Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, China

Abstract As of July 27, 2020, COVID‐19 has caused 640,000 deaths worldwide and has had a major impact on people's productivity and lives. Analyzing the spatial distribution characteristics of COVID‐19 cases and their relationships with meteorological and environmental factors might help enrich...

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Main Authors: Xiaochi Huang, Han Zhou, Xiaofeng Yang, Wen Zhou, Jiejun Huang, Yanbin Yuan
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2021-06-01
Series:GeoHealth
Subjects:
GWR
Online Access:https://doi.org/10.1029/2020GH000358
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spelling doaj-b707ff79f7514cd48e509e15abb67f432021-07-01T11:46:10ZengAmerican Geophysical Union (AGU)GeoHealth2471-14032021-06-0156n/an/a10.1029/2020GH000358Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, ChinaXiaochi Huang0Han Zhou1Xiaofeng Yang2Wen Zhou3Jiejun Huang4Yanbin Yuan5School of Resource and Environmental Engineering Wuhan University of Technology Wuhan ChinaSchool of Resource and Environmental Engineering Wuhan University of Technology Wuhan ChinaWuhan Regional Climate Center Hubei Meteorological Service Wuhan ChinaSchool of Energy and Environment Guy Carpenter Asia–Pacific Climate Impact Centre City University of Hong Kong Hong Kong ChinaSchool of Resource and Environmental Engineering Wuhan University of Technology Wuhan ChinaSchool of Resource and Environmental Engineering Wuhan University of Technology Wuhan ChinaAbstract As of July 27, 2020, COVID‐19 has caused 640,000 deaths worldwide and has had a major impact on people's productivity and lives. Analyzing the spatial distribution characteristics of COVID‐19 cases and their relationships with meteorological and environmental factors might help enrich our knowledge of virus transmission and formulate reasonable epidemic prevention strategies. Taking the cumulative confirmed cases in Hubei province from January 23, 2020, to April 8, 2020, as an example, this study analyzed the spatial evolution characteristics of confirmed COVID‐19 cases in Hubei province using exploratory spatial data analysis and explored the spatial relationship between the main environmental and meteorological factors and confirmed COVID‐19 cases using a geographically weighted regression (GWR) model. Results show that there was no obvious spatial clustering of confirmed COVID‐19 cases in Hubei province, while the decline and end of the newly confirmed cases revealed relatively obvious negative spatial correlations. Due to the lockdown in Hubei province, the main air quality indexes (e.g., AQI and PM2.5) decreased significantly and environmental quality was better than historical contemporaneous levels. Meanwhile, the results of the GWR model suggest that the impacts of environmental and meteorological factors on the development of COVID‐19 were not significant. These findings indicate that measures such as social distancing and isolation played the primary role in controlling the development of the COVID‐19 epidemic.https://doi.org/10.1029/2020GH000358COVID‐19environmental and meteorological factorsESDAGWRHubei provincespatial autocorrelation
collection DOAJ
language English
format Article
sources DOAJ
author Xiaochi Huang
Han Zhou
Xiaofeng Yang
Wen Zhou
Jiejun Huang
Yanbin Yuan
spellingShingle Xiaochi Huang
Han Zhou
Xiaofeng Yang
Wen Zhou
Jiejun Huang
Yanbin Yuan
Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, China
GeoHealth
COVID‐19
environmental and meteorological factors
ESDA
GWR
Hubei province
spatial autocorrelation
author_facet Xiaochi Huang
Han Zhou
Xiaofeng Yang
Wen Zhou
Jiejun Huang
Yanbin Yuan
author_sort Xiaochi Huang
title Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, China
title_short Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, China
title_full Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, China
title_fullStr Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, China
title_full_unstemmed Spatial Characteristics of Coronavirus Disease 2019 and Their Possible Relationship With Environmental and Meteorological Factors in Hubei Province, China
title_sort spatial characteristics of coronavirus disease 2019 and their possible relationship with environmental and meteorological factors in hubei province, china
publisher American Geophysical Union (AGU)
series GeoHealth
issn 2471-1403
publishDate 2021-06-01
description Abstract As of July 27, 2020, COVID‐19 has caused 640,000 deaths worldwide and has had a major impact on people's productivity and lives. Analyzing the spatial distribution characteristics of COVID‐19 cases and their relationships with meteorological and environmental factors might help enrich our knowledge of virus transmission and formulate reasonable epidemic prevention strategies. Taking the cumulative confirmed cases in Hubei province from January 23, 2020, to April 8, 2020, as an example, this study analyzed the spatial evolution characteristics of confirmed COVID‐19 cases in Hubei province using exploratory spatial data analysis and explored the spatial relationship between the main environmental and meteorological factors and confirmed COVID‐19 cases using a geographically weighted regression (GWR) model. Results show that there was no obvious spatial clustering of confirmed COVID‐19 cases in Hubei province, while the decline and end of the newly confirmed cases revealed relatively obvious negative spatial correlations. Due to the lockdown in Hubei province, the main air quality indexes (e.g., AQI and PM2.5) decreased significantly and environmental quality was better than historical contemporaneous levels. Meanwhile, the results of the GWR model suggest that the impacts of environmental and meteorological factors on the development of COVID‐19 were not significant. These findings indicate that measures such as social distancing and isolation played the primary role in controlling the development of the COVID‐19 epidemic.
topic COVID‐19
environmental and meteorological factors
ESDA
GWR
Hubei province
spatial autocorrelation
url https://doi.org/10.1029/2020GH000358
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