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A dynamic modeling study on the effects of Wuhan traffic control and centralized quarantine measures on COVID-19 epidemic. (Special Issue: Spatio-temporal dynamics analysis, risk assessment and emergency management for COVID-19 epidemic.) [Chinese]
Journal of Shandong University ; 58(10):25-31, 2020.
Article Dans Chinois | GIM | ID: covidwho-1975286
ABSTRACT

Objective:

To quantitatively evaluate the effects of traffic control and centralized quarantine measures on COVID-19 epidemic in Wuhan, so as to provide scientific basis for epidemic prevention and control. Methods The SEIAHR model was established based on SEIR dynamic model, which took into account the characteristics of asymptomatic carriers and unconfirmed quarantined patients. Based on the timing of prevention measures, the epidemic was divided into three stages, the parameters were fitted, the basic reproduction numbers of different stages were calculated, and the development trend of epidemic was predicted. Results The R0 decreased dramatically. The R0 of the three stages were 3.684 1(95%CI 3.106 1-4.048 0), 2.178 8(95%CI 1.725 8-3.577 6)and 0.362 5(95%CI 0.349 9-0.367 6), respectively. Due to the traffic control travel and centralized quarantine, the peak of the disease moved forward from April 19 to March 14, 2020. The scale of the epidemic had also been reduced by prevention and control measures. Conclusion The traffic control and centralized quarantine measures implemented in Wuhan were effective for the epidemic control, which can provide reference for other countries.
Mots clés

Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: GIM Type d'étude: Études expérimentales / Étude pronostique langue: Chinois Revue: Journal of Shandong University Année: 2020 Type de document: Article

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Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: GIM Type d'étude: Études expérimentales / Étude pronostique langue: Chinois Revue: Journal of Shandong University Année: 2020 Type de document: Article