Equitable Response in Crisis: Methodology and Application for COVID-19

Benjamin D. Trump, A. Jin, S. Galaitsi, Christopher Cummings, H. Jarman, S. Greer, Vidur Sharma, I. Linkov
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Abstract

Equitable allocation and distribution of the COVID-19 vaccine have proven to be a major policy challenge exacerbated by incomplete pandemic risk data. To rectify this shortcoming, a three-step data visualization methodology was developed to assess COVID-19 vaccination equity in the United States using state health department, U.S. Census, and CDC data. Part one establishes an equitable pathway deviation index to identify populations with limited vaccination. Part two measures perceived access and public intentions to vaccinate over time. Part three synthesizes these data with the social vulnerability index to identify areas and communities at particular risk. Results demonstrate significant equity differences at a census-tract level, and across demographic and socioeconomic population characteristics. Results were used by various federal agencies to improve coordinated pandemic risk response and implement a commitment to equity as defined by the Executive Order regarding COVID-19 vaccination and booster policy. This methodology can be utilized in other fields where addressing the difficulties of promoting health equity in public policy is essential.
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危机中的公平应对:应对COVID-19的方法与应用
事实证明,公平分配和分发COVID-19疫苗是一项重大政策挑战,大流行风险数据不完整加剧了这一挑战。为了纠正这一缺点,研究人员开发了一种三步数据可视化方法,利用州卫生部门、美国人口普查和疾病预防控制中心的数据来评估美国COVID-19疫苗接种的公平性。第一部分建立了一个公平的路径偏差指数来识别有限接种人群。第二部分衡量随着时间的推移,人们对接种疫苗的可及性和公众意愿。第三部分将这些数据与社会脆弱性指数综合起来,以确定特别危险的地区和社区。结果表明,在人口普查区水平上,以及在人口统计学和社会经济人口特征上,存在显著的公平差异。结果被各联邦机构用于改善协调一致的大流行风险应对,并履行行政命令中关于COVID-19疫苗接种和加强政策的公平承诺。这一方法可用于其他领域,在这些领域,必须解决在公共政策中促进卫生公平的困难。
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CiteScore
5.20
自引率
13.60%
发文量
34
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