Developing a regionally representative risk assessment tool to identify men at highest risk of HIV acquisition in sub-Saharan Africa

开发具有区域代表性的风险评估工具，以确定撒哈拉以南非洲地区感染艾滋病毒风险最高的男性

• 批准号: 10762645
• 负责人: Nora Rosenberg
• 金额: $ 41.68万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10762645
• 关键词: AIDS prevention; Accounting; Acquired Immunodeficiency Syndrome; Address; Adopted; Adult; Africa South of the Sahara; African; Anti-Retroviral Agents; Antigens; Area; Assessment tool; Avidity; Behavior; Biological Markers; Botswana; Caring; Central Africa; Communities; Complex; Country; Data; Data Set; Data Sources; Eligibility Determination; Enzyme Immunoassay; Epidemic; Epidemiology; Federal Government; Geography; Goals; Government; HIV; HIV-1; HIV/AIDS; Health; Household; Incidence; Individual; Infection; Injectable; Machine Learning; Measures; Methods; Modeling; Nigeria; Oral; Outcome; Performance; Population; Positioning Attribute; Predisposition; Prevalence; Prevention; Prevention strategy; Principal Investigator; ROC Curve; Research; Research Personnel; Risk; Risk Assessment; Sensitivity and Specificity; Series; South African; Specialist; Survey Methodology; Surveys; Techniques; Tenofovir; Time; Validation; Viral; Viral Load result; Woman; Work; Zambia; aged; analytical method; drug testing; experience; high risk; high risk men; machine learning method; male; men; mortality; population based; pre-exposure prophylaxis; predictive modeling; public health priorities; random forest; response; risk stratification; stem; tool; transmission process

PROJECT SUMMARY/ABSTRACT Background: In sub-Saharan Africa (SSA), HIV prevention has lagged behind UNAIDS targets. Approximately 730,000 adults are infected each year, with men accounting for more than one third of these new infections. Biomedical HIV prevention strategies, such as oral and injectable pre-exposure prophylaxis (PrEP), are promising measures for reducing HIV acquisition. However, providing PrEP to all men is infeasible and unnecessary. Risk stratification approaches are needed to identify men at highest risk of HIV acquisition and in greatest need of PrEP. Although multiple risk assessment tools have been developed for women, few tools have been developed for men. Those that have been developed have important limitations with respect to internal and external validity. The goal of this proposal is to develop a risk assessment tool for identifying men at highest risk for HIV acquisition using rigorous analytic methods in a regionally representative dataset. Methods and Specific Aims: In Aim 1, we will use nationally representative data from 15 SSA countries collected from 2015-2019 as part of the Population-based HIV Impact Assessments (PHIAs), the Nigeria AIDS Indicator and Impact Surveys (NAIIS), and the South African National HIV Prevalence, Incidence and Behaviour Survey (SABSSM). These 15 surveys represent 249,000 new annual male infections in a population of 122 million susceptible men. These surveys all have a set of biomarkers (limiting-antigen avidity enzyme immunoassay, HIV-1 viral load, and antiretroviral drug detection) indicative of recent HIV-1 infection. We will apply two machine-learning methods to develop risk assessment tools to identify men aged 15-49 at greatest risk of HIV-1. We will calculate the area under the receiver operating characteristic curve (AUC), as well as sensitivity and specificity at select thresholds. In Aim 2, we will externally validate the tools in ten second-round national surveys conducted in SSA from 2020-2022 and select a final tool. Using the final tool, we will estimate the AUC and the sensitivity and specificity at meaningful thresholds. At each threshold, we will calculate the number of men at increased risk of HIV-1 infection, the number needed to treat with PrEP to avert one new infection, and the estimated number of infections averted. Team: This is a proposal led by multiple Principal Investigators (mPIs)—one with epidemiologic expertise in HIV prevention in SSA and the other with extensive statistical experience using complex survey data. The team includes co-investigators with expertise in machine learning and biomedical HIV prevention. They are supported by a technical advisory panel of regional HIV prevention specialists; the principal investigators of the PHIA, NAIIS, and SABSSM surveys; and an expert biostatistician in the field of HIV research. Impact: We will use rigorous methods to develop a regional tool to identify men at highest risk of HIV acquisition. This research is crucial for a targeted HIV response and ultimately ending the HIV epidemic in SSA.

项目总结/摘要 背景：在撒哈拉以南非洲，艾滋病毒预防工作落后于艾滋病规划署的目标。约 每年有730 000名成年人受到感染，其中男子占新感染人数的三分之一以上。 生物医学艾滋病毒预防策略，如口服和注射暴露前预防（PrEP）， 减少艾滋病毒感染的有效措施。然而，向所有男性提供PrEP是不可行的， 没必要需要采用风险分层方法来确定感染艾滋病毒风险最高的男性， 尽管已经为妇女开发了多种风险评估工具，但很少有工具 是为男性开发的。已经制定的标准在内部和外部环境方面有重要的局限性， 外部效度该提案的目标是开发一种风险评估工具，以确定处于最高风险的男性 在区域代表性数据集中使用严格的分析方法进行艾滋病毒采集。 方法和具体目标：在目标1中，我们将使用来自15个撒哈拉以南非洲国家的全国代表性数据 作为基于人口的艾滋病毒影响评估（PHIAs）的一部分，从2015-2019年收集的尼日利亚艾滋病 指标和影响调查以及南非全国艾滋病毒流行率、发病率和行为调查 调查（SABSSM）。这15项调查表明，在122名男性中，每年有249 000名男性新感染。 百万易感人群这些调查都有一套生物标志物（限制性抗原亲合力酶 免疫测定、HIV-1病毒载量和抗逆转录病毒药物检测），指示近期HIV-1感染。我们将 应用两种机器学习方法来开发风险评估工具，以识别年龄在15-49岁之间的男性， HIV-1的风险。我们将计算受试者工作特征曲线下面积（AUC），以及 选择阈值的灵敏度和特异性。在目标2中，我们将在10个第二轮中对工具进行外部验证 2020-2022年在撒哈拉以南非洲进行国家调查，并选择最终工具。使用最终工具，我们将估计 AUC以及有意义阈值的灵敏度和特异性。在每个阈值处，我们将计算 HIV-1感染风险增加的男性人数，需要用PrEP治疗以避免一个新的 感染，以及避免感染的估计数量。 团队：这是一项由多名主要研究者（mPI）领导的提案-其中一名具有HIV流行病学专业知识 另一个是在使用复杂调查数据方面具有广泛统计经验的专家。球队 包括在机器学习和生物医学艾滋病毒预防方面具有专业知识的共同研究者。即可支持这些平衡 由区域艾滋病毒预防专家组成的技术咨询小组; PHIA的主要调查人员， NAIIS和SABSSM调查;以及艾滋病毒研究领域的专家生物统计学家。 影响：我们将采用严格的方法开发一种区域工具，以确定感染艾滋病毒风险最高的男性。 这项研究对于有针对性的艾滋病毒应对和最终结束撒哈拉以南非洲的艾滋病毒流行至关重要。