Designing HIV Testing Algorithms Based on 2015 WHO Guidelines Using Data from Six Sites in Sub-Saharan Africa

Our objective was to evaluate the performance of HIV testing algorithms based on WHO recommendations, using data from specimens collected at six HIV testing and counseling sites in sub-Saharan Africa (Conakry, Guinea; Kitgum and Arua, Uganda; Homa Bay, Kenya; Douala, Cameroon; Baraka, Democratic Republic of Congo). A total of 2,780 samples, including 1,306 HIV-positive samples, were included in the analysis. HIV testing algorithms were designed using Determine as a first test. Second and third rapid diagnostic tests (RDTs) were selected based on site-specific performance, adhering where possible to the WHO-recommended minimum requirements of ≥99% sensitivity and specificity. The threshold for specificity was reduced to 98% or 96% if necessary. We also simulated algorithms consisting of one RDT followed by a simple confirmatory assay. The positive predictive values (PPV) of the simulated algorithms ranged from 75.8% to 100% using strategies recommended for high-prevalence settings, 98.7% to 100% using strategies recommended for low-prevalence settings, and 98.1% to 100% using a rapid test followed by a simple confirmatory assay. Although we were able to design algorithms that met the recommended PPV of ≥99% in five of six sites using the applicable high-prevalence strategy, options were often very limited due to suboptimal performance of individual RDTs and to shared falsely reactive results. These results underscore the impact of the sequence of HIV tests and of shared false-reactivity data on algorithm performance. Where it is not possible to identify tests that meet WHO-recommended specifications, the low-prevalence strategy may be more suitable.