Open AccessExtended SEIQR type model for COVID-19 epidemic and data analysis
Author(s) -
Swarnali Sharma,
Vitaly Volpert,
Malay Banerjee
Publication year - 2017
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2020386
Subject(s) - epidemic model , covid-19 , basic reproduction number , statistics , type (biology) , demography , econometrics , asymptomatic , order (exchange) , mathematics , disease , biology , medicine , sociology , economics , infectious disease (medical specialty) , ecology , population , finance , pathology
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.