The stochastic [Formula: see text] -SEIHRD model: Adding randomness to the COVID-19 spread

Álvaro Leitao; Carlos Vázquez

doi:10.1016/j.cnsns.2022.106731

The stochastic $θ$ -SEIHRD model: Adding randomness to the COVID-19 spread

Commun Nonlinear Sci Numer Simul. 2022 Dec:115:106731. doi: 10.1016/j.cnsns.2022.106731. Epub 2022 Jul 23.

Authors

Álvaro Leitao^{1

2}, Carlos Vázquez^{1

2}

Affiliations

¹ CITIC, Universidade da Coruña, Spain.
² Department of Mathematics, Universidade da Coruña, Spain.

Abstract

In this article we mainly extend a newly introduced deterministic model for the COVID-19 disease to a stochastic setting. More precisely, we incorporated randomness in some coefficients by assuming that they follow a prescribed stochastic dynamics. In this way, the model variables are now represented by stochastic process, that can be simulated by appropriately solving the system of stochastic differential equations. Thus, the model becomes more complete and flexible than the deterministic analogous, as it incorporates additional uncertainties which are present in more realistic situations. In particular, confidence intervals for the main variables and worst case scenarios can be computed.

Keywords: 60G99; 65C05; 65C30; CIR process; COVID-19; Compartmental models; Monte Carlo simulation; RODEs; Stochastic modelling.