Fractional modeling and simulation of a novel Coronavirus (COVID‐19) outbreak: A meta‐population approach

Abstract In this paper, we describe a computational technique to model the novel coronavirus (COVID‐19) outbreak using Caputo–Fabrizio (CF) fractional derivatives. The proposed model is formulated as an SEIHR (Susceptible–Exposed–Infected–Hospitalized–Recovered) system of nonlinear fractional differential equations. For numerical analysis, we develop a specialized scheme based on the Adams–Bashforth method (ABM) to solve the system. Our work examines how different fractional orders affect the dynamics of the COVID‐19 outbreak, demonstrating memory and disease transmission. We compare the course of the pandemic in India and Pakistan. We derive the numerical scheme through ABM for simulations to show the impact of on the COVID‐19 pandemic in both countries. This effect is more obvious in Pakistan, where the virus propagated more slowly than in India fractional order modeling captures the complex dynamics of infectious disease outbreaks and highlights the effectiveness of timely intervention measures to control the spread of COVID‐19. In addition, we study the existence and uniqueness of the model through the Picard theorem. In the last part, we present the graphical presentation of the model.