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Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China / 中华流行病学杂志
Chinese Journal of Epidemiology ; (12): 466-469, 2020.
Article en Zh | WPRIM | ID: wpr-811645
Biblioteca responsable: WPRO
ABSTRACT
Objective@#To evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision- making departments.@*Methods@#Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number R0(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time.@*Results@#For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the R0(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, R0(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the R0(t)s less than 1. The results could be used for the decision making to free population floating conditionally.@* Conclusions@#Dynamic R0(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future.
Palabras clave
Texto completo: 1 Base de datos: WPRIM Tipo de estudio: Prognostic_studies Idioma: Zh Revista: Chinese Journal of Epidemiology Año: 2020 Tipo del documento: Article
Texto completo: 1 Base de datos: WPRIM Tipo de estudio: Prognostic_studies Idioma: Zh Revista: Chinese Journal of Epidemiology Año: 2020 Tipo del documento: Article