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Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China()

The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. It is important to identify high-risk residence communities and the risk factors for decision making on targeted prevention and control measures. In this paper, the number of confirmed and suspecte...

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Autores principales: Guo, Xiaojing, Zhou, Xinyue, Tian, Fengshi, Zhang, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076970/
http://dx.doi.org/10.1016/j.jnlssr.2021.04.001
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author Guo, Xiaojing
Zhou, Xinyue
Tian, Fengshi
Zhang, Hui
author_facet Guo, Xiaojing
Zhou, Xinyue
Tian, Fengshi
Zhang, Hui
author_sort Guo, Xiaojing
collection PubMed
description The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. It is important to identify high-risk residence communities and the risk factors for decision making on targeted prevention and control measures. In this paper, the number of confirmed and suspected cases of COVID-19 in the residence communities in Wuhan, China was collected together with the characteristic variables of the residence communities and the distances between the residence communities and nearby crowded places. The correlation analysis was conducted between the number of confirmed cases and the characteristic/distance variables. Concerning the characteristic variables, there are significant positive correlations between the number of COVID-19 confirmed cases and the construction area, covered area, total number of houses, total number of buildings, volume ratio, property charge, and number of second-hand houses in the residence communities in Wuhan, while minor or no correlation is observed for the average price of houses, construction year, greening ratio, or number of sold houses. Concerning the distance variables, there are significant negative correlations between the number of confirmed cases and the distances from the residence communities to the nearest universities, business clusters, and railway stations, while minor or no correlation is observed for the Huanan Seafood Wholesale Market, kindergartens, primary schools, middle schools, shopping malls, cinemas, subway stations, bus stops, inter-city bus stations, airport, general hospitals, or appointed hospitals for COVID-19 pandemic. Therefore, the residence communities which are newly-built, where the volume ratio or property charge is high or the construction area, covered area, or total number of houses, buildings, second-hand houses, or sold houses is large, or which are close to universities, business clusters, subway stations, or railway stations are the high-risk ones where strict measures should be taken. This study provides the authorities with a valuable reference for precise disease prevention and control on the residence community level in similar cities in the world.
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spelling pubmed-80769702021-04-27 Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China() Guo, Xiaojing Zhou, Xinyue Tian, Fengshi Zhang, Hui Journal of Safety Science and Resilience Article The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. It is important to identify high-risk residence communities and the risk factors for decision making on targeted prevention and control measures. In this paper, the number of confirmed and suspected cases of COVID-19 in the residence communities in Wuhan, China was collected together with the characteristic variables of the residence communities and the distances between the residence communities and nearby crowded places. The correlation analysis was conducted between the number of confirmed cases and the characteristic/distance variables. Concerning the characteristic variables, there are significant positive correlations between the number of COVID-19 confirmed cases and the construction area, covered area, total number of houses, total number of buildings, volume ratio, property charge, and number of second-hand houses in the residence communities in Wuhan, while minor or no correlation is observed for the average price of houses, construction year, greening ratio, or number of sold houses. Concerning the distance variables, there are significant negative correlations between the number of confirmed cases and the distances from the residence communities to the nearest universities, business clusters, and railway stations, while minor or no correlation is observed for the Huanan Seafood Wholesale Market, kindergartens, primary schools, middle schools, shopping malls, cinemas, subway stations, bus stops, inter-city bus stations, airport, general hospitals, or appointed hospitals for COVID-19 pandemic. Therefore, the residence communities which are newly-built, where the volume ratio or property charge is high or the construction area, covered area, or total number of houses, buildings, second-hand houses, or sold houses is large, or which are close to universities, business clusters, subway stations, or railway stations are the high-risk ones where strict measures should be taken. This study provides the authorities with a valuable reference for precise disease prevention and control on the residence community level in similar cities in the world. China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. 2021-06 2021-04-24 /pmc/articles/PMC8076970/ http://dx.doi.org/10.1016/j.jnlssr.2021.04.001 Text en © 2021 The Authors 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
Guo, Xiaojing
Zhou, Xinyue
Tian, Fengshi
Zhang, Hui
Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China()
title Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China()
title_full Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China()
title_fullStr Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China()
title_full_unstemmed Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China()
title_short Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China()
title_sort identification of the high-risk residence communities and possible risk factors of covid-19 in wuhan, china()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076970/
http://dx.doi.org/10.1016/j.jnlssr.2021.04.001
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