SEAIR Epidemic spreading model of COVID-19

Lasko Basnarkov

doi:10.1016/j.chaos.2020.110394

SEAIR Epidemic spreading model of COVID-19

Chaos Solitons Fractals. 2021 Jan:142:110394. doi: 10.1016/j.chaos.2020.110394. Epub 2020 Oct 28.

Author

Lasko Basnarkov^{1

2}

Affiliations

¹ Faculty of Computer Science and Engineering, SS. Cyril and Methodius University, PO Box 393, Skopje 1000, Macedonia.
² Macedonian Academy of Sciences and Arts, PO Box 428, Skopje 1000, Macedonia.

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.

Keywords: COVID-19; Complex networks; Eigenvector centrality; Epidemic spreading; Jacobian matrix eigenvectors; SEAIR epidemic model.