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

基本信息

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
项目类别：
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

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

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项目摘要

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会增加与男性发生性关系（MSM）和已经开发了许多干预措施，以减少物质中的艾滋病毒收购和传播使用MSM。然而，尽管有大量的研究记录了这些关联，但很大关于大多数物质使用和HIV之间的特定行为途径的不确定性仍然存在负责这种升高的风险（例如，使用避孕套，性伴侣选择或HIV药物依从性）。没有这些知识，很难确定MSM或估计使用MSM在物质中干预措施的人口水平的影响。另外，使用物质，依从性，降低风险和综合干预措施都表现出极好的希望减少艾滋病毒发病率，但是大规模的比较有效性试验极具挑战性和昂贵，可以很少全面检查这些干预措施对特定子组的独特价值（例如，种族/种族或年龄）。因此，该项目寻求1）综合酒精之间关系的数据， MSM中甲基苯丙胺和HIV，包括使用物质对HIV风险行为的影响和预防措施连续体，2）估计可归因于HIV感染的合理范围和来源 MSM中使用的酒精和甲基苯丙胺使用原则上且广泛使用的网络方法流行模型（即EpiModel），3）确定降低HIV发病率的最佳和健壮策略在使用MSM的物质中。对于这项工作的各个方面，我们将利用高级统计和严格校准我们的模型，验证它们与独立数据源验证的计算工具，并进行广泛的灵敏度分析。增加这些模型对现实决定的实用性制作，我们将利用不确定性量化来确保已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的潜在不准确之后。所有模型开发将可以使用开源软件来实现其他复制，修改和扩展研究人员。该项目的团队在实现这些目标方面的专业知识非常有效网络分析，药物使用流行病学，流行性建模和高性能计算。最后，旨在直接告知主要利益相关者的活动，以减少艾滋病毒的发病率和最大化该项目对艾滋病毒消除工作的影响。