RAPID: Understanding the Disparate Impact of COVID-19

有传闻证据表明，与相对富裕的社区相比，新冠肺炎 (COVID-19) 大流行对有色人种社区和贫困社区的影响更大。 本研究将利用两个项目系统地研究 COVID-19 大流行对不同社会经济群体产生不同影响的原因和后果。 第一个项目使用新的跨州调查数据来调查穷人获得公共健康保险是否会减少个人感染 COVID-19 疾病的机会。 研究人员收集数据的独特方式和他们使用的方法使他们能够建立公共健康保险与 COVID-19 传播之间的因果关系。 第二个项目将使用不同的跨州调查数据来调查 COVID-19 对政治和意识形态偏好的影响。该研究项目的结果将为政策提供重要投入，以减少大流行对不同群体的不同影响，并间接降低传播速度及其总体负面影响。该研究项目调查了 COVID-19 对不同社区的不同影响。 该项目将收集根据《平价医疗法案》(ACA) 扩大医疗补助计划的州和未扩大医疗补助计划的州的毗邻县的数据，并使用断点回归 (RD) 设计来估计获得公共医疗保险对感染 COVID-19 概率的因果影响。第二个项目将使用小组调查数据来调查 COVID-19 大流行对政治意识形态、信仰和参与的影响。 该项目基于从 8 个州的 1000 人收集的面板数据。 抽样框架和收集的数据细节使绩效指标能够建立因果关系，同时控制各种社会经济和政策变量。 通过研究 COVID-19 不同影响的原因和后果，这项研究提供了比迄今为止提供的更广泛、更细致的 COVID-19 影响。 该研究项目的结果将为政策提供重要投入，以减少大流行对不同群体的不同影响，并间接降低传播速度及其总体负面影响。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

There is anecdotal evidence that the COVID-19 pandemic has disproportionately affected communities of color and poor communities than relatively affluent communities. This research will use two projects to systematically study the causes and consequences of disparate effects of the COVID-19 pandemic on different socioeconomic groups. The first project uses new cross state survey data to investigate whether access to public health insurance for the poor reduces the chances that individuals contract the COVID-19 disease. The unique way the researchers collect the data and the methodology they use allows them to establish a causal relationship between public health insurance access and COVID-19 spread. The second project will use a different cross-state survey data to investigate the effects of COVID-19 on political and ideological preferences. The results of this research project will provide important inputs into policies to reduce the disparate effects of the pandemic on different groups and indirectly reduce the rate of spread and its negative impact in the aggregate.This research project investigates the disparate effects of COVID-19 on different communities. The project will collect data from adjoining counties across states that expanded Medicaid under the Affordable Care Act (ACA) and those that did not and use regression discontinuity (RD) design to estimate the causal effects of access to public health insurance on the probability of getting COVID-19. The second project will use panel survey data to investigate the effects of the COVID-19 pandemic on political ideology, beliefs, and participation. This project is based on panel data collected from 1000 individuals in 8 states. The sampling frame, and details of the data collected allows the PIs to establish a causal relationship while controlling for a wide variety of socioeconomic and policy variables. By studying the causes and consequences of the disparate effects of COVID-19, this research provides a broader and more nuanced effects of COVID-19 than had hitherto been provided. The results of this research project will provide important inputs into policies to reduce the disparate effects of the pandemic on different groups and indirectly reduce the rate of spread and its negative impact in the aggregate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.