CovidV1, an2020, Analysis, bibRecord, 000021

[Study on assessing early epidemiological parameters of coronavirus disease epidemic in China].

Identifieur interne : 000021 ( an2020/Analysis ); précédent : 000020; suivant : 000022

[Study on assessing early epidemiological parameters of coronavirus disease epidemic in China].

Auteurs : Q Q Song [République populaire de Chine] ; H. Zhao [République populaire de Chine] ; L Q Fang [République populaire de Chine] ; W. Liu [République populaire de Chine] ; C. Zheng [République populaire de Chine] ; Y. Zhang [République populaire de Chine]

Source :

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi [ 0254-6450 ] ; 2020.

RBID : pubmed:32113196

Abstract

Objective: To study the early dynamics of the epidemic of coronavirus disease (COVID-19) in China from 15 to 31 January, 2020, and estimate the corresponding epidemiological parameters (incubation period, generation interval and basic reproduction number) of the epidemic. Methods: By means of Weibull, Gamma and Lognormal distributions methods, we estimated the probability distribution of the incubation period and generation interval data obtained from the reported COVID-19 cases. Moreover, the AIC criterion was used to determine the optimal distribution. Considering the epidemic is ongoing, the exponential growth model was used to fit the incidence data of COVID-19 from 10 to 31 January, 2020, and exponential growth method, maximum likelihood method and SEIR model were used to estimate the basic reproduction number. Results: Early COVID-19 cases kept an increase in exponential growth manner before 26 January, 2020, then the increase trend became slower. The average incubation period was 5.01 (95%CI: 4.31-5.69) days; the average generation interval was 6.03 (95%CI: 5.20-6.91) days. The basic reproduction number was estimated to be 3.74 (95%CI: 3.63-3.87), 3.16 (95%CI: 2.90-3.43), and 3.91 (95%CI: 3.71-4.11) by three methods, respectively. Conclusions: The Gamma distribution fits both the generation interval and incubation period best, and the mean value of generation interval is 1.02 day longer than that of incubation period. The relatively high basic reproduction number indicates that the epidemic is still serious; Based on our analysis, the turning point of the epidemic would be seen on 26 January, the growth rate would be lower afterwards.

DOI: 10.3760/cma.j.cn112338-20200205-00069
PubMed: 32113196

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pubmed:32113196

Le document en format XML

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<front><div type="abstract" xml:lang="en"><b>Objective:</b>
 To study the early dynamics of the epidemic of coronavirus disease (COVID-19) in China from 15 to 31 January, 2020, and estimate the corresponding epidemiological parameters (incubation period, generation interval and basic reproduction number) of the epidemic. <b>Methods:</b>
 By means of Weibull, Gamma and Lognormal distributions methods, we estimated the probability distribution of the incubation period and generation interval data obtained from the reported COVID-19 cases. Moreover, the AIC criterion was used to determine the optimal distribution. Considering the epidemic is ongoing, the exponential growth model was used to fit the incidence data of COVID-19 from 10 to 31 January, 2020, and exponential growth method, maximum likelihood method and SEIR model were used to estimate the basic reproduction number. <b>Results:</b>
 Early COVID-19 cases kept an increase in exponential growth manner before 26 January, 2020, then the increase trend became slower. The average incubation period was 5.01 (95%<i>CI</i>
: 4.31-5.69) days; the average generation interval was 6.03 (95%<i>CI</i>
: 5.20-6.91) days. The basic reproduction number was estimated to be 3.74 (95%<i>CI</i>
: 3.63-3.87), 3.16 (95%<i>CI</i>
: 2.90-3.43), and 3.91 (95%<i>CI</i>
: 3.71-4.11) by three methods, respectively. <b>Conclusions:</b>
 The Gamma distribution fits both the generation interval and incubation period best, and the mean value of generation interval is 1.02 day longer than that of incubation period. The relatively high basic reproduction number indicates that the epidemic is still serious; Based on our analysis, the turning point of the epidemic would be seen on 26 January, the growth rate would be lower afterwards.</div>
</front>
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<name sortKey="Liu, W" sort="Liu, W" uniqKey="Liu W" first="W" last="Liu">W. Liu</name>
<name sortKey="Zhang, Y" sort="Zhang, Y" uniqKey="Zhang Y" first="Y" last="Zhang">Y. Zhang</name>
<name sortKey="Zhao, H" sort="Zhao, H" uniqKey="Zhao H" first="H" last="Zhao">H. Zhao</name>
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[Study on assessing early epidemiological parameters of coronavirus disease epidemic in China].

[Study on assessing early epidemiological parameters of coronavirus disease epidemic in China].

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