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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Main Authors: Xiaojing Guo, Xinyue Zhou, Fengshi Tian, Hui Zhang
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2021-06-01
Series:Journal of Safety Science and Resilience
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666449621000037
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spelling doaj-982cb029c5f142aa928196033e070b9d2021-08-12T04:35:52ZengKeAi Communications Co., Ltd.Journal of Safety Science and Resilience2666-44962021-06-01223139Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, ChinaXiaojing Guo0Xinyue Zhou1Fengshi Tian2Hui Zhang3Institute of Public Safety Research, Tsinghua University, Beijing 100084, ChinaDepartment of Marketing, Zhejiang University, Hangzhou 310058, ChinaInstitute of Public Safety Research, Tsinghua University, Beijing 100084, ChinaInstitute of Public Safety Research, Tsinghua University, Beijing 100084, China; Corresponding author.; Department of Marketing, Zhejiang University, Hangzhou 310058, ChinaThe 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.http://www.sciencedirect.com/science/article/pii/S2666449621000037COVID-19Residence communityRisk factorCorrelation analysis
collection DOAJ
language English
format Article
sources DOAJ
author Xiaojing Guo
Xinyue Zhou
Fengshi Tian
Hui Zhang
spellingShingle Xiaojing Guo
Xinyue Zhou
Fengshi Tian
Hui Zhang
Identification of the high-risk residence communities and possible risk factors of COVID-19 in Wuhan, China
Journal of Safety Science and Resilience
COVID-19
Residence community
Risk factor
Correlation analysis
author_facet Xiaojing Guo
Xinyue Zhou
Fengshi Tian
Hui Zhang
author_sort Xiaojing Guo
title 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_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_sort identification of the high-risk residence communities and possible risk factors of covid-19 in wuhan, china
publisher KeAi Communications Co., Ltd.
series Journal of Safety Science and Resilience
issn 2666-4496
publishDate 2021-06-01
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.
topic COVID-19
Residence community
Risk factor
Correlation analysis
url http://www.sciencedirect.com/science/article/pii/S2666449621000037
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