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SEIR modeling of the COVID-19 and its dynamics

He, Shaobo ; Peng, Yuexi ; Sun, Kehui

Nonlinear dynamics, 2020, Vol.101 (3), p.1667-1680 [Periódico revisado por pares]

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Título:
SEIR modeling of the COVID-19 and its dynamics
Autor: He, Shaobo ; Peng, Yuexi ; Sun, Kehui
Assuntos: Automotive Engineering ; Classical Mechanics ; Control ; Dynamical Systems ; Engineering ; Mechanical Engineering ; Original Paper ; Vibration
É parte de: Nonlinear dynamics, 2020, Vol.101 (3), p.1667-1680
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: In this paper, a SEIR epidemic model for the COVID-19 is built according to some general control strategies, such as hospital, quarantine and external input. Based on the data of Hubei province, the particle swarm optimization (PSO) algorithm is applied to estimate the parameters of the system. We found that the parameters of the proposed SEIR model are different for different scenarios. Then, the model is employed to show the evolution of the epidemic in Hubei province, which shows that it can be used to forecast COVID-19 epidemic situation. Moreover, by introducing the seasonality and stochastic infection the parameters, nonlinear dynamics including chaos are found in the system. Finally, we discussed the control strategies of the COVID-19 based on the structure and parameters of the proposed model.
Editor: Dordrecht: Springer Netherlands
Idioma: Inglês

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