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Spatial spillover and COVID-19 spread in the U.S.

BACKGROUND: This research estimates the effects of vulnerability on the spread of COVID-19 cases across U.S. counties. Vulnerability factors (Socioeconomic Status, Minority Status & Language, Housing type, Transportation, Household Composition & Disability, Epidemiological Factors, Healthcar...

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Autores principales: Ulimwengu, John, Kibonge, Aziza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8475369/
https://www.ncbi.nlm.nih.gov/pubmed/34579689
http://dx.doi.org/10.1186/s12889-021-11809-2
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author Ulimwengu, John
Kibonge, Aziza
author_facet Ulimwengu, John
Kibonge, Aziza
author_sort Ulimwengu, John
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description BACKGROUND: This research estimates the effects of vulnerability on the spread of COVID-19 cases across U.S. counties. Vulnerability factors (Socioeconomic Status, Minority Status & Language, Housing type, Transportation, Household Composition & Disability, Epidemiological Factors, Healthcare system Factors, High-risk Environments, and Population density) do not only influence an individual’s likelihood of getting infected but also influence the likelihood of his/her neighbors getting infected. Thus, spatial interactions occurring among individuals are likely to lead to spillover effects which may cause further virus transmission. METHODS: This research uses the COVID-19 community index (CCVI), which defines communities likely vulnerable to the impact of the pandemic and captures the multi-dimensionality of vulnerability. The spatial Durbin model was used to estimate the spillover effects of vulnerability to COVID-19 in U.S. counties, from May 1 to December 15, 2020. RESULTS: The findings confirm the existence of spatial spillover effects; with indirect effects (from neighboring counties) dominating the direct effects (from county-own vulnerability level). This not only validates social distancing as a strategy to contain the spread of the pandemic but also calls for comprehensive and coordinated approach to fight its effects. By keeping vulnerability factors constant but varying the number of reported infected cases every 2 weeks, we found that marginal effects of vulnerability vary significantly across counties. This might be the reflection of both the changing intensity of the pandemic itself but also the lack of consistency in the measures implemented to combat it. CONCLUSION: Overall, the results indicate that high vulnerability in Minority, Epidemiological factors, Healthcare System Factors, and High-Risk Environments in each county and adjacent counties leads to an increase in COVID-19 confirmed cases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11809-2.
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spelling pubmed-84753692021-09-28 Spatial spillover and COVID-19 spread in the U.S. Ulimwengu, John Kibonge, Aziza BMC Public Health Research BACKGROUND: This research estimates the effects of vulnerability on the spread of COVID-19 cases across U.S. counties. Vulnerability factors (Socioeconomic Status, Minority Status & Language, Housing type, Transportation, Household Composition & Disability, Epidemiological Factors, Healthcare system Factors, High-risk Environments, and Population density) do not only influence an individual’s likelihood of getting infected but also influence the likelihood of his/her neighbors getting infected. Thus, spatial interactions occurring among individuals are likely to lead to spillover effects which may cause further virus transmission. METHODS: This research uses the COVID-19 community index (CCVI), which defines communities likely vulnerable to the impact of the pandemic and captures the multi-dimensionality of vulnerability. The spatial Durbin model was used to estimate the spillover effects of vulnerability to COVID-19 in U.S. counties, from May 1 to December 15, 2020. RESULTS: The findings confirm the existence of spatial spillover effects; with indirect effects (from neighboring counties) dominating the direct effects (from county-own vulnerability level). This not only validates social distancing as a strategy to contain the spread of the pandemic but also calls for comprehensive and coordinated approach to fight its effects. By keeping vulnerability factors constant but varying the number of reported infected cases every 2 weeks, we found that marginal effects of vulnerability vary significantly across counties. This might be the reflection of both the changing intensity of the pandemic itself but also the lack of consistency in the measures implemented to combat it. CONCLUSION: Overall, the results indicate that high vulnerability in Minority, Epidemiological factors, Healthcare System Factors, and High-Risk Environments in each county and adjacent counties leads to an increase in COVID-19 confirmed cases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11809-2. BioMed Central 2021-09-27 /pmc/articles/PMC8475369/ /pubmed/34579689 http://dx.doi.org/10.1186/s12889-021-11809-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ulimwengu, John
Kibonge, Aziza
Spatial spillover and COVID-19 spread in the U.S.
title Spatial spillover and COVID-19 spread in the U.S.
title_full Spatial spillover and COVID-19 spread in the U.S.
title_fullStr Spatial spillover and COVID-19 spread in the U.S.
title_full_unstemmed Spatial spillover and COVID-19 spread in the U.S.
title_short Spatial spillover and COVID-19 spread in the U.S.
title_sort spatial spillover and covid-19 spread in the u.s.
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8475369/
https://www.ncbi.nlm.nih.gov/pubmed/34579689
http://dx.doi.org/10.1186/s12889-021-11809-2
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