A Multi-step Differential Transform Approach for a Nonlinear Fractional COVID–19 Pandemic Model

In this article, a successive implementation of the differential transform method is applied to obtain a semi-analytic approximate solution of a nonlinear fractional model of COVID19. The initial values and parameters of the COVID populations are taken from confirmed cases during the early days of the outbreak in Wuhan, China. The ultimate goal is to obtain an approximate solution that maintains convergence and stability over a long period of time. Based on the computational outcomes for various initial populations and parameters, analyzing and interpreting the model’s parameters can lead to optimal virus control. Furthermore, the obtained approximate solutions will be tested for the integer-derivative case against the fourth-order Runge-Kutta results.