Research article Special Issues

Extended SEIQR type model for COVID-19 epidemic and data analysis

  • Received: 09 August 2020 Accepted: 19 October 2020 Published: 02 November 2020
  • An extended SEIQR type model is considered in order to model the COVID-19 epidemic. It contains the classes of susceptible individuals, exposed, infected symptomatic and asymptomatic, quarantined, hospitalized and recovered. The basic reproduction number and the final size of epidemic are determined. The model is used to fit available data for some European countries. A more detailed model with two different subclasses of susceptible individuals is introduced in order to study the influence of social interaction on the disease progression. The coefficient of social interaction $K$ characterizes the level of social contacts in comparison with complete lockdown ($K = 0$) and the absence of lockdown ($K = 1$). The fitting of data shows that the actual level of this coefficient in some European countries is about 0.1, characterizing a slow disease progression. A slight increase of this value in the autumn can lead to a strong epidemic burst.

    Citation: Swarnali Sharma, Vitaly Volpert, Malay Banerjee. Extended SEIQR type model for COVID-19 epidemic and data analysis[J]. Mathematical Biosciences and Engineering, 2020, 17(6): 7562-7604. doi: 10.3934/mbe.2020386

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  • An extended SEIQR type model is considered in order to model the COVID-19 epidemic. It contains the classes of susceptible individuals, exposed, infected symptomatic and asymptomatic, quarantined, hospitalized and recovered. The basic reproduction number and the final size of epidemic are determined. The model is used to fit available data for some European countries. A more detailed model with two different subclasses of susceptible individuals is introduced in order to study the influence of social interaction on the disease progression. The coefficient of social interaction $K$ characterizes the level of social contacts in comparison with complete lockdown ($K = 0$) and the absence of lockdown ($K = 1$). The fitting of data shows that the actual level of this coefficient in some European countries is about 0.1, characterizing a slow disease progression. A slight increase of this value in the autumn can lead to a strong epidemic burst.


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