Coronavirus dynamics, infections and preventive interventions using fractional-calculus analysis

In this research work, we construct an epidemic model to understand COVID-19 transmission vaccination and therapy considerations. The model's equilibria were examined, and the reproduction parameter was calculated via a next-generation matrix method, symbolized by ${\mathcal{R}}_0$. We have shown that the infection-free steady state of our system is locally asymptotically stable for ${\mathcal{R}}_0<1$. Also, the local asymptotic stability of the endemic steady state has been established for ${\mathcal{R}}_0>1$. We have used a partial rank correlation coefficient method for sensitivity analysis of the threshold parameter ${\mathcal{R}}_0$. The contribution of vaccination to the threshold parameter is explored through graphical results. In addition to this, the uniqueness and existence of the solution to the postulated model of COVID-19 infection is shown. We ran various simulations of the proposed COVID-19 dynamics with varied input parameters to scrutinize the complex dynamics of COVID-19 infection. We illustrated the variation in the dynamical behavior of the system with different values of the input parameters. The key factors of the system are visualized for the public health officials for the control of the infection.