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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...

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Autores principales: Tang, Weiming, Liao, Huipeng, Marley, Gifty, Wang, Zaisheng, Cheng, Weibin, Wu, Dan, Yu, Rongbinand
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
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.
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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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