Investigating the Hypotheses of the COVID-19 Computational Model

A mathematical model uses equations and presumptions to depict real-world occurrences in a condensed manner. By examining the interactions between variables, it aids in the understanding and forecasting of complex systems. A mathematical model's initialization summarizes the issue, its significance, and the model's goals. In this paper, a nonsingular derivative of fractional order numerical representation of the novel coronavirus COVID-19 is given a qualitative study. Two compartments make a concerned model, one healthy and the other infected. To create the necessary criteria for the existence and singularity of a model's solution under an additional nonsingular derivative, we first construct some essential conditions. A mathematical model must be able to accurately capture the dynamics of the phenomena to ensure its existence. To establish the necessary findings, we use the traditional fixed point theory. In addition, using nonlinear analytic methods, they show that Ulam's type is stable. To get approximations of solutions for various compartments of a model under study, we expand the ordinary Laplace transform in conjunction with the Adomian decomposition technique. The results are then supported by graphical interpretations utilizing specific numerical values for the respective model parameters, which contribute to support their study.