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.

中文翻译：

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针对非洲国家 15-49 岁女性的 HIV-1 风险评估工具：15 项全国代表性调查的汇总分析

背景 非洲妇女感染 HIV-1 的比例过高。了解哪些女性最有可能感染 HIV-1 可以指导通过暴露前预防 (PrEP) 进行有针对性的预防。我们的目标是识别感染 HIV-1 风险最高的女性，并估计不同敏感性水平下的 PrEP 效率。方法 从 2015 年至 2019 年 15 项基于人口的住户调查中收集了具有全国代表性的数据。这项分析包括 15-49 岁、HIV-1 血清检测呈阴性或近期感染 HIV-1 的女性。最小绝对收缩和选择算子回归模型适合 28 个变量来预测近期的 HIV-1。模型针对全体人群进行了训练并进行了内部交叉验证。使用接受者操作特征曲线下面积 (AUC)、敏感性和为避免一种感染而需要使用 PrEP 治疗 (NNT) 的数量来评估性能。结果 在 209,012 名参与者中，有 248 人近期感染过 HIV-1，代表 1.18 亿女性，每年新增感染人数为 402,000 人（95% CI：309,000-495,000）。模型中保留了两个变量：生活在 HIV-1 病毒血症高发的次国家地区，以及性伴侣住在外面。全群体 AUC 为 0.80（95% CI：0.76-0.84）；交叉验证的 AUC 为 0.79（95% CI：0.75-0.84）。如果敏感性为 33%，如果 790 万名女性完全遵守 PrEP，则可避免多达 130,000 例病例； NNT 为 61。如果敏感性为 67%，如果 2510 万名女性完全遵守 PrEP，则可避免多达 260,000 例病例； NNT 将为 96。 结论 该风险评估工具具有通用性、预测性，并且在覆盖范围和效率之间进行权衡。