Fractional dynamics of coronavirus with comorbidity via Caputo-Fabrizio derivative

Abstract

Coronavirus and its associated comorbidities have been the drivers of many deaths across the globe in recent times. Individuals with underlying medical conditions are at higher risk of becoming critically ill and developing complications if they are infected with the Coronavirus. In this paper, a Caputo-Fabrizio fractional-order model of coronavirus disease with comorbidity is formulated to access the impact of comorbidity diseases on COVID-19 transmission using both a fractional-order as well as a stochastic approach. Exponential law is utilized to present the existence and uniqueness of solutions using the fixed-point theory. The fractional stochastic approach is adopted to examine the same model to explore the random effect. Numerical simulations are used to support the theoretical results and the simulation results suggest that the increase of comorbidity development and the fractional-order derivative factor simultaneously increases the prevalence of the infection and the spread of the disease. The fractional stochastic numerical results suggest that the prediction of infection rate is more stochastic than deterministic.