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Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope

OBJECTIVES: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. METHODS: We collected publicly available COVID-19 epidemiological data from 436 Chinese...

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Autores principales: Zhang, Lei, Tao, Yusha, Wang, Jing, Ong, Jason J., Tang, Weiming, Zou, Maosheng, Bai, Lu, Ding, Miao, Shen, Mingwang, Zhuang, Guihua, Fairley, Christopher K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266579/
https://www.ncbi.nlm.nih.gov/pubmed/32502662
http://dx.doi.org/10.1016/j.ijid.2020.05.122
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author Zhang, Lei
Tao, Yusha
Wang, Jing
Ong, Jason J.
Tang, Weiming
Zou, Maosheng
Bai, Lu
Ding, Miao
Shen, Mingwang
Zhuang, Guihua
Fairley, Christopher K.
author_facet Zhang, Lei
Tao, Yusha
Wang, Jing
Ong, Jason J.
Tang, Weiming
Zou, Maosheng
Bai, Lu
Ding, Miao
Shen, Mingwang
Zhuang, Guihua
Fairley, Christopher K.
author_sort Zhang, Lei
collection PubMed
description OBJECTIVES: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. METHODS: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January–15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. RESULTS: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6–6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3–7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2–1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. CONCLUSIONS: Early epidemic characteristics are important indicators for the size of the entire epidemic.
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spelling pubmed-72665792020-06-03 Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope Zhang, Lei Tao, Yusha Wang, Jing Ong, Jason J. Tang, Weiming Zou, Maosheng Bai, Lu Ding, Miao Shen, Mingwang Zhuang, Guihua Fairley, Christopher K. Int J Infect Dis Article OBJECTIVES: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. METHODS: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January–15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. RESULTS: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6–6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3–7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2–1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. CONCLUSIONS: Early epidemic characteristics are important indicators for the size of the entire epidemic. The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2020-08 2020-06-02 /pmc/articles/PMC7266579/ /pubmed/32502662 http://dx.doi.org/10.1016/j.ijid.2020.05.122 Text en © 2020 The Author(s) 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
Zhang, Lei
Tao, Yusha
Wang, Jing
Ong, Jason J.
Tang, Weiming
Zou, Maosheng
Bai, Lu
Ding, Miao
Shen, Mingwang
Zhuang, Guihua
Fairley, Christopher K.
Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope
title Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope
title_full Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope
title_fullStr Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope
title_full_unstemmed Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope
title_short Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope
title_sort early characteristics of the covid-19 outbreak predict the subsequent epidemic scope
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266579/
https://www.ncbi.nlm.nih.gov/pubmed/32502662
http://dx.doi.org/10.1016/j.ijid.2020.05.122
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