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About:
Estimation of the epidemic properties of the 2019 novel coronavirus: A mathematical modeling study
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Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
title
Estimation of the epidemic properties of the 2019 novel coronavirus: A mathematical modeling study
Creator
Peng, Liping
Du, Zhicheng
Hao, Chun
Dong, Roman
Gilmour Phd, Stuart
Gilmour, Stuart
Gu Phd, Jing
Hao Phd, Yuantao
Li, Jinghua
Mmed, Ying
Wang, Mengying
Wang, Yijing
Xu,
Yoneoka, Daisuke
You, Xinyi
source
MedRxiv
abstract
Background The 2019 novel Coronavirus (COVID-19) emerged in Wuhan, China in December 2019 and has been spreading rapidly in China. Decisions about its pandemic threat and the appropriate level of public health response depend heavily on estimates of its basic reproduction number and assessments of interventions conducted in the early stages of the epidemic. Methods We conducted a mathematical modeling study using five independent methods to assess the basic reproduction number (R0) of COVID-19, using data on confirmed cases obtained from the China National Health Commission for the period 10th January to 8th February. We analyzed the data for the period before the closure of Wuhan city (10th January to 23rd January) and the post-closure period (23rd January to 8th February) and for the whole period, to assess both the epidemic risk of the virus and the effectiveness of the closure of Wuhan city on spread of COVID-19. Findings Before the closure of Wuhan city the basic reproduction number of COVID-19 was 4.38 (95% CI: 3.63-5.13), dropping to 3.41 (95% CI: 3.16-3.65) after the closure of Wuhan city. Over the entire epidemic period COVID-19 had a basic reproduction number of 3.39 (95% CI: 3.09-3.70), indicating it has a very high transmissibility. Interpretation COVID-19 is a highly transmissible virus with a very high risk of epidemic outbreak once it emerges in metropolitan areas. The closure of Wuhan city was effective in reducing the severity of the epidemic, but even after closure of the city and the subsequent expansion of that closure to other parts of Hubei the virus remained extremely infectious. Emergency planners in other cities should consider this high infectiousness when considering responses to this virus.
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2020-02-20
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bibo:doi
10.1101/2020.02.18.20024315
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medrxiv
sha1sum (hex)
36521caf90f471c9da1a4e84f8562440d73ead9a
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https://doi.org/10.1101/2020.02.18.20024315
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Estimation of the epidemic properties of the 2019 novel coronavirus: A mathematical modeling study
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covid:36521caf90f471c9da1a4e84f8562440d73ead9a#body_text
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schema:about
of
named entity 'PROPERTIES'
named entity 'ESTIMATION'
named entity '2019'
named entity 'emerged'
named entity 'conducted'
named entity '2019 NOVEL CORONAVIRUS'
named entity 'EPIDEMIC'
named entity 'APPROPRIATE'
named entity 'LEVEL'
named entity 'CHINA'
named entity 'BASIC REPRODUCTION NUMBER'
named entity 'EPIDEMIC'
named entity 'ESTIMATES'
named entity '2019 NOVEL CORONAVIRUS'
named entity 'DECEMBER'
named entity 'EARLY STAGES'
named entity 'MATHEMATICAL MODELING'
named entity 'STUDY'
named entity 'RESPONSE'
named entity 'SPREADING'
named entity 'ASSESSMENTS'
named entity 'PANDEMIC'
named entity 'ABOUT'
named entity 'RAPIDLY'
named entity '2019'
named entity 'ITS'
named entity 'WUHAN'
named entity 'INTERVENTIONS'
named entity 'PUBLIC HEALTH'
named entity 'DEPEND'
named entity 'DECISIONS'
named entity 'THREAT'
named entity 'early stages'
named entity 'public health'
named entity 'Wuhan'
named entity 'basic reproduction number'
named entity 'fitting model'
named entity 'analytic expression'
named entity 'SIR model'
named entity 'epidemic'
named entity 'Wuhan'
named entity 'basic reproduction number'
named entity 'epidemic'
named entity '95% CI'
named entity 'basic reproduction number'
named entity 'Euler equation'
named entity 'standardized testing'
named entity 'Monte Carlo'
named entity 'basic reproduction number'
named entity 'coronavirus'
named entity 'China'
named entity 'COVID-19'
named entity 'basic reproduction number'
named entity 'virus'
named entity 'exponential growth'
named entity 'Exponential growth'
named entity 'virus'
named entity 'global pandemic'
named entity 'single case'
named entity 'epidemic'
named entity 'COVID-19'
named entity 'Hubei'
named entity 'Hubei province'
named entity 'Bayesian Method'
named entity 'nCoV'
named entity 'coronavirus'
named entity 'basic reproduction number'
named entity 'mumps'
named entity 'basic reproduction number'
named entity 'SEIR'
named entity 'mathematical modeling'
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