Threshold dynamics of a stochastic SIHR epidemic model of COVID-19 with general population-size dependent contact rate

Abstract

In this paper, we propose a stochastic SIHR epidemic model of COVID-19. A basic reproduction number R0s is defined to determine the extinction or persistence of the disease. If R0s < 1, the disease will be extinct. If R0s > 1, the disease will be strongly stochastically permanent. Based on realistic parameters of COVID-19, we numerically analyze the effect of key parameters such as transmission rate, confirmation rate and noise intensity on the dynamics of disease transmission and obtain sensitivity indices of some parameters on R0s by sensitivity analysis. It is found that: 1) The threshold level of deterministic model is overestimated in case of neglecting the effect of environmental noise; 2) The decrease of transmission rate and the increase of confirmed rate are beneficial to control the spread of COVID-19. Moreover, our sensitivity analysis indicates that the parameters β, σ and δ have significantly effects on R0s