Spatial Clustering of County-Level COVID-19 Rates in the U.S.

Despite the widespread prevalence of cases associated with the coronavirus disease 2019 (COVID-19) pandemic, little is known about the spatial clustering of COVID-19 in the United States. Data on COVID-19 cases were used to identify U.S. counties that have both high and low COVID-19 incident proport...

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Autores principales:	Marcus R. Andrews, Kosuke Tamura, Janae N. Best, Joniqua N. Ceasar, Kaylin G. Batey, Troy A. Kearse, Lavell V. Allen, Yvonne Baumer, Billy S. Collins, Valerie M. Mitchell, Tiffany M. Powell-Wiley
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	COVID-19 geographic information systems applied spatial statistics Medicine R
Acceso en línea:	https://doaj.org/article/58f487be55d34f1f92d03ed18d391196
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id	oai:doaj.org-article:58f487be55d34f1f92d03ed18d391196
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spelling	oai:doaj.org-article:58f487be55d34f1f92d03ed18d3911962021-11-25T17:51:42ZSpatial Clustering of County-Level COVID-19 Rates in the U.S.10.3390/ijerph1822121701660-46011661-7827https://doaj.org/article/58f487be55d34f1f92d03ed18d3911962021-11-01T00:00:00Zhttps://www.mdpi.com/1660-4601/18/22/12170https://doaj.org/toc/1661-7827https://doaj.org/toc/1660-4601Despite the widespread prevalence of cases associated with the coronavirus disease 2019 (COVID-19) pandemic, little is known about the spatial clustering of COVID-19 in the United States. Data on COVID-19 cases were used to identify U.S. counties that have both high and low COVID-19 incident proportions and clusters. Our results suggest that there are a variety of sociodemographic variables that are associated with the severity of COVID-19 county-level incident proportions. As the pandemic evolved, communities of color were disproportionately impacted. Subsequently, it shifted from communities of color and metropolitan areas to rural areas in the U.S. Our final period showed limited differences in county characteristics, suggesting that COVID-19 infections were more widespread. The findings might address the systemic barriers and health disparities that may result in high incident proportions of COVID-19 clusters.Marcus R. AndrewsKosuke TamuraJanae N. BestJoniqua N. CeasarKaylin G. BateyTroy A. KearseLavell V. AllenYvonne BaumerBilly S. CollinsValerie M. MitchellTiffany M. Powell-WileyMDPI AGarticleCOVID-19geographic information systemsapplied spatial statisticsMedicineRENInternational Journal of Environmental Research and Public Health, Vol 18, Iss 12170, p 12170 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 geographic information systems applied spatial statistics Medicine R
spellingShingle	COVID-19 geographic information systems applied spatial statistics Medicine R Marcus R. Andrews Kosuke Tamura Janae N. Best Joniqua N. Ceasar Kaylin G. Batey Troy A. Kearse Lavell V. Allen Yvonne Baumer Billy S. Collins Valerie M. Mitchell Tiffany M. Powell-Wiley Spatial Clustering of County-Level COVID-19 Rates in the U.S.
description	Despite the widespread prevalence of cases associated with the coronavirus disease 2019 (COVID-19) pandemic, little is known about the spatial clustering of COVID-19 in the United States. Data on COVID-19 cases were used to identify U.S. counties that have both high and low COVID-19 incident proportions and clusters. Our results suggest that there are a variety of sociodemographic variables that are associated with the severity of COVID-19 county-level incident proportions. As the pandemic evolved, communities of color were disproportionately impacted. Subsequently, it shifted from communities of color and metropolitan areas to rural areas in the U.S. Our final period showed limited differences in county characteristics, suggesting that COVID-19 infections were more widespread. The findings might address the systemic barriers and health disparities that may result in high incident proportions of COVID-19 clusters.
format	article
author	Marcus R. Andrews Kosuke Tamura Janae N. Best Joniqua N. Ceasar Kaylin G. Batey Troy A. Kearse Lavell V. Allen Yvonne Baumer Billy S. Collins Valerie M. Mitchell Tiffany M. Powell-Wiley
author_facet	Marcus R. Andrews Kosuke Tamura Janae N. Best Joniqua N. Ceasar Kaylin G. Batey Troy A. Kearse Lavell V. Allen Yvonne Baumer Billy S. Collins Valerie M. Mitchell Tiffany M. Powell-Wiley
author_sort	Marcus R. Andrews
title	Spatial Clustering of County-Level COVID-19 Rates in the U.S.
title_short	Spatial Clustering of County-Level COVID-19 Rates in the U.S.
title_full	Spatial Clustering of County-Level COVID-19 Rates in the U.S.
title_fullStr	Spatial Clustering of County-Level COVID-19 Rates in the U.S.
title_full_unstemmed	Spatial Clustering of County-Level COVID-19 Rates in the U.S.
title_sort	spatial clustering of county-level covid-19 rates in the u.s.
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/58f487be55d34f1f92d03ed18d391196
work_keys_str_mv	AT marcusrandrews spatialclusteringofcountylevelcovid19ratesintheus AT kosuketamura spatialclusteringofcountylevelcovid19ratesintheus AT janaenbest spatialclusteringofcountylevelcovid19ratesintheus AT joniquanceasar spatialclusteringofcountylevelcovid19ratesintheus AT kaylingbatey spatialclusteringofcountylevelcovid19ratesintheus AT troyakearse spatialclusteringofcountylevelcovid19ratesintheus AT lavellvallen spatialclusteringofcountylevelcovid19ratesintheus AT yvonnebaumer spatialclusteringofcountylevelcovid19ratesintheus AT billyscollins spatialclusteringofcountylevelcovid19ratesintheus AT valeriemmitchell spatialclusteringofcountylevelcovid19ratesintheus AT tiffanympowellwiley spatialclusteringofcountylevelcovid19ratesintheus
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Spatial Clustering of County-Level COVID-19 Rates in the U.S.

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