Noppert Grace A, Clarke Philippa, Hoover Andrew, Kubale John, Melendez Robert, Duchowny Kate, Hegde Sonia T
Institute for Social Research, University of Michigan.
Department of Epidemiology, Johns Hopkins University.
medRxiv. 2023 May 19:2023.05.19.23290222. doi: 10.1101/2023.05.19.23290222.
A lack of fine, spatially-resolute case data for the U.S. has prevented the examination of how COVID-19 burden has been distributed across neighborhoods, a known geographic unit of both risk and resilience, and is hampering efforts to identify and mitigate the long-term fallout from COVID-19 in vulnerable communities. Using spatially-referenced data from 21 states at the ZIP code or census tract level, we documented how the distribution of COVID-19 at the neighborhood-level varies significantly within and between states. The median case count per neighborhood (IQR) in Oregon was 3,608 (2,487) per 100,000 population, indicating a more homogenous distribution of COVID-19 burden, whereas in Vermont the median case count per neighborhood (IQR) was 8,142 (11,031) per 100,000. We also found that the association between features of the neighborhood social environment and burden varied in magnitude and direction by state. Our findings underscore the importance of local contexts when addressing the long-term social and economic fallout communities will face from COVID-19.
美国缺乏精细的、具有空间分辨率的病例数据,这阻碍了对新冠疫情负担如何在社区(一个已知的风险和恢复力地理单位)中分布的研究,并且妨碍了识别和减轻弱势群体中新冠疫情长期影响的努力。利用来自21个州邮政编码或人口普查区层面的空间参考数据,我们记录了新冠疫情在社区层面的分布在州内和州际之间如何显著不同。俄勒冈州每个社区每10万人的病例数中位数(四分位距)为3608(2487),表明新冠疫情负担分布更为均匀,而在佛蒙特州,每个社区每10万人的病例数中位数(四分位距)为8142(11031)。我们还发现,社区社会环境特征与负担之间的关联在不同州的大小和方向各不相同。我们的研究结果强调了在应对社区将面临的新冠疫情长期社会和经济影响时考虑当地情况的重要性。