Validating HIV viral suppression threshold adjustments for comparable estimates using data from nationally representative household surveys in sub-Saharan Africa

IntroductionTo enable comparable global assessments of viral load suppression (VLS) among people living with HIV on antiretroviral therapy (ART), UNAIDS applies a model to adjust VLS estimates reported at different thresholds to a common VL [&le;]1000 copies/mL definition. We assessed performance of the current reverse Weibull model and alternatives using survey data from sub-Saharan Africa. MethodsUsing data from 21 Population-based HIV Impact Assessment surveys (PHIAs) in 16 sub-Saharan African countries (2015-2022), we assessed six models (Weibull, reverse Weibull, Pareto, Frechet, gamma, and lognormal) in adjusting VLS reported at VL <50, <200, <400 copies/mL to [&le;]1000. We compared predictions using parameters from Johnson et al. and recalibrated using PHIAs, assessing whether new shape parameters improved adjustments and varied by sex and age. ResultsIn adjustments from all thresholds, the Weibull model had the lowest prediction errors (Root-mean-squared error for <200 to [&le;]1000: Weibull: 1.9%; reverse Weibull: 3.1%; Pareto: 2.5%). Prediction errors for reverse Weibull and Pareto models were higher in subgroups with low VLS, compared to Weibull. Across 21 surveys, in adjustments from <200 to [&le;]1000, reverse Weibull overestimated VLS by 2.3%, compared to 1.5% by Weibull and Pareto. The Frechet, gamma, and lognormal models performed similarly to Weibull. Shape parameter estimates for the Weibull and reverse Weibull were slightly higher after recalibration and varied by sex and age. ConclusionThe Weibull, Frechet, gamma, and lognormal models, provided more reliable VLS adjustments across thresholds than the previously recommended reverse Weibull model, avoiding inflated VLS estimates which could obscure gaps in HIV treatment programmes and underestimate HIV transmission risks.