Wang Chuyuan, Li Ziqi, Clay Mathews Mason, Praharaj Sarbeswar, Karna Brajesh, Solís Patricia
Department of Geography and Environmental Planning, Towson University, Towson, MD, USA.
Knowledge Exchange for Resilience, Arizona State University, Tempe, AZ, USA.
Int J Environ Health Res. 2022 May;32(5):1147-1154. doi: 10.1080/09603123.2020.1847258. Epub 2020 Nov 23.
This study aims to examine the spatially varying relationships between social vulnerability factors and COVID-19 cases and deaths in the contiguous United States. County-level COVID-19 data and the Centers for Disease Control and Prevention social vulnerability index (SVI) dataset were analyzed using local Spearman's rank correlation coefficient. Results suggested that SVI and four social vulnerability themes have spatially varying relationships with COVID-19 cases and deaths, which means spatial heterogeneity is an essential factor that influences the relationship, and the strength of association varies significantly across counties. County hot spots that were subject to all four social vulnerability themes during the pandemic were also identified. Local communities and health authorities should pay immediate attention to the most influential social vulnerability factors that are dominant in their region and incorporate measures tailored to the specific groups of people who are under the greatest risk of being affected during the COVID-19 pandemic.
本研究旨在考察美国本土社会脆弱性因素与新冠疫情病例及死亡之间的空间变化关系。利用局部斯皮尔曼等级相关系数对县级新冠疫情数据和美国疾病控制与预防中心社会脆弱性指数(SVI)数据集进行了分析。结果表明,社会脆弱性指数和四个社会脆弱性主题与新冠疫情病例及死亡存在空间变化关系,这意味着空间异质性是影响这种关系的一个重要因素,且各县之间的关联强度差异显著。研究还确定了疫情期间受所有四个社会脆弱性主题影响的县级热点地区。当地社区和卫生当局应立即关注本地区占主导地位的最具影响力的社会脆弱性因素,并针对在新冠疫情期间受影响风险最大的特定人群制定相应措施。