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The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic
BACKGROUND: Evaluating whether an infectious disease has reached a turning point is important for planning additional intervention efforts. This study aimed to analyze the changing patterns and the tempogeographic features of the coronavirus disease 2019 (COVID-19) epidemic in China, to provide furt...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184457/ https://www.ncbi.nlm.nih.gov/pubmed/32296826 http://dx.doi.org/10.1093/cid/ciaa423 |
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author | Tang, Weiming Liao, Huipeng Marley, Gifty Wang, Zaisheng Cheng, Weibin Wu, Dan Yu, Rongbinand |
author_facet | Tang, Weiming Liao, Huipeng Marley, Gifty Wang, Zaisheng Cheng, Weibin Wu, Dan Yu, Rongbinand |
author_sort | Tang, Weiming |
collection | PubMed |
description | BACKGROUND: Evaluating whether an infectious disease has reached a turning point is important for planning additional intervention efforts. This study aimed to analyze the changing patterns and the tempogeographic features of the coronavirus disease 2019 (COVID-19) epidemic in China, to provide further evidence for real-time responses. METHODS: Daily data on COVID-19 cases between 31 December 2019 and 26 February 2020 were collected and analyzed for Hubei and non-Hubei regions in China. Observed trends for new and cumulative cases were analyzed through joinpoint regression analysis. Spatial analysis was applied to show the geographic distribution and changing patterns of the epidemic. RESULTS: By 26 February 2020, 78 630 confirmed COVID-19 cases had been reported in China. In Hubei, an increasing trend (slope = 221) was observed for new cases between 24 January and 7 February 2020, after which a decline commenced (slope = −868). However, as the diagnosis criteria changed, a sudden increase (slope = 5530) was observed on 12 February, which sharply decreased afterward (slope = −4898). In non-Hubei regions, the number of new cases increased from 20 January to 3 February and started to decline afterward (slope = −53). The spatial analysis identified Chongqing, Guangzhou, Shenzhen, Changsha, Nanchang, Wenzhou, Shanghai, Xinyang, Jining, and Beijing as the hotspots outside of Hubei Province in China. CONCLUSIONS: The joinpoint regression analysis indicated that the epidemic might be under control in China, especially for regions outside of Hubei Province. Further improvement in the response strategies based on these new patterns is needed. |
format | Online Article Text |
id | pubmed-7184457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-71844572020-04-29 The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic Tang, Weiming Liao, Huipeng Marley, Gifty Wang, Zaisheng Cheng, Weibin Wu, Dan Yu, Rongbinand Clin Infect Dis Articles and Commentaries BACKGROUND: Evaluating whether an infectious disease has reached a turning point is important for planning additional intervention efforts. This study aimed to analyze the changing patterns and the tempogeographic features of the coronavirus disease 2019 (COVID-19) epidemic in China, to provide further evidence for real-time responses. METHODS: Daily data on COVID-19 cases between 31 December 2019 and 26 February 2020 were collected and analyzed for Hubei and non-Hubei regions in China. Observed trends for new and cumulative cases were analyzed through joinpoint regression analysis. Spatial analysis was applied to show the geographic distribution and changing patterns of the epidemic. RESULTS: By 26 February 2020, 78 630 confirmed COVID-19 cases had been reported in China. In Hubei, an increasing trend (slope = 221) was observed for new cases between 24 January and 7 February 2020, after which a decline commenced (slope = −868). However, as the diagnosis criteria changed, a sudden increase (slope = 5530) was observed on 12 February, which sharply decreased afterward (slope = −4898). In non-Hubei regions, the number of new cases increased from 20 January to 3 February and started to decline afterward (slope = −53). The spatial analysis identified Chongqing, Guangzhou, Shenzhen, Changsha, Nanchang, Wenzhou, Shanghai, Xinyang, Jining, and Beijing as the hotspots outside of Hubei Province in China. CONCLUSIONS: The joinpoint regression analysis indicated that the epidemic might be under control in China, especially for regions outside of Hubei Province. Further improvement in the response strategies based on these new patterns is needed. Oxford University Press 2020-08-01 2020-04-15 /pmc/articles/PMC7184457/ /pubmed/32296826 http://dx.doi.org/10.1093/cid/ciaa423 Text en © The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com. https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) |
spellingShingle | Articles and Commentaries Tang, Weiming Liao, Huipeng Marley, Gifty Wang, Zaisheng Cheng, Weibin Wu, Dan Yu, Rongbinand The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic |
title | The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic |
title_full | The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic |
title_fullStr | The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic |
title_full_unstemmed | The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic |
title_short | The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic |
title_sort | changing patterns of coronavirus disease 2019 (covid-19) in china: a tempogeographic analysis of the severe acute respiratory syndrome coronavirus 2 epidemic |
topic | Articles and Commentaries |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184457/ https://www.ncbi.nlm.nih.gov/pubmed/32296826 http://dx.doi.org/10.1093/cid/ciaa423 |
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