Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States

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 C...

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Autores principales:	Hadeel AlQadi, Majid Bani-Yaghoub, Sindhu Balakumar, Siqi Wu, Alex Francisco
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	disease surveillance gender race ethnicity COVID-19 SatScan Medicine R
Acceso en línea:	https://doaj.org/article/04af936bde8b43caad124647dbdadc82
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spelling	oai:doaj.org-article:04af936bde8b43caad124647dbdadc822021-11-11T16:37:17ZAssessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States10.3390/ijerph1821114961660-46011661-7827https://doaj.org/article/04af936bde8b43caad124647dbdadc822021-11-01T00:00:00Zhttps://www.mdpi.com/1660-4601/18/21/11496https://doaj.org/toc/1661-7827https://doaj.org/toc/1660-4601Coronavirus 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.Hadeel AlQadiMajid Bani-YaghoubSindhu BalakumarSiqi WuAlex FranciscoMDPI AGarticledisease surveillancegenderraceethnicityCOVID-19SatScanMedicineRENInternational Journal of Environmental Research and Public Health, Vol 18, Iss 11496, p 11496 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	disease surveillance gender race ethnicity COVID-19 SatScan Medicine R
spellingShingle	disease surveillance gender race ethnicity COVID-19 SatScan Medicine R Hadeel AlQadi Majid Bani-Yaghoub Sindhu Balakumar Siqi Wu Alex Francisco Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States
description	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.
format	article
author	Hadeel AlQadi Majid Bani-Yaghoub Sindhu Balakumar Siqi Wu Alex Francisco
author_facet	Hadeel AlQadi Majid Bani-Yaghoub Sindhu Balakumar Siqi Wu Alex Francisco
author_sort	Hadeel AlQadi
title	Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States
title_short	Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States
title_full	Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States
title_fullStr	Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States
title_full_unstemmed	Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States
title_sort	assessment of retrospective covid-19 spatial clusters with respect to demographic factors: case study of kansas city, missouri, united states
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/04af936bde8b43caad124647dbdadc82
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Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States

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