Rapid Tests for Recent Infection (RTRI) for Precision Public Health in Sub-Saharan Africa: Next-Generation Strategies Amid Changing HIV Epidemiology

撒哈拉以南非洲地区近期感染快速检测 (RTRI) 实现精准公共卫生：艾滋病毒流行病学变化中的下一代策略

• 批准号: 10620014
• 负责人: Anna Bershteyn
• 金额: $ 80.93万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-11-04 至 2027-10-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10620014
• 关键词: AIDS prevention; Acceleration; Adopted; Adult; Africa South of the Sahara; Age; Antibody Avidity; Authorization documentation; Avidity; Big Data; Big Data Methods; Bioethics; Botswana; Budgets; Cause of Death; Client; Cost Measures; Country; Data; Data Element; Decision Making; Detection; Diagnosis; Disease Outbreaks; Epidemic; Epidemiology; Exposure to; Fingers; Goals; Guidelines; HIV; HIV Antibodies; HIV Genome; HIV Infections; HIV Seropositivity; Health; Health Benefit; Health Care Costs; Health care facility; Home; Human immunodeficiency virus test; Incidence; Individual; Infection; Infectious Diseases Research; International; Intervention; Intuition; Investments; Lead; Lesotho; Life; Machine Learning; Maps; Measures; Modeling; Mozambique; Namibia; Network-based; Newly Diagnosed; Paper; Pattern; Persons; Phylogenetic Analysis; Plasma; Policies; Policy Making; Population; Populations at Risk; Prevalence; Public Health; Radial; Reaction Time; Resources; Role; Running; Sensitivity and Specificity; Sepsis; Serum; Services; Social Network; South Africa; Specificity; Stigmatization; Sustainable Development; Testing; Time; Training; Venous; Work; Zambia; antibody detection; authority; cohort; cost; cost effectiveness; cost estimate; design; epidemic response; health economics; heuristics; improved; incremental cost; infectious disease model; machine learning model; mathematical model; microcosting; network models; next generation; novel; outbreak response; point of care; point of care testing; prevention service; programs; rapid test; response; standard of care; test strip; testing services; tool; transmission process

ABSTRACT/SUMMARY HIV is a leading cause of death in sub-Saharan Africa (SSA), but rates of new infections in declining. As a result, some HIV services are becoming less efficient: HIV prevention is averting fewer infections per client served, and HIV testing yield (i.e., the fraction of tests leading to new diagnoses) is declining. Given resource constraints, HIV prevention and testing programs will need to increase efficiency in order to maintain momentum toward epidemic control. Specifically, a precision public health approach could be used to focus services where their health benefits would be greatest. Precision public health has been challenging to implement in SSA’s generalized HIV epidemics because most transmission is not confined to identifiable key populations, eluding precise responses. Until recently, the only tool for describing HIV transmission has been phylogenetic analysis of HIV genome sequences, which is too slow and costly for real-time response at scale. Rapid tests for recent HIV infection (RTRI) recently became available in SSA, offering a novel opportunity to identify active transmission clusters and respond with precision. RTRI detects high-avidity antibodies that appear approximately one year after HIV infection. If only low-avidity antibodies are detected, this infection likely occurred in the past year. Zambia is an early adopter of RTRI and followed-up two-thirds of positive HIV tests with RTRI in 2021. Despite the large scale of Zambia’s RTRI program, it has not been evaluated in terms of impact or cost-effectiveness, and outbreak response thresholds have not been optimized. However, the wealth of data now collected by the RTRI program could guide higher-performing, next-generation outbreak response strategies. Our team has expertise in Zambian HIV policy, program implementation, health economics, bioethics, geospatial analysis, machine learning, and infectious disease modeling. We helped to develop the only HIV social network model rigorously validated to predict HIV incidence, prevalence, and transmission patterns in SSA, which has been used for international and country-level HIV policy decision-making for over a decade. We propose to partner with the Center for Infectious Disease Research in Zambia (CIDRZ), a Zambian-run NGO that has been supporting MoH for over a decade in HIV policy-making and implementation (including RTRI), to (Aim 1) determine whether the RTRI program can help Zambia achieve its epidemic control goals, (Aim 2) measure the cost and estimate the cost-effectiveness of the RTRI program, and (Aim 3) use “big data” methods to design next-generation outbreak responses, taking into account trade-offs of sensitivity vs. specificity, precision vs. ease-of-use, and precision vs. avoidance of collecting potentially stigmatizing data elements. While pursuing scientific Aims and hypotheses aligned with the NOSI “Harnessing Big Data to Halt HIV”, we will also have direct policy impact by providing real-time analytics, HIV outbreak mapping, and input for RTRI policy decision-making.

摘要/摘要 艾滋病毒是撒哈拉以南非洲(SSA)的主要死亡原因，但非洲的新感染率正在下降。结果, 一些艾滋病毒服务正在变得不那么有效：艾滋病毒预防正在避免每个服务对象更少的感染，以及 艾滋病毒检测收益率(即导致新诊断的检测比例)正在下降。在资源受限的情况下， 艾滋病毒预防和检测方案将需要提高效率，以保持实现以下目标的势头 疫情控制。具体地说，可以使用精确的公共卫生方法将服务集中在他们的 健康福利将是最大的。精准公共卫生在SSA的实施中一直具有挑战性 普遍的艾滋病毒流行，因为大多数传播并不局限于可识别的关键人群， 精确的回应。直到最近，描述艾滋病毒传播的唯一工具一直是系统发育分析 对于大规模的实时反应来说，这太慢了，而且成本太高。最近的快速测试 艾滋病毒感染(RTRI)最近在SSA中可用，为识别活跃的传播提供了新的机会 并以精确的方式响应。RTRI检测出现约一年的高亲和力抗体 在感染艾滋病毒之后。如果只检测到低亲和力抗体，这种感染很可能发生在过去一年。 赞比亚是RTRI的早期采用者，并在2021年跟踪了RTRI三分之二的艾滋病毒阳性检测。尽管 赞比亚RTRI方案的规模之大，尚未从影响或成本效益的角度进行评估， 疫情应对阈值还没有得到优化。然而，美国政府现在收集的大量数据 RTRI计划可以指导更高性能的下一代疫情应对策略。我们队有 在赞比亚艾滋病毒政策、方案执行、卫生经济学、生物伦理学、地理空间分析、 机器学习和传染病建模。我们帮助开发了唯一的艾滋病毒社交网络模型 经过严格验证，可以预测SSA中艾滋病毒的发病率、流行率和传播模式，这已经被 十多年来用于国际和国家一级的艾滋病毒政策决策。我们建议与合作伙伴 与赞比亚传染病研究中心(CIDRZ)合作，该中心是赞比亚运营的非政府组织，一直在 十多年来在艾滋病毒政策制定和执行方面支持卫生部(包括RTRI)，以(目标1) 确定RTRI方案是否能够帮助赞比亚实现其疫情控制目标，(目标2)衡量 成本和估算RTRI方案的成本效益，以及(目标3)使用“大数据”方法设计 下一代疫情响应，考虑了敏感性与特异性、精确度与 易用性、精确度和避免收集可能使人蒙羞的数据元素。在追求的同时 科学目标和假说与NOSI“利用大数据遏制艾滋病毒”保持一致，我们也将有直接的 通过为RTRI政策决策提供实时分析、艾滋病毒爆发地图和输入，实现政策影响。