Study of transmission pattern of COVID-19 among cardiac and noncardiac population using a nonlinear mathematical model

Abstract Recent studies have intensified the risk of post-COVID-19 cardiovascular diseases. In an effort to understand the intricate dynamics of COVID-19 infection, this article suggests a four-compartment model to portray the dynamic interplay between the susceptible population, the COVID-19-infected population detected without and with cardiovascular disease, and the recovered population. Basic properties such as nonnegativity and boundedness of solutions and the existence of disease-free and endemic equilibria are discussed. The model’s basic reproduction number is obtained. Sufficient conditions for local and global stability at the equilibrium point are established by restricting the functionals and parameters of the system. Numerical examples are illustrated to support the results. The relative significance of the model parameters to disease transmission is determined by performing a sensitivity analysis of the model. It is found that a rise in infection among the cardio population will drastically affect the overall infection rate compared to that of the noncardio population, supporting the real-time scenario. This model also emphasizes the importance of vaccination and treatment in controlling the spread of the virus.