Specificity of Four Laboratory Approaches for Cross-Sectional HIV Incidence Determination: Analysis of Samples from Adults with Known Nonrecent HIV Infection from Five African Countries

Abstract

Assays to determine cross-sectional HIV incidence misclassify some individuals with nonrecent HIV infection as recently infected, overestimating HIV incidence. We analyzed factors associated with false-recent misclassification in five African countries. Samples from 2197 adults from Botswana, Kenya, South Africa, Tanzania, and Uganda who were HIV infected > 12 months were tested using the (1) BED capture enzyme immunoassay (BED), (2) avidity assay, (3) BED and avidity assays with higher assay cutoffs (BED+ avidity screen), and (4) multiassay algorithm (MAA) that includes the BED+ avidity screen, CD4 cell count, and HIV viral load. Logistic regression identified factors associated with misclassification. False-recent misclassification rates and 95% confidence intervals were BED alone: 7.6% (6.6, 8.8); avidity assay alone: 3.5% (2.7, 4.3); BED+ avidity screen: 2.2% (1.7, 2.9); and MAA: 1.2% (0.8, 1.8). The misclassification rate for the MAA was significantly lower than the rates for the other three methods (each p < 0.05). Misclassification rates were lower when the analysis was limited to subtype C-endemic countries, with the lowest rate obtained for the MAA [0.8% (0.2, 1.9)]. Factors associated with misclassification were for BED alone: country of origin, antiretroviral treatment (ART), viral load, and CD4 cell count; for avidity assay alone: country of origin; for BED+ avidity screen: country of origin and ART. No factors were associated with misclassification using the MAA. In a multivariate model, these associations remained significant with one exception: the association of ART with misclassification was completely attenuated. A MAA that included CD4 cell count and viral load had lower false-recent misclassification than the BED or avidity assays (alone or in combination). Studies are underway to compare the sensitivity of these methods for detection of recent HIV infection