A Mathematical Model of COVID-19 Infection Transmission Dynamics

Abstract

A compartmental nonlinear deterministic epidemic model of coronavirus infection 2019 (COVID-19) transmission dynamics incorporating social distancing; face masks use and hospitalization is formulated. The disease-free equilibrium state was obtained and at this disease-free equilibrium state, the basic reproduction number was computed using the next generator matrix operator. It was shown, using linearization method and Routh-Hurwitz stability criterion, that the disease-free equilibrium state is locally asymptotically stable whenever the basic reproduction number is less than unity. The sensitivity analysis of  with respect to the model parameters was carried out using the normalized forward sensitivity indices. The results of the sensitivity index of  shows that the most sensitive parameter is the infection transmission probability which was also taken as the social distancing parameter. Numerical simulations show that, the use of single intervention strategy is beneficial in reducing COVID-19 disease burden. It is further shown that effective combination of social distancing, use of face masks in public and isolation (hospitalization) of infected individuals will lead to a great decrease in COVID-19 infection burden.