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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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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