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Spatiotemporal spread pattern of the COVID-19 cases in China
The COVID-19 pandemic is currently spreading widely around the world, causing huge threats to public safety and global society. This study analyzes the spatiotemporal pattern of the COVID-19 pandemic in China, reveals China’s epicenters of the pandemic through spatial clustering, and delineates the...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775067/ https://www.ncbi.nlm.nih.gov/pubmed/33382758 http://dx.doi.org/10.1371/journal.pone.0244351 |
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author | Feng, Yongjiu Li, Qingmei Tong, Xiaohua Wang, Rong Zhai, Shuting Gao, Chen Lei, Zhenkun Chen, Shurui Zhou, Yilun Wang, Jiafeng Yan, Xiongfeng Xie, Huan Chen, Peng Liu, Shijie Xv, Xiong Liu, Sicong Jin, Yanmin Wang, Chao Hong, Zhonghua Luan, Kuifeng Wei, Chao Xu, Jinfu Jiang, Hua Xiao, Changjiang Guo, Yiyou |
author_facet | Feng, Yongjiu Li, Qingmei Tong, Xiaohua Wang, Rong Zhai, Shuting Gao, Chen Lei, Zhenkun Chen, Shurui Zhou, Yilun Wang, Jiafeng Yan, Xiongfeng Xie, Huan Chen, Peng Liu, Shijie Xv, Xiong Liu, Sicong Jin, Yanmin Wang, Chao Hong, Zhonghua Luan, Kuifeng Wei, Chao Xu, Jinfu Jiang, Hua Xiao, Changjiang Guo, Yiyou |
author_sort | Feng, Yongjiu |
collection | PubMed |
description | The COVID-19 pandemic is currently spreading widely around the world, causing huge threats to public safety and global society. This study analyzes the spatiotemporal pattern of the COVID-19 pandemic in China, reveals China’s epicenters of the pandemic through spatial clustering, and delineates the substantial effect of distance to Wuhan on the pandemic spread. The results show that the daily new COVID-19 cases mostly occurred in and around Wuhan before March 6, and then moved to the Grand Bay Area (Shenzhen, Hong Kong and Macau). The total COVID-19 cases in China were mainly distributed in the east of the Huhuanyong Line, where the epicenters accounted for more than 60% of the country’s total in/on 24 January and 7 February, half in/on 31 January, and more than 70% from 14 February. The total cases finally stabilized at approximately 84,000, and the inflection point for Wuhan was on 14 February, one week later than those of Hubei (outside Wuhan) and China (outside Hubei). The generalized additive model-based analysis shows that population density and distance to provincial cities were significantly associated with the total number of the cases, while distances to prefecture cities and intercity traffic stations, and population inflow from Wuhan after 24 January, had no strong relationships with the total number of cases. The results and findings should provide valuable insights for understanding the changes in the COVID-19 transmission as well as implications for controlling the global COVID-19 pandemic spread. |
format | Online Article Text |
id | pubmed-7775067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-77750672021-01-11 Spatiotemporal spread pattern of the COVID-19 cases in China Feng, Yongjiu Li, Qingmei Tong, Xiaohua Wang, Rong Zhai, Shuting Gao, Chen Lei, Zhenkun Chen, Shurui Zhou, Yilun Wang, Jiafeng Yan, Xiongfeng Xie, Huan Chen, Peng Liu, Shijie Xv, Xiong Liu, Sicong Jin, Yanmin Wang, Chao Hong, Zhonghua Luan, Kuifeng Wei, Chao Xu, Jinfu Jiang, Hua Xiao, Changjiang Guo, Yiyou PLoS One Research Article The COVID-19 pandemic is currently spreading widely around the world, causing huge threats to public safety and global society. This study analyzes the spatiotemporal pattern of the COVID-19 pandemic in China, reveals China’s epicenters of the pandemic through spatial clustering, and delineates the substantial effect of distance to Wuhan on the pandemic spread. The results show that the daily new COVID-19 cases mostly occurred in and around Wuhan before March 6, and then moved to the Grand Bay Area (Shenzhen, Hong Kong and Macau). The total COVID-19 cases in China were mainly distributed in the east of the Huhuanyong Line, where the epicenters accounted for more than 60% of the country’s total in/on 24 January and 7 February, half in/on 31 January, and more than 70% from 14 February. The total cases finally stabilized at approximately 84,000, and the inflection point for Wuhan was on 14 February, one week later than those of Hubei (outside Wuhan) and China (outside Hubei). The generalized additive model-based analysis shows that population density and distance to provincial cities were significantly associated with the total number of the cases, while distances to prefecture cities and intercity traffic stations, and population inflow from Wuhan after 24 January, had no strong relationships with the total number of cases. The results and findings should provide valuable insights for understanding the changes in the COVID-19 transmission as well as implications for controlling the global COVID-19 pandemic spread. Public Library of Science 2020-12-31 /pmc/articles/PMC7775067/ /pubmed/33382758 http://dx.doi.org/10.1371/journal.pone.0244351 Text en © 2020 Feng et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Feng, Yongjiu Li, Qingmei Tong, Xiaohua Wang, Rong Zhai, Shuting Gao, Chen Lei, Zhenkun Chen, Shurui Zhou, Yilun Wang, Jiafeng Yan, Xiongfeng Xie, Huan Chen, Peng Liu, Shijie Xv, Xiong Liu, Sicong Jin, Yanmin Wang, Chao Hong, Zhonghua Luan, Kuifeng Wei, Chao Xu, Jinfu Jiang, Hua Xiao, Changjiang Guo, Yiyou Spatiotemporal spread pattern of the COVID-19 cases in China |
title | Spatiotemporal spread pattern of the COVID-19 cases in China |
title_full | Spatiotemporal spread pattern of the COVID-19 cases in China |
title_fullStr | Spatiotemporal spread pattern of the COVID-19 cases in China |
title_full_unstemmed | Spatiotemporal spread pattern of the COVID-19 cases in China |
title_short | Spatiotemporal spread pattern of the COVID-19 cases in China |
title_sort | spatiotemporal spread pattern of the covid-19 cases in china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775067/ https://www.ncbi.nlm.nih.gov/pubmed/33382758 http://dx.doi.org/10.1371/journal.pone.0244351 |
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