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.

项目摘要/摘要 基于代理的建模为流行病学家提供了一种高级工具，以估计关键流行病学 大型潜水员人群的结果。拟议的研究将基于一个公认的模型 平台，HIV校准的动态模型（HIV-CDM），以构建迈阿密的HIV流行模型， 这是该国新艾滋病毒感染率最高的经历。 为了应对迈阿密不断增长的艾滋病毒流行，当地决策者，临床医生和研究人员形成了 旨在消除迈阿密大都会地区所有新的艾滋病毒感染的“达到零”工作队。 该运动是建立在预防组合原则的基础上的，该原则同时使用了许多 基于证据的预防策略，例如预防，预防前预防（PREP）和 经常/针对性的HIV测试。目前尚不清楚该运动对事件艾滋病毒的影响 迈阿密的感染。该提案试图使用基于代理的建模来估计 在2017年通过的零竞选活动中概述的预防联合计划。 估计特定的流行预后（例如，HIV事件，HIV患病率，流行病的时间），此 方法还可以评估每个组件对程序成功的相对贡献。这样的 估计对于最大化竞选目标以及协助实施 类似的艾滋病毒消除计划。 该建议将：（1）扩展HIV-CDM模型，以模拟人口统计和HIV风险行为 迈阿密大都市人口多样化； （2）估计到零的成功和局限性 使用HIV-CDM模型的活动； （3）在该亚组中进行主要和次要分析 迈阿密人口更好地了解当前的研究差距，并在前两个目标中确定的差距。每个 研究计划的组成部分将得到支持和对齐，并与旨在 为候选人提供必要的专业发展和心态来执行研究 目的，开始独立的研究职业。 从这项工作中获得的结果可能直接影响迈阿密的评估 并在美国和全球范围内通知所有未来的HIV消除运动。此外，培训计划将 提供卓越的方法论和实践经验，导致独立和有影响力的科学 职业。支持这项工作将是一个由艾滋病毒消除的学术和社区领袖的心态团队， 流行病学和建模方法。这种概念化将以方法论和实质性为基础 我在领导有关流行病建模和HIV流行病学的众多研究时所证明的经验。