An HIV-1 risk assessment tool for women aged 15-49 in African countries: A pooled analysis across 15 nationally representative surveys.

BACKGROUND:Women in Africa disproportionately acquire HIV-1. Understanding which women are most likely to acquire HIV-1 can guide focused prevention with pre-exposure prophylaxis (PrEP). Our objective is to identify women at highest risk of HIV-1 and estimate PrEP efficiency at different sensitivity levels. METHODS:Nationally representative data were collected from 2015-2019 from 15 population-based household surveys. This analysis included women aged 15-49 who tested HIV-1 sero-negative or had recent HIV-1. Least absolute shrinkage and selection operator regression models were fit with 28 variables to predict recent HIV-1. Models were trained on the full population and internally cross-validated. Performance was evaluated using area under the receiver-operating-characteristic curve (AUC), sensitivity, and number needed to treat (NNT) with PrEP to avert one infection. RESULTS:Among 209,012 participants 248 had recent HIV-1 infection, representing 118 million women and 402,000 (95% CI: 309,000-495,000) new annual infections. Two variables were retained in the model: living in a subnational area with high HIV-1 viremia and having a sexual partner living outside the home. Full-population AUC was 0.80 (95% CI: 0.76-0.84); cross-validated AUC was 0.79 (95% CI: 0.75-0.84). At a sensitivity of 33%, up to 130,000 cases could be averted if 7.9 million women were perfectly adherent to PrEP; NNT would be 61. At a sensitivity of 67%, up to 260,000 cases could be averted if 25.1 million women were perfectly adherent to PrEP; the NNT would be 96. CONCLUSIONS:This risk assessment tool was generalizable, predictive, and parsimonious with tradeoffs between reach and efficiency.