Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model

Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emp...

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Autores principales:	Ping He, Yu Gao, Longfei Guo, Tongtong Huo, Yuxin Li, Xingren Zhang, Yunfeng Li, Cheng Peng, Fanyun Meng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	COVID-19 risk assessment niche model epidemic prevention and control Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/ec8b01a95f894883802427f9454075d6
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spelling	oai:doaj.org-article:ec8b01a95f894883802427f9454075d62021-11-11T19:24:31ZEvaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model10.3390/su1321116672071-1050https://doaj.org/article/ec8b01a95f894883802427f9454075d62021-10-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/11667https://doaj.org/toc/2071-1050Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emphasize many research efforts. In this study, we collected location information for confirmed COVID-19 cases in Beijing, Shenyang, Dalian, and Shijiazhuang from 5 October 2020 to 5 January 2021, and selected 15 environmental variables to construct a model that comprehensively considered the parameters affecting the outbreak and spread of COVID-19 epidemics. Annual average temperature, catering, medical facilities, and other variables were processed using ArcGIS 10.3 and classified into three groups, including natural environmental variables, positive socio-environmental variables, and benign socio-environmental variables. We modeled the epidemic risk distribution for each area using the MaxEnt model based on the case occurrence data and environmental variables in four regions, and evaluated the key environmental variables influencing the epidemic distribution. The results showed that medium-risk zones were mainly distributed in Changping and Shunyi in Beijing, while Huanggu District in Shenyang and the southern part of Jinzhou District and the eastern part of Ganjingzi District in Dalian also represented areas at moderate risk of epidemics. For Shijiazhuang, Xinle, Gaocheng and other places were key COVID-19 epidemic spread areas. The jackknife assessment results revealed that positive socio-environmental variables are the most important factors affecting the outbreak and spread of COVID-19. The average contribution rate of the seafood market was 21.12%, and this contribution reached as high as 61.3% in Shenyang. The comprehensive analysis showed that improved seafood market management, strengthened crowd control and information recording, industry-catered specifications, and well-trained employees have become urgently needed prevention strategies in different regions. The comprehensive analysis indicated that the niche model could be used to classify the epidemic risk and propose prevention and control strategies when combined with the assessment results of the jackknife test, thus providing a theoretical basis and information support for suppressing the spread of COVID-19 epidemics.Ping HeYu GaoLongfei GuoTongtong HuoYuxin LiXingren ZhangYunfeng LiCheng PengFanyun MengMDPI AGarticleCOVID-19risk assessmentniche modelepidemic prevention and controlEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 11667, p 11667 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 risk assessment niche model epidemic prevention and control Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	COVID-19 risk assessment niche model epidemic prevention and control Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Ping He Yu Gao Longfei Guo Tongtong Huo Yuxin Li Xingren Zhang Yunfeng Li Cheng Peng Fanyun Meng Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model
description	Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emphasize many research efforts. In this study, we collected location information for confirmed COVID-19 cases in Beijing, Shenyang, Dalian, and Shijiazhuang from 5 October 2020 to 5 January 2021, and selected 15 environmental variables to construct a model that comprehensively considered the parameters affecting the outbreak and spread of COVID-19 epidemics. Annual average temperature, catering, medical facilities, and other variables were processed using ArcGIS 10.3 and classified into three groups, including natural environmental variables, positive socio-environmental variables, and benign socio-environmental variables. We modeled the epidemic risk distribution for each area using the MaxEnt model based on the case occurrence data and environmental variables in four regions, and evaluated the key environmental variables influencing the epidemic distribution. The results showed that medium-risk zones were mainly distributed in Changping and Shunyi in Beijing, while Huanggu District in Shenyang and the southern part of Jinzhou District and the eastern part of Ganjingzi District in Dalian also represented areas at moderate risk of epidemics. For Shijiazhuang, Xinle, Gaocheng and other places were key COVID-19 epidemic spread areas. The jackknife assessment results revealed that positive socio-environmental variables are the most important factors affecting the outbreak and spread of COVID-19. The average contribution rate of the seafood market was 21.12%, and this contribution reached as high as 61.3% in Shenyang. The comprehensive analysis showed that improved seafood market management, strengthened crowd control and information recording, industry-catered specifications, and well-trained employees have become urgently needed prevention strategies in different regions. The comprehensive analysis indicated that the niche model could be used to classify the epidemic risk and propose prevention and control strategies when combined with the assessment results of the jackknife test, thus providing a theoretical basis and information support for suppressing the spread of COVID-19 epidemics.
format	article
author	Ping He Yu Gao Longfei Guo Tongtong Huo Yuxin Li Xingren Zhang Yunfeng Li Cheng Peng Fanyun Meng
author_facet	Ping He Yu Gao Longfei Guo Tongtong Huo Yuxin Li Xingren Zhang Yunfeng Li Cheng Peng Fanyun Meng
author_sort	Ping He
title	Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model
title_short	Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model
title_full	Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model
title_fullStr	Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model
title_full_unstemmed	Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model
title_sort	evaluating the disaster risk of the covid-19 pandemic using an ecological niche model
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ec8b01a95f894883802427f9454075d6
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Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model

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