Department of Health Behavior, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Clin Infect Dis. 2024 Nov 22;79(5):1223-1232. doi: 10.1093/cid/ciae211.
Women in Africa disproportionately acquire human immunodeficiency virus type 1 (HIV-1). Understanding which women are most likely to acquire HIV-1 can guide focused prevention with preexposure prophylaxis (PrEP). Our objective was to identify women at the highest risk of HIV-1 and estimate PrEP efficiency at different sensitivity levels.
Nationally representative data were collected from 2015 through 2019 from 15 population-based household surveys. This analysis included women aged 15-49 who tested HIV-1 seronegative 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 1 infection.
Among 209 012 participants, 248 had recent HIV-1 infection, representing 118 million women and 402 000 (95% confidence interval [CI], 309 000-495 000) annual infections. Two variables were retained: living in a subnational area with high HIV-1 viremia and having a sexual partner living outside the home. The full-population AUC was 0.80 (95% CI, .76-.84); cross-validated AUC was 0.79 (95% CI, .75-.84). At 33% sensitivity, 130 000 cases could be averted if 7.9 million women were perfectly adherent to PrEP; NNT would be 61. At 67% sensitivity, 260 000 cases could be averted if 25.1 million women were perfectly adherent; NNT would be 96.
This risk assessment tool was generalizable, predictive, and parsimonious with trade-offs between reach and efficiency.
非洲的女性不成比例地感染了人类免疫缺陷病毒 1 型（HIV-1）。了解哪些女性最有可能感染 HIV-1，可以指导使用暴露前预防（PrEP）进行有针对性的预防。我们的目标是确定 HIV-1 感染风险最高的女性，并估计不同敏感性水平下 PrEP 的效率。
2015 年至 2019 年，我们从 15 项基于人群的家庭调查中收集了全国代表性数据。该分析包括年龄在 15-49 岁之间的 HIV-1 血清阴性或最近 HIV-1 检测呈阳性的女性。使用最小绝对收缩和选择算子回归模型，对 28 个变量进行拟合，以预测最近的 HIV-1。模型在全人群中进行训练，并进行内部交叉验证。使用接收器操作特征曲线（ROC）下的面积（AUC）、敏感性和用 PrEP 预防 1 次感染所需的治疗人数（NNT）来评估性能。
在 209012 名参与者中，有 248 人最近感染了 HIV-1，代表了 1.18 亿名女性和 402000 例（95%置信区间[CI]，309000-495000）年感染。保留了两个变量：居住在 HIV-1 病毒载量高的国家以下地区和有一个居住在家庭以外的性伴侣。全人群 AUC 为 0.80（95%CI，0.76-0.84）；交叉验证 AUC 为 0.79（95%CI，0.75-0.84）。在敏感性为 33%时，如果 790 万名妇女完全遵守 PrEP 规定，可预防 13 万例病例；NNT 将为 61。在敏感性为 67%时，如果 2510 万名妇女完全遵守 PrEP 规定，可预防 26 万例病例；NNT 将为 96。
该风险评估工具具有可推广性、预测性和简约性，在可及性和效率之间存在权衡。
