Stochastic and deterministic analysis of a COVID-19 pandemic model under vaccination strategy and crowding effect

Adil Ez-Zetoun; Omar  Khyar; Karam  Allali; Khadija  Akdim; Mehdi  Zahid

doi:10.5269/bspm.67238

Adil Ez-Zetoun Cadi Ayyad University
Omar Khyar
Karam Allali
Khadija Akdim
Mehdi Zahid

Abstract

In this paper, we present a novel SICVS COVID-19 pandemic model incorporating a vaccination strategy and crowding effect. First, we investigate the steady states and proved the local stability of the corresponding deterministic problem. Then we study the proposed stochastic epidemic model; we have considered a random incidence highlighting all the improbable fluctuations that appear in the infection process. Hence, the COVID-19 transmission parameter in the considered model will be stochastically perturbed by the white noise. We show the disease extinction of the pandemic according to the stochastic noise intensity. It was established, in the stochastic study, the existence of a possible extinction of the pandemic even if the basic reproduction number is greater than unity. Furthermore we discuss the persistence in mean of the studied infection in terms of the stochastic model parameters. Our numerical simulations confirm the theoretical findings. The proposed model was validated and supported by a comparison, during the second wave of the pandemic in Morocco, between the trajectories of the clinical data of Covid-19 and those which represent our SICVS model. In addition, the impact of vaccination and social distancing strategies on reducing the infection severity were observed.

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