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About:
Estimation of the time-varying reproduction number of COVID-19 outbreak in China
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wasabi.inria.fr
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research paper
schema:ScholarlyArticle
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
title
Estimation of the time-varying reproduction number of COVID-19 outbreak in China
Creator
Zhang, Yuan
Zhou, Feng
Zhou, Z
Chen, Y
Hu, Y
Lin, J
Lin, Qiushi
Zhang, F
Zhou, Q
Hu, Wenjie
Sun, Jiarui
You, Chong
Zhou, Xiao-Hua
Chen, Zhengchao
Deng, Yuhao
Pang, Cheng
Deng, C
Pang, Heng
source
Elsevier; Medline; PMC
abstract
BACKGROUND: The 2019 novel coronavirus (COVID-19) outbreak in Wuhan, China has attracted world-wide attention. As of March 31, 2020, a total of 82,631 cases of COVID-19 in China were confirmed by the National Health Commission (NHC) of China. METHODS: Three approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers. RESULTS: A total of 198 chains of transmission together with dates of symptoms onset and 139 dates of infections were identified among 14,829 confirmed cases outside Hubei Province as reported as of March 31, 2020. Based on this information, we found that the serial interval had an average of 4.60 days with a standard deviation of 5.55 days, the incubation period had an average of 8.00 days with a standard deviation of 4.75 days and the infectious period had an average of 13.96 days with a standard deviation of 5.20 days. The estimated controlled reproduction numbers, [Formula: see text] , produced by all three methods in all analyzed regions of China are significantly smaller compared with the basic reproduction numbers [Formula: see text]. CONCLUSIONS: The controlled reproduction number in China is much lower than one in all regions of China by now. It fell below one within 30 days from the implementations of unprecedent containment measures, which indicates that the strong measures taken by China government was effective to contain the epidemic. Nonetheless, efforts are still needed in order to end the current epidemic as imported cases from overseas pose a high risk of a second outbreak.
has issue date
2020-05-11
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xsd:dateTime
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bibo:doi
10.1016/j.ijheh.2020.113555
bibo:pmid
32460229
has license
no-cc
sha1sum (hex)
b5d475f0a67034f1bd432df91907ef606801be48
schema:url
https://doi.org/10.1016/j.ijheh.2020.113555
resource representing a document's title
Estimation of the time-varying reproduction number of COVID-19 outbreak in China
has PubMed Central identifier
PMC7211652
has PubMed identifier
32460229
schema:publication
Int J Hyg Environ Health
resource representing a document's body
covid:b5d475f0a67034f1bd432df91907ef606801be48#body_text
is
schema:about
of
named entity 'China'
named entity 'Hygiene'
named entity 'Environmental Health'
named entity 'WORLD'
named entity 'CASES'
named entity 'China'
named entity 'China'
named entity 'NHC'
named entity 'COVID-19'
named entity 'China'
named entity 'reproduction number'
named entity 'epidemic'
named entity 'grows exponentially'
named entity 'genome sequencing'
named entity 'metapopulation'
named entity 'basic reproduction number'
named entity 'incubation period'
named entity 'pathogen'
named entity 'epidemic'
named entity 'quarantine'
named entity 'January 30'
named entity 'COVID'
named entity 'epidemic'
named entity 'China'
named entity 'respiratory droplets'
named entity 'pathogens'
named entity 'incubation period'
named entity 'Chinese government'
named entity 'generation time'
named entity 'COVID'
named entity 'China'
named entity 'reproduction number'
named entity 'reproduction number'
named entity 'serial interval'
named entity 'China'
named entity 'coronavirus'
named entity 'China'
named entity 'grow exponentially'
named entity 'nucleic acid'
named entity 'coronavirus'
named entity 'serial interval'
named entity 'infection'
named entity 'Poisson distribution'
named entity 'Hubei'
named entity 'infection'
named entity 'probability'
named entity 'basic reproduction number'
named entity 'reproduction number'
named entity 'COVID'
named entity 'IF2'
named entity 'serial interval'
named entity 'reproduction number'
named entity 'February 12'
named entity 'serial interval'
named entity 'log-scale'
named entity 'likelihood function'
named entity 'reproduction number'
named entity 'serial interval'
named entity 'serial interval'
named entity 'Hubei'
named entity 'Hubei'
named entity 'COVID-19'
named entity '95% confidence interval'
named entity 'standard deviation'
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