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Early forecasting of the potential risk zones of COVID-19 in China's megacities
Recently, the coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Early and quick identification of the potential risk zones of COVID-19 infection is increasingly vital for the megacities implementing targeted infection prevention and control measures. In this study, the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7252152/ https://www.ncbi.nlm.nih.gov/pubmed/32353723 http://dx.doi.org/10.1016/j.scitotenv.2020.138995 |
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author | Ren, Hongyan Zhao, Lu Zhang, An Song, Liuyi Liao, Yilan Lu, Weili Cui, Cheng |
author_facet | Ren, Hongyan Zhao, Lu Zhang, An Song, Liuyi Liao, Yilan Lu, Weili Cui, Cheng |
author_sort | Ren, Hongyan |
collection | PubMed |
description | Recently, the coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Early and quick identification of the potential risk zones of COVID-19 infection is increasingly vital for the megacities implementing targeted infection prevention and control measures. In this study, the communities with confirmed cases during January 21–February 27 were collected and considered as the specific epidemic data for Beijing, Guangzhou, and Shenzhen. We evaluated the spatiotemporal variations of the epidemics before utilizing the ecological niche models (ENM) to assemble the epidemic data and nine socioeconomic variables for identifying the potential risk zones of this infection in these megacities. Three megacities were differentiated by the spatial patterns and quantities of infected communities, average cases per community, the percentages of imported cases, as well as the potential risks, although their COVID-19 infection situations have been preliminarily contained to date. With higher risks that were predominated by various influencing factors in each megacity, the potential risk zones coverd about 75% to 100% of currently infected communities. Our results demonstrate that the ENM method was capable of being employed as an early forecasting tool for identifying the potential COVID-19 infection risk zones on a fine scale. We suggest that local hygienic authorities should keep their eyes on the epidemic in each megacity for sufficiently implementing and adjusting their interventions in the zones with more residents or probably crowded places. This study would provide useful clues for relevant hygienic departments making quick responses to increasingly severe epidemics in similar megacities in the world. |
format | Online Article Text |
id | pubmed-7252152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72521522020-05-28 Early forecasting of the potential risk zones of COVID-19 in China's megacities Ren, Hongyan Zhao, Lu Zhang, An Song, Liuyi Liao, Yilan Lu, Weili Cui, Cheng Sci Total Environ Article Recently, the coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Early and quick identification of the potential risk zones of COVID-19 infection is increasingly vital for the megacities implementing targeted infection prevention and control measures. In this study, the communities with confirmed cases during January 21–February 27 were collected and considered as the specific epidemic data for Beijing, Guangzhou, and Shenzhen. We evaluated the spatiotemporal variations of the epidemics before utilizing the ecological niche models (ENM) to assemble the epidemic data and nine socioeconomic variables for identifying the potential risk zones of this infection in these megacities. Three megacities were differentiated by the spatial patterns and quantities of infected communities, average cases per community, the percentages of imported cases, as well as the potential risks, although their COVID-19 infection situations have been preliminarily contained to date. With higher risks that were predominated by various influencing factors in each megacity, the potential risk zones coverd about 75% to 100% of currently infected communities. Our results demonstrate that the ENM method was capable of being employed as an early forecasting tool for identifying the potential COVID-19 infection risk zones on a fine scale. We suggest that local hygienic authorities should keep their eyes on the epidemic in each megacity for sufficiently implementing and adjusting their interventions in the zones with more residents or probably crowded places. This study would provide useful clues for relevant hygienic departments making quick responses to increasingly severe epidemics in similar megacities in the world. Elsevier B.V. 2020-08-10 2020-04-26 /pmc/articles/PMC7252152/ /pubmed/32353723 http://dx.doi.org/10.1016/j.scitotenv.2020.138995 Text en © 2020 Elsevier B.V. All rights reserved. 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 Ren, Hongyan Zhao, Lu Zhang, An Song, Liuyi Liao, Yilan Lu, Weili Cui, Cheng Early forecasting of the potential risk zones of COVID-19 in China's megacities |
title | Early forecasting of the potential risk zones of COVID-19 in China's megacities |
title_full | Early forecasting of the potential risk zones of COVID-19 in China's megacities |
title_fullStr | Early forecasting of the potential risk zones of COVID-19 in China's megacities |
title_full_unstemmed | Early forecasting of the potential risk zones of COVID-19 in China's megacities |
title_short | Early forecasting of the potential risk zones of COVID-19 in China's megacities |
title_sort | early forecasting of the potential risk zones of covid-19 in china's megacities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7252152/ https://www.ncbi.nlm.nih.gov/pubmed/32353723 http://dx.doi.org/10.1016/j.scitotenv.2020.138995 |
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