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

用于解决新发传染病感染和死亡率差异的社会和生物驱动因素的系统建模

• 批准号: 10415713
• 负责人: Jonathan L Zelner
• 金额: $ 67.93万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-20 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10415713
• 关键词: 2019-nCoV; Address; Attitude; Automobile Driving; Base Ratios; Behavior; Behavior Therapy; Behavioral; Biological; Biological Models; COVID-19; COVID-19 mortality; COVID-19 pandemic; COVID-19 vaccination; Childhood; Clinical Data; Clinical effectiveness; Communicable Diseases; Data; Data Analyses; Data Collection; Dimensions; Disease; Disease Outbreaks; Disease Progression; Dose; Effectiveness; Emerging Communicable Diseases; Ensure; Epidemic; Epidemiologic Factors; Epidemiology; Ethnic Origin; Etiology; Evaluation; Foundations; Frequencies; Future; Geography; Goals; Herd Immunity; Immunity; Incidence; Individual; Inequality; Infection; Intervention; Intervention Studies; Joints; Limb structure; Long-Term Effects; Longitudinal cohort; Masks; Measles; Measures; Medical Sociology; Methods; Minority Groups; Mission; Modeling; Morbidity - disease rate; National Institute on Minority Health and Health Disparities; Nature; Neighborhoods; Observational Study; Outcome; Phase; Policies; Population; Population Surveillance; Predisposition; Prospective Studies; Public Health; Race; Readiness; Research; Research Design; Risk; Series; Socioeconomic Status; Sociology; Statistical Models; Surveys; Thinking; Time; Vaccination; Vaccines; Work; Yawning; design; disease transmission; disparity reduction; dynamic system; effectiveness evaluation; emerging pathogen; foot; geographic disparity; health care availability; infection risk; infectious disease model; intervention effect; lens; low socioeconomic status; models and simulation; mortality; mortality risk; pandemic disease; pathogen; population based; prevent; prospective; protective effect; racial disparity; racial minority; residential segregation; response; simulation; social; social contact; social determinants; social epidemiology; social factors; social inequality; socioeconomic disparity; socioeconomics; surveillance data; surveillance study; therapy design; tool; transmission process; vaccine access; vaccine hesitancy

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.

项目摘要/摘要 疾病和死亡从199大流行中的疾病和死亡的分布在每一个中都非常不平等 方面。在整个2021年冬季和春季，疫苗接种运动已经重复了这些不平等现象。 低风险，较富有和白人的人比其同行者更早地接受了接种疫苗的机会。 对于那些通过社会流行病学和医学社会学的理论观察大流行的人来说 这些差异的肢体和性质很容易被预期。但是，预测和动态系统 指导国内和全球共同响应的模型通常忽略了社会 感染的决定因素及其结果。该应用程序的目的是概述多层次的方法 传染病的传播建模和数据分析，以使社会决定因素的暴露因素， 与传播和疾病的生物学特征相等的疾病和死亡率 进展。我们的总体目标是开发一组将从Covid-19的工具扩展的工具 大流行是为了防止未来爆发，流行病和流行病中的类似差距。第一个目的 项目将开发和分析传输模型，以整合共同的社会和生物驱动因素 感染差异。这项拟议的工作将确定促进感染风险差异的病因学因素，以及 提出与政策相关的替代方法来衡量感染差异。我们的第二个目标将评估 基于人群的前瞻性和观察性研究设计对社会经济差异的敏感性 感染风险和结果。我们将使用模拟研究与从分析中得出的输入参数 详细的SARS-COV-2案例数据，以了解这些研究设计的情况掩盖了密钥 差异的维度。第三个目标将评估疫苗接种政策，行为和 人口水平感染不平等的干预措施。随着COVID-19疫苗接种运动的发展 很明显，疫苗犹豫和疫苗接种是对实现大量水平的双重威胁 人口免疫。我们将将有关疫苗犹豫的调查数据与有关医疗保健访问的数据和 SARS-COV-2发病率以参数化空间传输模型突出了风险和途径的不平等现象 为了缩小这些差距，用于1900和其他可预防疾病的疫苗。两者一起，提议 项目将奠定基础系统建模工具，可用于在未来流行病中促进公平 和大流行反应。