Computational approaches to understand the impact of social determinants of health on HIV care continuums

项目摘要/摘要 背景：与男性发生性关系的黑人男性(MSM)受艾滋病毒和其他疾病的影响不成比例 造成艾滋病毒预防和护理连续体不平等的社会结构性因素。证据 表明住房不稳定、刑事司法介入和失业等因素可能会构成 黑人男男性接触者参与艾滋病毒预防和护理的重大障碍。然而，到目前为止，现有的 对于黑人MSM来说，干预措施在解决这些障碍方面一直无效。因为这样的干预 是资源密集型和后勤挑战，特别是对于弱势社区来说，他们往往 流动性强，不太可能在传统环境中从事研究，干预时需要指导 发展阶段，以确定最有效和最有效的干预策略。基于代理的模型 (ABMS)提供虚拟评估候选干预措施的机会，以促进更高效和及时 干预性发展。因为它们允许进行反事实实验，所以ABM也可以 促进识别使用传统方法难以隔离的影响，并提供 指导实施艾滋病毒预防干预措施的有价值的见解。目标：在现有基础上构建 建模平台，该提案将利用现有的多个数据源来表征 社会结构性应激源、心理社会介体和艾滋病毒预防和护理连续结果 并结合实施科学和基于代理的建模方法来理解 减少艾滋病毒传播的结构性干预措施的潜在影响。方法：我们将利用当地的 经验数据，以在现有的基于代理的模型中创建真实的合成种群并应用 统计和计算方法，以更好地了解社会结构因素如何影响 艾滋病毒预防和护理连续体。然后，我们将进行一系列实验，以评估社会- 结构性因素影响现有生物医学干预措施的采用，并比较 具有不同干预组合意义的情景：更好地理解在哪里以及如何进行干预 集中干预努力提供了通过解决以下问题来改善护理连续体结果的潜力 黑人男男性接触者参与艾滋病毒预防和护理的社会结构性障碍。一旦开发出来，我们的 方法可适用于其他地理区域，以反映当地卫生部门的预防优先事项 并可作为在实施科学中应用ABM方法来推进HIV的范例 预防科学。

PROJECT SUMMARY/ABSTRACT Background: Black men who have sex with men (MSM) are disproportionately affected by HIV and other socio-structural factors that contribute to inequities along the HIV prevention and care continuum. Evidence suggests that factors such as housing instability, criminal justice involvement, and unemployment may pose significant barriers to engagement in HIV prevention and care for Black MSM. To date however, existing interventions have been ineffective at addressing these barriers for Black MSM. Because such interventions are resource intensive and logistically challenging, particularly for vulnerable communities who are often highly mobile and less likely to engage in research in traditional settings, guidance is needed at the intervention development stage to determine the most impactful and efficient intervention strategies. Agent-based models (ABMs) provide an opportunity to virtually evaluate candidate interventions to facilitate more efficient and timely intervention development. Because they allow for the conduct of counterfactual experiments, ABMs can also facilitate identification of effects that would be difficult to isolate using traditional approaches and provide valuable insights to guide implementation of HIV prevention interventions. Objective: Building on an existing modeling platform, this proposal will utilize multiple existing data sources to characterize relationships among socio-structural stressors, psychosocial mediators, and HIV prevention and care continuum outcomes among Black MSM and combine methods from implementation science and agent-based modeling to understand the potential impact of structural interventions for reducing HIV transmission. Methods: We will utilize local empirical data to create a realistic synthetic population within an existing agent-based model and apply statistical and computational methods to better understand how socio-structural factors impact engagement in HIV prevention and care continuums. We will then conduct a series of experiments to evaluate how socio- structural factors impact the uptake of existing biomedical interventions and compare outcomes under scenarios with different combinations of interventions Significance: A better understanding of where and how to focus intervention efforts offers potential to improve outcomes along the care continuum by addressing socio-structural barriers to HIV prevention and care engagement for Black MSM. Once developed, our approach can be adapted to other geographic areas to reflect prevention priorities for local health departments and can serve as an example application of ABM methods within implementation science to advance HIV prevention science.