Updated Risk Score Algorithms for Acute HIV Infection Detection at a Sexually Transmitted Infections Clinic in Lilongwe, Malawi.

Abstract

BACKGROUND Detection of acute (pre-seroconversion) HIV infection (AHI), the phase of highest transmission risk, requires resource-intensive RNA- or antigen-based detection methods that can be infeasible for routine use. Risk score algorithms can improve the efficiency of AHI detection by identifying persons at highest risk of AHI for prioritized RNA/antigen testing, but prior algorithms have not considered geospatial information, potential differences by sex, or current antibody testing paradigms. METHODS We used elastic net models to develop sex-stratified risk score algorithms in a case-control study of persons (136 with AHI, 250 without HIV) attending a sexually transmitted infections (STI) clinic in Lilongwe, Malawi from 2015 to 2019. We designed algorithms for varying clinical contexts according to three levels of data availability: 1) routine demographic and clinical information, 2) behavioral and occupational data obtainable through patient interview, and 3) geospatial variables requiring external datasets or field data collection. We calculated sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) to assess model performance and developed a web application to support implementation. RESULTS The highest-performing AHI risk score algorithm for men (AUC=0.74) contained five variables (condom use, body aches, fever, rash, genital sores/ulcers) from the first two levels of data availability. The highest-performing algorithm for women (AUC=0.81) contained fifteen variables from all three levels of data availability. A risk score cut-point of 0.26 had an AHI detection sensitivity of 93% and specificity of 27% for males, and a cut-point of 0.15 had 97% sensitivity and 44% specificity for females. Additional models are available in the web application. CONCLUSION Risk score algorithms can facilitate efficient AHI detection in STI clinic settings, creating opportunities for HIV transmission prevention interventions during this critical period of elevated transmission risk.