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: 10328515
• 负责人: Daniel Escudero
• 金额: $ 5.57万
• 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 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10328515
• 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.

项目总结/摘要 基于主体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 在众多不同的人群中取得的成果。拟议的研究将建立在一个行之有效的模型上 艾滋病毒校准动态模型（HIV-CDM）平台，以构建迈阿密的艾滋病毒流行模型， 这是该国艾滋病毒新感染率最高的地区之一。 为了应对迈阿密日益严重的艾滋病疫情，当地的政策制定者、临床医生和研究人员组成了 一个旨在消除迈阿密大都市地区所有新的艾滋病毒感染的“归零”工作组。 该运动是建立在综合预防的原则基础上的， 基于证据的预防策略，如治疗即预防、暴露前预防（PrEP），以及 频繁/有针对性的艾滋病毒检测。目前尚不清楚这一运动将对艾滋病毒事件产生什么影响 迈阿密的感染该提案旨在使用基于代理的建模来估计 在2017年通过的“零排放”运动中概述的联合预防计划。沿着 估计特定的流行病结果（例如，艾滋病毒发病率、艾滋病毒流行率、消除流行病的时间）， 这种方法还可以评估每个组成部分对计划成功的相对贡献。等 估计数对于最大限度地实现运动的目标至关重要，并有助于执行 类似的艾滋病毒消除计划。 本建议将：（1）扩展HIV-CDM模型，模拟人口统计学特征和艾滋病危险行为， 多样化的大都市迈阿密人口;（2）估计“归零”的成功和局限性 使用HIV-CDM模型的运动;和（3）在 迈阿密人口，以更好地了解目前的研究差距，以及那些确定的前两个目标。每个 研究计划的组成部分将得到支持，并与具体的培训组成部分保持一致， 为候选人提供必要的专业发展和指导，以执行研究 目标，并开始开始独立的研究生涯。 从这项工作中获得的结果可能会直接影响对迈阿密“零排放”运动的评估 并为美国和全球未来的艾滋病消除运动提供信息。此外，培训计划将 提供卓越的方法和实践经验，导致独立和有影响力的科学 事业支持这项工作的将是一个消除艾滋病毒学术和社区领导人辅导小组， 流行病学和建模方法。这种指导将建立在方法和实质性的基础上， 我在领导流行病建模和艾滋病流行病学的众多研究时所展示的经验。