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


Journal

Mathematical biosciences and engineering : MBE
ISSN: 1551-0018
Titre abrégé: Math Biosci Eng
Pays: United States
ID NLM: 101197794

Informations de publication

Date de publication:
02 11 2020
Historique:
entrez: 31 12 2020
pubmed: 1 1 2021
medline: 16 1 2021
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 33378910
doi: 10.3934/mbe.2020386
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

7562-7604

Auteurs

Swarnali Sharma (S)

Department of Mathematics, Vijaygarh Jyotish Ray College, Kolkata - 700032, India.

Vitaly Volpert (V)

Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622 Villeurbanne, France.
INRIA Team Dracula, INRIA Lyon La Doua, 69603 Villeurbanne, France.
Peoples Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation.

Malay Banerjee (M)

Department of Mathematics & Statistics, IIT Kanpur, Kanpur - 208016, India.

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Classifications MeSH