specific FRRs varysubstantially by scenario â BioRad Avidity and LAg provided the lowest FRRs and highestincidence precision in scenarios considered.ConclusionsâThe introduction of a low viral load threshold provides crucial improvements inRITAs. However, it does not eliminate non-zero FRRs, and MDRIs must be consistentlyestimated. The tuning of thresholds is essential for comparing and optimizing the use of assays.The translation of directly measured FRRs into context-specific FRRs critically affects theirmagnitudes and our understanding of the utility of assays.