Subject: COVID-19, Epidemic spreading, Complex networks, Eigenvector centrality, SEAIR epidemic model Jacobian matrix eigenvectors
Year: 2021
Type: Article
Title: SEAIR Epidemic spreading model of COVID-19
Author: Basnarkov, Lasko
Abstract: We study Susceptible-Exposed-Asymptomatic-Infectious-Recovered (SEAIR) epidemic spreading model of COVID-19. It captures two important characteristics of the infectiousness of COVID-19: delayed start and its appearance before onset of symptoms, or even with total absence of them. The model is theoretically analyzed in continuous-time compartmental version and discrete-time version on random regular graphs and complex networks. We show analytically that there are relationships between the epidemic thresholds and the equations for the susceptible populations at the endemic equilibrium in all three versions, which hold when the epidemic is weak. We provide theoretical arguments that eigenvector centrality of a node approximately determines its risk to become infected.
Publisher: Pergamon
Relation: Chaos, Solitons & Fractals
Identifier: oai:repository.ukim.mk:20.500.12188/22953
Identifier: http://hdl.handle.net/20.500.12188/22953
