An HIV-1 Risk Assessment Tool For Men Aged 15-59 Years in 13 African Countries: a Pooled Analysis of Nationally Representative Surveys.
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Alternative Title:Journal of Acquired Immune Deficiency Syndromes (1999), 2026, v. 101, no. 2: An HIV-1 Risk Assessment Tool For Men Aged 15-59 Years in 13 African Countries: a Pooled Analysis of Nationally Representative Surveys.
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Journal Article:Journal of Acquired Immune Deficiency Syndromes (1999)
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Description:Globally, approximately half of new HIV acquisitions occur among African adults. This analysis examines which cisgender men are at highest risk of acquiring HIV-1 and in greatest need of HIV pre-exposure prophylaxis (PrEP).
National population-based surveys from Eswatini, Ivory Coast, Kenya, Lesotho, Malawi, Namibia, Nigeria, Rwanda, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe.
The 13 surveys were pooled and sampling weights were applied to represent all susceptible men aged 15-59 years old. HIV-1 incidence was calculated based on a recent HIV-1 testing algorithm. A least absolute shrinkage and selection operator (Lasso) regression model was fit with 28 variables to predict recent HIV-1. Models were trained and internally cross-validated to estimate area under the receiver-operating characteristic curve (AUC). Along the receiver-operating characteristic curve, at sensitivity levels from 10% to 90%, performance tradeoffs were evaluated.
Of 167,121 participants, 112 had recent HIV-1, representing 256,000 new annual infections among 122 million men. Only 2 variables were retained-reporting a male sexual partner and living in a subnational area where a high proportion of adults have detectable HIV-1 viremia. Overall AUC was 0.80 (95% Confidence Interval: 0.71 to 0.89); cross-validated AUC was 0.76 (95% CI: 0.64 to 0.87). At 10% sensitivity, 25,000 cases could be averted if 357,000 men adhered to PrEP (Number Needed to Treat = 14). At 90% sensitivity, 229,000 cases could be averted if 50 million men adhered to PrEP (Number Needed to Treat = 219).
This predictive, parsimonious, generalizable risk assessment tool could help policymakers weigh tradeoffs between PrEP reach and efficiency. -
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ISSN:1525-4135 ; 1944-7884
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Pubmed ID:41065287
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Pubmed Central ID:PMC13009710
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Funding:U54CA254568/NH/NIH HHSUnited States/ ; UGGH002172/CC/CDC HHSUnited States/ ; U54TW012041/NH/NIH HHSUnited States/ ; R01HD105526/NH/NIH HHSUnited States/ ; R01AI176309/NH/NIH HHSUnited States/ ; U2GGH00217/CC/CDC HHSUnited States/ ; R21MH125705/NH/NIH HHSUnited States/ ; D43TW012274/NH/NIH HHSUnited States/ ; R21 MH134750/MH/NIMH NIH HHSUnited States/ ; K01AI182506/NH/NIH HHSUnited States/ ; 5NU2GGH001226/CC/CDC HHSUnited States/ ; 1U2GGH00094/CC/CDC HHSUnited States/ ; R01HL165686/NH/NIH HHSUnited States/ ; U2GGH001271/CC/CDC HHSUnited States/ ; R01AI147331/NH/NIH HHSUnited States/ ; U01CA275048/NH/NIH HHSUnited States/ ; UGGH002108/CC/CDC HHSUnited States/ ; NU2GGH001629/CC/CDC HHSUnited States/ ; K24AI120796/NH/NIH HHSUnited States/ ; U01AI096299/NH/NIH HHSUnited States/ ; P30AI050410/NH/NIH HHSUnited States/ ; UG1HD113162/NH/NIH HHSUnited States/ ; NU2GGH001271/CC/CDC HHSUnited States/ ; K01 AI182506/AI/NIAID NIH HHSUnited States/ ; R21MH134750/NH/NIH HHSUnited States/ ; U2GGH002173/CC/CDC HHSUnited States/
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Pages in Document:173-182 (18 pdf pages)
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Volume:101
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Issue:2
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Main Document Checksum:urn:sha-512:9fa580268d19d8cf4cfbf2c10dc3f2f57d7f297bf0097f5dc42e4f2d4f7b711b5bec512834c2f38e46b480a3d2507fc206fc36663c5524218e3aae9371fc2819
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