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Impact of population movement on the spread of 2019-nCoV in China
Since Dec 2019, China has experienced an outbreak caused by a novel coronavirus, 2019-nCoV. A travel ban was implemented for Wuhan, Hubei on Jan 23 to slow down the outbreak. We found a significant positive correlation between population influx from Wuhan and confirmed cases in other cities across C...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269026/ https://www.ncbi.nlm.nih.gov/pubmed/32321369 http://dx.doi.org/10.1080/22221751.2020.1760143 |
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author | Zhang, Chi Chen, Cai Shen, Wei Tang, Feng Lei, Hao Xie, Yu Cao, Zicheng Tang, Kang Bai, Junbo Xiao, Lehan Xu, Yutian Song, Yanxin Chen, Jiwei Guo, Zhihui Guo, Yichen Wang, Xiao Xu, Modi Zou, Huachun Shu, Yuelong Du, Xiangjun |
author_facet | Zhang, Chi Chen, Cai Shen, Wei Tang, Feng Lei, Hao Xie, Yu Cao, Zicheng Tang, Kang Bai, Junbo Xiao, Lehan Xu, Yutian Song, Yanxin Chen, Jiwei Guo, Zhihui Guo, Yichen Wang, Xiao Xu, Modi Zou, Huachun Shu, Yuelong Du, Xiangjun |
author_sort | Zhang, Chi |
collection | PubMed |
description | Since Dec 2019, China has experienced an outbreak caused by a novel coronavirus, 2019-nCoV. A travel ban was implemented for Wuhan, Hubei on Jan 23 to slow down the outbreak. We found a significant positive correlation between population influx from Wuhan and confirmed cases in other cities across China (R(2) = 0.85, P < 0.001), especially cities in Hubei (R(2) = 0.88, P < 0.001). Removing the travel restriction would have increased 118% (91%–172%) of the overall cases for the coming week, and a travel ban taken three days or a week earlier would have reduced 47% (26%–58%) and 83% (78%–89%) of the early cases. We would expect a 61% (48%–92%) increase of overall cumulative cases without any restrictions on returning residents, and 11% (8%–16%) increase if the travel ban stays in place for Hubei. Cities from Yangtze River Delta, Pearl River Delta, and Capital Economic Circle regions are at higher risk. |
format | Online Article Text |
id | pubmed-7269026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-72690262020-06-11 Impact of population movement on the spread of 2019-nCoV in China Zhang, Chi Chen, Cai Shen, Wei Tang, Feng Lei, Hao Xie, Yu Cao, Zicheng Tang, Kang Bai, Junbo Xiao, Lehan Xu, Yutian Song, Yanxin Chen, Jiwei Guo, Zhihui Guo, Yichen Wang, Xiao Xu, Modi Zou, Huachun Shu, Yuelong Du, Xiangjun Emerg Microbes Infect Letter Since Dec 2019, China has experienced an outbreak caused by a novel coronavirus, 2019-nCoV. A travel ban was implemented for Wuhan, Hubei on Jan 23 to slow down the outbreak. We found a significant positive correlation between population influx from Wuhan and confirmed cases in other cities across China (R(2) = 0.85, P < 0.001), especially cities in Hubei (R(2) = 0.88, P < 0.001). Removing the travel restriction would have increased 118% (91%–172%) of the overall cases for the coming week, and a travel ban taken three days or a week earlier would have reduced 47% (26%–58%) and 83% (78%–89%) of the early cases. We would expect a 61% (48%–92%) increase of overall cumulative cases without any restrictions on returning residents, and 11% (8%–16%) increase if the travel ban stays in place for Hubei. Cities from Yangtze River Delta, Pearl River Delta, and Capital Economic Circle regions are at higher risk. Taylor & Francis 2020-05-18 /pmc/articles/PMC7269026/ /pubmed/32321369 http://dx.doi.org/10.1080/22221751.2020.1760143 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd https://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/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Letter Zhang, Chi Chen, Cai Shen, Wei Tang, Feng Lei, Hao Xie, Yu Cao, Zicheng Tang, Kang Bai, Junbo Xiao, Lehan Xu, Yutian Song, Yanxin Chen, Jiwei Guo, Zhihui Guo, Yichen Wang, Xiao Xu, Modi Zou, Huachun Shu, Yuelong Du, Xiangjun Impact of population movement on the spread of 2019-nCoV in China |
title | Impact of population movement on the spread of 2019-nCoV in China |
title_full | Impact of population movement on the spread of 2019-nCoV in China |
title_fullStr | Impact of population movement on the spread of 2019-nCoV in China |
title_full_unstemmed | Impact of population movement on the spread of 2019-nCoV in China |
title_short | Impact of population movement on the spread of 2019-nCoV in China |
title_sort | impact of population movement on the spread of 2019-ncov in china |
topic | Letter |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269026/ https://www.ncbi.nlm.nih.gov/pubmed/32321369 http://dx.doi.org/10.1080/22221751.2020.1760143 |
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