Systems modeling to address the social and biological drivers of disparities in infection and mortality from emerging infectious diseases

项目摘要/摘要 新冠肺炎大流行的疾病和死亡分布在每个国家都非常不平等 尺寸。在整个2021年冬季和春季的疫苗接种运动中，这些不平等现象一再发生。 风险更低、更富有和更白的人比他们的同龄人更早获得疫苗接种。 对于那些通过社会流行病学和医学社会学的理论视角来看待大流行的人来说， 这些差距的极端和性质是很容易预料到的。然而，预测和动态系统 引导国内和全球新冠肺炎反应的模特们通常会忽视社会 感染的决定因素及其后果。本应用程序的目标是概述一种多层次的方法 到传染病传播建模和数据分析，将暴露的社会决定因素， 严重疾病和死亡与传播和疾病的生物学特征同等重要 进步。我们的首要目标是开发一套能够延伸新冠肺炎经验的工具 预防未来暴发、流行病和大流行的类似差异。这样做的第一个目的是 该项目将开发和分析传播模型，将联合社会和生物驱动因素整合在一起 感染差异。这项拟议的工作将确定导致感染风险差异的病因因素，以及 提出与政策相关的替代方法来衡量感染差异。我们的第二个目标是评估 基于人群的前瞻性和观察性研究设计对#年社会经济差异的敏感性 感染风险和结果。我们将使用从分析得出的输入参数进行的模拟研究 详细的SARS-CoV-2病例数据，以了解这些研究在什么情况下设计了晦涩的钥匙 不同维度的差异。第三个目标将评估疫苗接种政策、行为和 对人群感染不平等的干预。随着新冠肺炎疫苗接种运动的进展 很明显，疫苗的迟疑和疫苗的可获得性是实现实质性水平的双重威胁。 种群免疫力。我们将把疫苗接种迟疑的调查数据与医疗保健可获得性和 SARS-CoV-2发病对强调风险和途径不公平的空间传播模型进行参数化 在新冠肺炎和其他疫苗可预防的疾病方面缩小这些差距。总而言之，拟议的 项目将为系统建模工具奠定基础，这些工具可用于促进未来疫情的公平性 和大流行应对措施。

Project Summary/Abstract The distribution of disease and death from the COVID-19 pandemic has been grossly unequal in every dimension. The vaccination campaign, throughout Winter and Spring 2021, has seen these inequities repeated. Lower-risk, wealthier, and Whiter individuals have received earlier access to vaccination than their counterparts. To those viewing the pandemic through the theoretical lens of social epidemiology and medical sociology, the extremity and nature of these disparities was easily anticipated. However, the predictive and dynamic systems models that have guided the domestic and global COVID-19 response have routinely ignored the social determinants of infection and its outcomes. The objective of this application is to outline a multi-level approach to infectious disease transmission modeling and data analysis that places the social determinants of exposure, severe disease and mortality on an equal footing with the biological features of transmission and disease progression. Our overarching goal is to develop a set of tools that will extend lessons from the COVID-19 pandemic to prevent similar disparities in future outbreaks, epidemics, and pandemics. The first aim of this project will develop and analyze transmission models that integrate the joint social and biological drivers of infection disparities. This proposed work will identify etiologic factors driving disparities in infection risk, and propose policy-relevant alternative approaches to measuring infection disparities. Our second aim will evaluate the sensitivity of population-based prospective and observational study designs to socioeconomic disparities in infection risk and outcomes. We will use simulation studies with input parameters derived from the analysis of detailed SARS-CoV-2 case data to understand the circumstances under which these study designs obscure key dimensions of disparity. The third aim will assess long-term effects of vaccination policies, behavior, and interventions on population-level infection inequalities. As the COVID-19 vaccination campaign has progressed it has become clear that vaccine hesitancy and vaccine access are dual threats to achieving substantial levels of population immunity. We will integrate survey data on vaccine hesitancy with data on healthcare access and SARS-CoV-2 incidence to parameterize a spatial transmission model highlighting inequity in risks and avenues for closing these gaps for COVID-19 and other vaccine preventable diseases. Taken together, the proposed projects will lay the foundation systems modeling tools that can be used to promote equity in future epidemic and pandemic responses.