A Modeling Investigation of the Disease Severity Driven by COVID-19-Induced Diabetic Patients

Abstract

In this study, we propose a new SEICHR compartmental model to investigate the transmission dynamics of COVID-19 in diabetic and non-diabetic patients. We emphasize the role of COVID-19-induced diabetic patients in disease dynamics. The well-posedness of the model and the stability of the equilibrium points are confirmed through rigorous mathematical analysis. Mathematical results are validated using numerical simulations. Sensitivity and bifurcation analyses are conducted to determine the most sensitive parameters in the proposed model. The sensitivity of the model parameters is examined using the partial rank correlation coefficients (PRCC) analysis. The results show that the disease progression rate is higher among COVID-19 infected diabetic patients than non-diabetic patients. The role of COVID-19-induced diabetic patients in driving disease severity was then analyzed through a constant and progressive delay in isolating them in hospitals. It can be observed numerically that a forward bifurcation region increases gradually with increases of the value of exposed individuals. In addition, the progressive waiting time was found to have a way greater effect on the transmission dynamics compared to the constant waiting time. Furthermore, the model outcomes could not verified in the light of real field data due to unavailability of data.