The Impact of Social Vulnerability on COVID-19 in the US: An Analysis of Spatially Varying Relationships
The Impact of Social Vulnerability on COVID-19 in the US: An Analysis of Spatially Varying Relationships
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DOI：
10.1016/j.amepre.2020.06.006
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发表时间：
2020-09-01
影响因子：
5.5
通讯作者：
Horney, Jennifer A.
中科院分区：
文献类型：
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作者：
Karaye, Ibraheem M.;Horney, Jennifer A.
引言：由于无法获得适当的医疗、交通和营养，社会弱势群体在灾害期间面临更大的健康挑战风险。这项研究估计了美国COVID-19感染病例数与社会脆弱性之间的关系，确定了易受大流行影响的县。方法：利用社会脆弱性指数和COVID-19病例数数据，拟合普通最小二乘回归模型，评估全球COVID-19病例数与社会脆弱性的关系。使用地理加权回归模型评估局部关系，该模型可以有效地探索空间非平稳性。结果：截至2020年5月12日，美国共有1320909人被诊断为COVID-19。在本研究纳入的县中（91.5%，3108人中有2844人），田纳西州特罗斯代尔的病例数最高（每10万人中有16525.22例），加利福尼亚州特哈马的病例数最低（每10万人中有1.54例）。在全球层面，总体社会脆弱性指数（e(beta) =1.65, p=0.03），少数群体地位和语言(e(beta) =6.69, p
Introduction: Because of their inability to access adequate medical care, transportation, and nutrition, socially vulnerable populations are at an increased risk of health challenges during disasters. This study estimates the association between case counts of COVID-19 infection and social vulnerability in the U.S., identifying counties at increased vulnerability to the pandemic.Methods: Using Social Vulnerability Index and COVID-19 case count data, an ordinary least squares regression model was fitted to assess the global relationship between COVID-19 case counts and social vulnerability. Local relationships were assessed using a geographically weighted regression model, which is effective in exploring spatial nonstationarity.Results: As of May 12, 2020, a total of 1,320,909 people had been diagnosed with COVID-19 in the U.S. Of the counties included in this study (91.5%, 2,844 of 3,108), the highest case count was recorded in Trousdale, Tennessee (16,525.22 per 100,000) and the lowest in Tehama, California (1.54 per 100,000). At the global level, overall Social Vulnerability Index (e(beta) =1.65, p=0.03) and minority status and language (e(beta) =6.69, p