Using agent-based modeling to estimate the effectiveness of the Miami Getting to Zero HIV campaign

使用基于主体的建模来评估迈阿密“零艾滋病毒”运动的有效性

• 批准号: 10084801
• 负责人: Daniel Escudero
• 金额: $ 12.63万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-02-22 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10084801
• 关键词: AIDS prevention; Address; Adopted; Advanced Development; Advisory Committees; Area; Behavioral; Calibration; Caring; Clinical; Communities; Contact Tracing; Country; County; Data; Development; Disease; Disease Progression; Effectiveness; Elements; Enrollment; Epidemic; Epidemiologic Methods; Epidemiologist; Epidemiology; Future; Goals; Government; HIV; HIV Infections; HIV diagnosis; HIV risk; Harm Reduction; Home; Human immunodeficiency virus test; Incidence; Individual; Infection; Influentials; Intervention; Leadership; Literature; Massachusetts; Mentorship; Methodology; Methods; Modality; Modeling; Outcome; Population; Population Heterogeneity; Prevalence; Prevention; Prevention Research; Prevention program; Prevention strategy; Race; Research; Research Personnel; Risk; Risk Behaviors; Sex Behavior; Stratification; Structure; Subgroup; Testing; Time; Training; Training Programs; Vertebral column; Work; advocacy organizations; base; burden of illness; career; condoms; demographics; design; epidemiological model; epidemiology study; evidence base; experience; infectious disease model; insight; metropolitan; pre-exposure prophylaxis; programs; response; secondary analysis; sex; skills; success; surveillance data; tool; transmission process; treatment as prevention; uptake; urban setting

Project Summary/Abstract Agent-based modeling has provided epidemiologists with an advanced tool to estimate critical epidemiologic outcomes among large, diverse populations. The proposed research will build on a well-established model platform, the HIV-Calibrated Dynamic Model (HIV-CDM), to construct a model of the HIV epidemic in Miami, which experiences among the highest rates of new HIV infection in the country. In response to the growing HIV epidemic in Miami, local policymakers, clinicians, and researchers have formed a “Getting to Zero” Task Force that seeks to eliminate all new HIV infections in the Miami metropolitan area. The campaign is founded on the principle of combination prevention, which enlists the concurrent use of many evidence-based prevention strategies, such as treatment as prevention, pre-exposure prophylaxis (PrEP), and frequent/targeted HIV testing. Presently it is unknown what effect this campaign will have on incident HIV infections in Miami. This proposal seeks to use agent-based modeling to estimate the long-term impact of the combination prevention program outlined in the Getting to Zero campaign adopted in 2017. Along with estimating specific epidemic outcomes (e.g., HIV incidence, HIV prevalence, time to epidemic elimination), this approach may also assess the relative contribution of each component to the success of the program. Such estimates will be crucial in maximizing the goals of the campaign, as well as assist with the implementation of similar HIV elimination programs. This proposal will: (1) expand the HIV-CDM model, to simulate the demographics and HIV risk behavior of the diverse metropolitan Miami population; (2) estimate the success and limitations of the Getting to Zero campaign using the HIV-CDM model; and (3) perform primary and secondary analyses within subgroups of the Miami population to better understand current research gaps, and those identified in the first two aims. Each component of the research plan will be supported and aligned with specific training components designed to provide the candidate with the necessary professional development and mentorship to execute the research aims, and begin an independent research career. The results obtained from this work may directly impact the assessment of the Miami Getting to Zero campaign and inform all future HIV elimination campaigns in the U.S. and globally. Additionally, the training program will provide exceptional methodological and practical experience leading to an independent and influential scientific career. Supporting this work will be a mentorship team of academic and community leaders in HIV elimination, epidemiology and modeling methodology. This mentorship will build on the methodological and substantive experience I have demonstrated while leading numerous studies on epidemic modeling and HIV epidemiology.

项目概要/摘要 基于代理的建模为流行病学家提供了一种先进的工具来估计关键的流行病学 拟议的研究将建立在一个完善的模型之上。 平台，艾滋病毒校准动态模型（HIV-CDM），构建迈阿密艾滋病毒流行模型， 是该国新发艾滋病毒感染率最高的国家之一。 为了应对迈阿密日益严重的艾滋病毒流行，当地政策制定者、支持者和研究人员组成了 一个“实现零”工作组，致力于消除迈阿密大都市区所有新的艾滋病毒感染。 该活动以联合预防为原则，同时使用多种预防措施。 基于证据的预防策略，例如治疗即预防、暴露前预防 (PrEP) 和 目前尚不清楚该活动将对艾滋病毒事件产生什么影响。 该提案旨在使用基于主体的模型来估计该病毒的长期影响。 2017 年通过的“实现零排放”运动中概述的综合预防计划。 估计具体的流行病结果（例如，艾滋病毒发病率、艾滋病毒流行率、消除流行病的时间），这 方法还可以评估每个组成部分对计划成功的相对贡献。 估计对于最大限度地实现该运动的目标以及协助实施 消除类似的艾滋病毒计划。 该提案将：（1）扩展 HIV-CDM 模型，模拟人群的人口统计和 HIV 风险行为 不同的迈阿密大都市人口；(2) 评估“归零”计划的成功和局限性 使用 HIV-CDM 模型开展活动；(3) 在亚组内进行初步和次要分析 迈阿密人口更好地了解当前的研究差距以及前两个目标中确定的差距。 研究计划的组成部分将得到支持，并与旨在 为候选人提供必要的专业发展和指导来执行研究 目标，并开始独立的研究生涯。 这项工作获得的结果可能会直接影响迈阿密“零排放”活动的评估 并为美国和全球未来所有艾滋病毒消除运动提供信息。此外，该培训计划还将。 提供卓越的方法论和实践经验，从而形成独立且有影响力的科学 支持这项工作的将是一个由消除艾滋病毒的学术和社区领袖组成的指导团队， 这种指导将建立在方法论和实质性基础上。 我在领导流行病模型和艾滋病毒流行病学的大量研究时展示了我的经验。