PDF(Pubmed)
Abstract：
Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The United States (U.S.) has the highest number of reported COVID-19 infections and related deaths in the world, accounting for 17.8% of total global confirmed cases as of August 2021. As COVID-19 spread throughout communities across the U.S., it became clear that inequities would arise among differing demographics. Several researchers have suggested that certain racial and ethnic minority groups may have been disproportionately impacted by the spread of COVID-19. In the present study, we used the daily data of COVID-19 cases in Kansas City, Missouri, to observe differences in COVID-19 clusters with respect to gender, race, and ethnicity. Specifically, we utilized a retrospective Poisson spatial scan statistic with respect to demographic factors to detect daily clusters of COVID-19 in Kansas City at the zip code level from March to November 2020. Our statistical results indicated that clusters of the male population were more widely scattered than clusters of the female population. Clusters of the Hispanic population had the highest prevalence and were also more widely scattered. This demographic cluster analysis can provide guidance for reducing the social inequalities associated with the COVID-19 pandemic. Moreover, applying stronger preventive and control measures to emerging clusters can reduce the likelihood of another epidemic wave of infection.
摘要：
2019年冠状病毒病（COVID-19）是由严重急性呼吸道综合征冠状病毒2（SARS-CoV-2）引起的。美国（U.S.）报告的COVID-19感染和相关死亡人数是世界上最高的，截至2021年8月，占全球确诊病例总数的17.8%。随着COVID-19在美国各地的社区传播，很明显，不同的人口结构之间会出现不平等。几位研究人员认为，某些种族和少数族裔群体可能受到COVID-19传播的不成比例的影响。在本研究中,我们使用了堪萨斯城的COVID-19病例的每日数据，密苏里州,为了观察COVID-19集群在性别方面的差异，种族,和种族。具体来说,我们利用人口统计因素的回顾性Poisson空间扫描统计量,在2020年3月至11月在堪萨斯城以邮政编码水平检测COVID-19的每日聚集性.我们的统计结果表明，男性群体比女性群体更分散。西班牙裔人口的集群患病率最高，并且分布范围也更广泛。这种人口统计学聚类分析可以为减少与COVID-19大流行相关的社会不平等提供指导。此外，对新兴集群采取更强有力的预防和控制措施，可以减少另一波流行病感染的可能性。
