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Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China
Investigating the spatial epidemic dynamics of COVID-19 is crucial in understanding the routine of spatial diffusion and in surveillance, prediction, identification and prevention of another potential outbreak. However, previous studies attempting to evaluate these spatial diffusion dynamics are lim...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046135/ https://www.ncbi.nlm.nih.gov/pubmed/35512611 http://dx.doi.org/10.1016/j.socscimed.2022.114988 |
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author | Gu, Lijuan Yang, Linsheng Wang, Li Guo, Yanan Wei, Binggan Li, Hairong |
author_facet | Gu, Lijuan Yang, Linsheng Wang, Li Guo, Yanan Wei, Binggan Li, Hairong |
author_sort | Gu, Lijuan |
collection | PubMed |
description | Investigating the spatial epidemic dynamics of COVID-19 is crucial in understanding the routine of spatial diffusion and in surveillance, prediction, identification and prevention of another potential outbreak. However, previous studies attempting to evaluate these spatial diffusion dynamics are limited. Using city as the research unit and spatial association analysis as the primary strategy, this study explored the changing primary risk factors impacting the spatial spread of COVID-19 across Chinese cities under various diffusion assumptions and throughout the epidemic stage. Moreover, this study investigated the characteristics and geographical distributions of high-risk areas in different epidemic stages. The results empirically indicated rapid intercity diffusion at the early stage and primarily intracity diffusion thereafter. Before countermeasures took effect, proximity, GDP per capita, medical resources, outflows from Wuhan and intercity mobility significantly affected early diffusion. With speedily effective countermeasures, outflows from the epicenter, proximity, and intracity outflows played an important role. At the early stage, high-risk areas were mainly cities adjacent to the epicenter, with higher GDP per capita, or a combination of higher GDP per capita and better medical resources, with more outflow from the epicenter, or more intercity mobility. After countermeasures were effected, cities adjacent to the epicenter, or with more outflow from the epicenter or more intracity mobility became high-risk areas. This study provides an insightful understanding of the spatial diffusion of COVID-19 across cities. The findings are informative for effectively handling the potential recurrence of COVID-19 in various settings. |
format | Online Article Text |
id | pubmed-9046135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90461352022-04-28 Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China Gu, Lijuan Yang, Linsheng Wang, Li Guo, Yanan Wei, Binggan Li, Hairong Soc Sci Med Article Investigating the spatial epidemic dynamics of COVID-19 is crucial in understanding the routine of spatial diffusion and in surveillance, prediction, identification and prevention of another potential outbreak. However, previous studies attempting to evaluate these spatial diffusion dynamics are limited. Using city as the research unit and spatial association analysis as the primary strategy, this study explored the changing primary risk factors impacting the spatial spread of COVID-19 across Chinese cities under various diffusion assumptions and throughout the epidemic stage. Moreover, this study investigated the characteristics and geographical distributions of high-risk areas in different epidemic stages. The results empirically indicated rapid intercity diffusion at the early stage and primarily intracity diffusion thereafter. Before countermeasures took effect, proximity, GDP per capita, medical resources, outflows from Wuhan and intercity mobility significantly affected early diffusion. With speedily effective countermeasures, outflows from the epicenter, proximity, and intracity outflows played an important role. At the early stage, high-risk areas were mainly cities adjacent to the epicenter, with higher GDP per capita, or a combination of higher GDP per capita and better medical resources, with more outflow from the epicenter, or more intercity mobility. After countermeasures were effected, cities adjacent to the epicenter, or with more outflow from the epicenter or more intracity mobility became high-risk areas. This study provides an insightful understanding of the spatial diffusion of COVID-19 across cities. The findings are informative for effectively handling the potential recurrence of COVID-19 in various settings. Elsevier Ltd. 2022-06 2022-04-28 /pmc/articles/PMC9046135/ /pubmed/35512611 http://dx.doi.org/10.1016/j.socscimed.2022.114988 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Gu, Lijuan Yang, Linsheng Wang, Li Guo, Yanan Wei, Binggan Li, Hairong Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China |
title | Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China |
title_full | Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China |
title_fullStr | Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China |
title_full_unstemmed | Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China |
title_short | Understanding the spatial diffusion dynamics of the COVID-19 pandemic in the city system in China |
title_sort | understanding the spatial diffusion dynamics of the covid-19 pandemic in the city system in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046135/ https://www.ncbi.nlm.nih.gov/pubmed/35512611 http://dx.doi.org/10.1016/j.socscimed.2022.114988 |
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