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Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina

As the COVID-19 pandemic moved beyond the initial heavily impacted and urbanized Northeast region of the United States, hotspots of cases in other urban areas ensued across the country in early 2020. In South Carolina, the spatial and temporal patterns were different, initially concentrating in smal...

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Autores principales: Huang, Qian, Jackson, Sarah, Derakhshan, Sahar, Lee, Logan, Pham, Erika, Jackson, Amber, Cutter, Susan L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857563/
https://www.ncbi.nlm.nih.gov/pubmed/33534870
http://dx.doi.org/10.1371/journal.pone.0246548
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author Huang, Qian
Jackson, Sarah
Derakhshan, Sahar
Lee, Logan
Pham, Erika
Jackson, Amber
Cutter, Susan L.
author_facet Huang, Qian
Jackson, Sarah
Derakhshan, Sahar
Lee, Logan
Pham, Erika
Jackson, Amber
Cutter, Susan L.
author_sort Huang, Qian
collection PubMed
description As the COVID-19 pandemic moved beyond the initial heavily impacted and urbanized Northeast region of the United States, hotspots of cases in other urban areas ensued across the country in early 2020. In South Carolina, the spatial and temporal patterns were different, initially concentrating in small towns within metro counties, then diffusing to centralized urban areas and rural areas. When mitigation restrictions were relaxed, hotspots reappeared in the major cities. This paper examines the county-scale spatial and temporal patterns of confirmed cases of COVID-19 for South Carolina from March 1(st)—September 5(th), 2020. We first describe the initial diffusion of the new confirmed cases per week across the state, which remained under 2,000 cases until Memorial Day weekend (epi week 23) then dramatically increased, peaking in mid-July (epi week 29), and slowly declining thereafter. Second, we found significant differences in cases and deaths between urban and rural counties, partially related to the timing of the number of confirmed cases and deaths and the implementation of state and local mitigations. Third, we found that the case rates and mortality rates positively correlated with pre-existing social vulnerability. There was also a negative correlation between mortality rates and county resilience patterns, as expected, suggesting that counties with higher levels of inherent resilience had fewer deaths per 100,000 population.
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spelling pubmed-78575632021-02-11 Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina Huang, Qian Jackson, Sarah Derakhshan, Sahar Lee, Logan Pham, Erika Jackson, Amber Cutter, Susan L. PLoS One Research Article As the COVID-19 pandemic moved beyond the initial heavily impacted and urbanized Northeast region of the United States, hotspots of cases in other urban areas ensued across the country in early 2020. In South Carolina, the spatial and temporal patterns were different, initially concentrating in small towns within metro counties, then diffusing to centralized urban areas and rural areas. When mitigation restrictions were relaxed, hotspots reappeared in the major cities. This paper examines the county-scale spatial and temporal patterns of confirmed cases of COVID-19 for South Carolina from March 1(st)—September 5(th), 2020. We first describe the initial diffusion of the new confirmed cases per week across the state, which remained under 2,000 cases until Memorial Day weekend (epi week 23) then dramatically increased, peaking in mid-July (epi week 29), and slowly declining thereafter. Second, we found significant differences in cases and deaths between urban and rural counties, partially related to the timing of the number of confirmed cases and deaths and the implementation of state and local mitigations. Third, we found that the case rates and mortality rates positively correlated with pre-existing social vulnerability. There was also a negative correlation between mortality rates and county resilience patterns, as expected, suggesting that counties with higher levels of inherent resilience had fewer deaths per 100,000 population. Public Library of Science 2021-02-03 /pmc/articles/PMC7857563/ /pubmed/33534870 http://dx.doi.org/10.1371/journal.pone.0246548 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Huang, Qian
Jackson, Sarah
Derakhshan, Sahar
Lee, Logan
Pham, Erika
Jackson, Amber
Cutter, Susan L.
Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina
title Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina
title_full Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina
title_fullStr Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina
title_full_unstemmed Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina
title_short Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina
title_sort urban-rural differences in covid-19 exposures and outcomes in the south: a preliminary analysis of south carolina
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857563/
https://www.ncbi.nlm.nih.gov/pubmed/33534870
http://dx.doi.org/10.1371/journal.pone.0246548
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