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吸毒 MSM 中艾滋病毒的最佳和稳健策略

• 批准号: 10402179
• 负责人: Patrick Francis Janulis
• 金额: $ 73.19万
• 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/10402179
• 关键词: AIDS prevention; Accounting; Acquired Immunodeficiency Syndrome; Address; Adherence; Alcohol consumption; Alcohols; Behavior; Behavioral; 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; Laboratories; Length; Methamphetamine; Modeling; Modification; National Institute of Drug Abuse; Network-based; Observational Study; Pathway Analysis; Pathway interactions; Persons; Population; Population Dynamics; 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; design; experience; experimental study; flexibility; high risk population; improved; insight; medication compliance; men who have sex with men; methamphetamine use; model development; novel; open source; prevent; protective factors; reduced substance use; sexual risk behavior; 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.

项目概要 酒精和甲基​​苯丙胺的使用会增加男男性接触者 (MSM) 和男性发生艾滋病毒的风险 已经制定了许多干预措施来减少艾滋病毒在物质之间的感染和传播 使用MSM。然而，尽管有大量研究记录了这些关联，但大量研究 关于物质使用和艾滋病毒之间的具体行为途径仍然存在不确定性 导致这种风险升高的因素（例如，使用安全套、选择性伴侣或坚持服用艾滋病毒药物）。 如果没有这方面的知识，就很难确定物质使用在 MSM 或 MSM 中导致艾滋病毒的程度 估计使用 MSM 物质的干预措施对人口水平的影响。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的良好前景 发生率，但大规模的比较有效性试验极具挑战性且成本高昂，并且可以 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，该项目旨在 1) 综合酒精之间关系的数据， 甲基苯丙胺和 MSM 中的艾滋病毒，包括物质使用对艾滋病毒危险行为的影响以及 预防护理连续体，2) 估计可归因于的 HIV 感染的合理范围和来源 使用有原则且广泛使用的网络方法来控制 MSM 中的酒精和甲基​​苯丙胺使用情况 流行病模型（即 EpiModel），以及 3）确定降低艾滋病毒发病率的最佳且稳健的策略 使用 MSM 的物质中。对于这项工作的各个方面，我们将利用先进的统计和 计算工具严格校准我们的模型，根据独立数据源验证它们，以及 进行广泛的敏感性分析。提高这些模型在现实世界决策中的实用性 制定时，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 在考虑了我们的模型参数和假设中潜在的不准确性之后。所有模型开发将 使用开源软件进行，可以轻松地由其他人复制、修改和扩展 研究人员。该项目团队非常有能力凭借跨领域的专业知识实现这些目标 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， 传播活动旨在直接向主要利益攸关方提供信息，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工作的影响。