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

基本信息

  • 批准号:
    10669177
  • 负责人:
  • 金额:
    $ 64.51万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

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.
项目总结/文摘

项目成果

期刊论文数量(0)
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Jonathan L Zelner其他文献

Jonathan L Zelner的其他文献

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{{ truncateString('Jonathan L Zelner', 18)}}的其他基金

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
  • 财政年份:
    2022
  • 资助金额:
    $ 64.51万
  • 项目类别:
IP20-003, Data driven transmission models to optimize influenza vaccination and pandemic mitigation strategies - COVID-19 Supplement
IP20-003,数据驱动的传播模型,以优化流感疫苗接种和大流行缓解策略 - COVID-19 补充
  • 批准号:
    10650190
  • 财政年份:
    2020
  • 资助金额:
    $ 64.51万
  • 项目类别:
IP20-003, Data driven transmission models to optimize influenza vaccination and pandemic mitigation strategies - COVID-19 Supplement
IP20-003,数据驱动的传播模型,以优化流感疫苗接种和大流行缓解策略 - COVID-19 补充
  • 批准号:
    10216144
  • 财政年份:
    2020
  • 资助金额:
    $ 64.51万
  • 项目类别:
IP20-003, Data driven transmission models to optimize influenza vaccination and pandemic mitigation strategies - COVID-19 Supplement
IP20-003,数据驱动的传播模型,以优化流感疫苗接种和大流行缓解策略 - COVID-19 补充
  • 批准号:
    10438198
  • 财政年份:
    2020
  • 资助金额:
    $ 64.51万
  • 项目类别:
IP20-003, Data driven transmission models to optimize influenza vaccination and pandemic mitigation strategies - COVID-19 Supplement
IP20-003,数据驱动的传播模型,以优化流感疫苗接种和大流行缓解策略 - COVID-19 补充
  • 批准号:
    10246775
  • 财政年份:
    2020
  • 资助金额:
    $ 64.51万
  • 项目类别:

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