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)和 已经开发了许多干预措施来减少艾滋病毒的获得和在物质之间的传播 使用MSM。然而，尽管有大量研究记录了这些联系，但大量的 关于物质使用和艾滋病毒之间的具体行为途径，大多数情况下仍然存在不确定性 对这种高风险负有责任(例如，避孕套的使用、性伴侣的选择或艾滋病毒药物的坚持)。 如果没有这方面的知识，很难确定物质使用在多大程度上导致男男性接触者或 估计干预措施对使用男男性接触者的人群水平的影响。此外，物质使用， 坚持、降低风险和联合干预都显示出减少艾滋病毒的极佳前景。 发病率，但大规模的比较有效性试验具有极大的挑战性和成本，而且可以 很少全面检查这些干预措施对特定亚群的独特价值(例如，通过 种族/民族或年龄)。因此，这个项目试图1)综合关于酒精和酒精之间关系的数据， 男男性接触者中的甲基苯丙胺和艾滋病毒，包括药物使用对艾滋病毒危险行为的影响 预防-护理连续体，2)估计艾滋病毒感染的可能范围和来源 利用原则和广泛使用的网络方法在男男性行为者中使用酒精和甲基苯丙胺 流行病模型(即EpiModel)，以及3)确定减少艾滋病毒发病率的最佳和可靠的策略 在使用MSM的物质中。对于这项工作的每一个方面，我们都将利用先进的统计和 计算工具，用于严格校准我们的模型，根据独立的数据源验证它们，以及 执行广泛的敏感性分析。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确定的战略最有可能成功 在考虑到我们的模型参数和假设中可能存在的不准确之后。所有模型开发都将 使用开放源码软件进行，可轻松复制、修改和扩展其他 研究人员。该项目的团队处于非常有利的地位，可以利用跨领域的专业知识来实现这些目标 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， 传播活动旨在直接告知主要利益攸关方，以减少艾滋病毒发病率和 最大限度地发挥该项目对消除艾滋病毒努力的影响。