Leveraging data synthesis to identify optimal and robust strategies for HIV elimination among substance-using MSM

利用数据合成来确定消除使用药物的 MSM 中的 HIV 的最佳且稳健的策略

• 批准号: 10612874
• 负责人: Patrick Francis Janulis
• 金额: $ 65.55万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10612874
• 关键词: AIDS prevention; Accounting; Acquired Immunodeficiency Syndrome; Address; Adherence; Age; Alcohol consumption; Alcohols; Behavior; Behavioral; Calibration; Characteristics; Cohort Studies; Collaborations; Complex; Computer software; Continuity of Patient Care; Data; Data Set; Data Sources; Decision Making; Dependence; Drug usage; Ensure; Epidemic; Epidemiology; Ethnic Origin; Funding; Goals; HIV; HIV Infections; HIV risk; Health; High Performance Computing; Incidence; Individual; Intervention; Knowledge; Length; Methamphetamine; Modeling; Modification; National Institute of Drug Abuse; Network-based; Observational Study; Pathway Analysis; Pathway interactions; Persons; Population; Population Dynamics; Populations at Risk; Positioning Attribute; Prevention; Race; Reporting; Research; Research Personnel; Research Priority; Resources; Risk; Risk Behaviors; Risk Factors; Risk Reduction; Services; Sex Behavior; Sexual Partners; Source; Structure; Subgroup; Surveys; Uncertainty; United States; United States National Institutes of Health; Work; alcohol effect; comparative effectiveness trial; computerized tools; condoms; cost; data integration; design; experience; experimental study; flexibility; high risk population; improved; insight; laboratory experiment; medication compliance; men who have sex with men; methamphetamine use; model development; novel; open source; prevent; protective factors; reduced substance use; sexual risk behavior; simulation; substance use; success; transmission process

Project Summary Alcohol and methamphetamine use increases risk of HIV among men who have sex with men (MSM) and numerous interventions have been developed to decrease HIV acquisition and transmission among substance using MSM. Yet, despite a considerable body of research documenting these associations, substantial uncertainty remains regarding the specific behavioral pathways between substance use and HIV that are most responsible for this elevated risk (e.g., condom use, sexual partner selection, or HIV medication adherence). Without this knowledge, it is difficult to identify the extent to which substance use drives HIV among MSM or estimate the population level impact of interventions among substance using MSM. In addition, substance use, adherence, risk reduction, and combined interventions have all shown excellent promise to reduce HIV incidence, but large-scale comparative effectiveness trials are extremely challenging and costly and can seldom comprehensively examine the unique value of these interventions to specific subgroups (e.g., by race/ethnicity or age). Accordingly, this project seeks to 1) synthesize data on the relationship between alcohol, methamphetamine, and HIV among MSM, including the impact of substance use on HIV risk behavior and the prevention-care continuum, 2) estimate the plausible range and sources of HIV infections attributable to alcohol and methamphetamine use among MSM using a principled and widely-used approach to network epidemic models (i.e., EpiModel), and 3) determine optimal and robust strategies for reducing HIV incidence among substance using MSM. For each aspect of this work, we will leverage advanced statistical and computational tools to rigorously calibrate our models, validate them against independent data sources, and perform extensive sensitivity analysis. To increase the usefulness of these models for real-world decision making, we will utilize uncertainty quantification to ensure the identified strategies are most likely to succeed after accounting for potential inaccuracy in our model parameters and assumptions. All model development will be conducted using open-source software enabling easy replication, modification, and extensions by other researchers. The project's team is exceptionally well positioned to achieve these goals with expertise spanning network analysis, drug use epidemiology, epidemic modeling, and high-performance computing. Finally, dissemination activities are designed to directly inform key stakeholders in order to reduce HIV incidence and maximize the impact of this project on HIV elimination efforts.

项目摘要 酒精和甲基苯丙胺的使用增加了男男性行为者（MSM）感染艾滋病毒的风险， 已经制定了许多干预措施，以减少艾滋病毒的获得和传播， 使用MSM。然而，尽管有相当多的研究记录了这些关联， 关于物质使用和艾滋病毒之间的具体行为途径， 造成这种高风险的原因（例如，避孕套的使用、性伴侣的选择或艾滋病毒药物治疗的依从性）。 如果没有这些知识，就很难确定物质使用在多大程度上推动了男男性行为者或 估计干预措施对使用药物的MSM人群的影响。此外，物质使用， 坚持治疗、降低风险和综合干预措施都显示出减少艾滋病毒感染的良好前景 发病率，但大规模的比较有效性试验极具挑战性和成本， 很少全面审查这些干预措施对特定亚组的独特价值（例如，通过 种族/民族或年龄）。因此，本项目寻求1）综合关于酒精， 甲基苯丙胺和艾滋病毒在男男性接触者，包括物质使用对艾滋病毒风险行为的影响， 预防-护理连续体，2）估计可归因于以下原因的艾滋病毒感染的可能范围和来源： 酒精和甲基苯丙胺使用的男男性行为者使用原则和广泛使用的方法，以网络 流行病模型（即，EpiModel），以及3）确定降低HIV发病率的最佳和稳健的策略 在使用MSM的物质中。对于这项工作的每个方面，我们将利用先进的统计和 计算工具来严格校准我们的模型，根据独立的数据源验证它们， 进行广泛的敏感性分析。为了提高这些模型对现实世界决策的有用性， 我们将利用不确定性量化来确保所确定的策略最有可能成功 在考虑了模型参数和假设的潜在不准确性之后。所有模型开发将 使用开源软件进行，使其他人能够轻松复制，修改和扩展 研究人员该项目的团队是非常好的定位，以实现这些目标的专业知识跨越 网络分析、药物使用流行病学、流行病建模和高性能计算。最后， 传播活动旨在直接向主要利益攸关方提供信息，以降低艾滋病毒发病率， 最大限度地发挥该项目对消除艾滋病毒工作的影响。