Emergent Dynamics: A Fuzzy Fractional-Order Model Unveiling the Complexities of COVID-19 Transmission

In this research article , we propose a fuzzy fractional-order SEI\( R_iU_i \)HR model to describe the transmission dynamics of COVID-19, comprising susceptible, exposed, infected, reported, unreported, hospitalized, and recovered compartments. The uncertainty in initial conditions is represented using fuzzy numbers, and the fuzzy Laplace transform combined with the Adomian decomposition method is employed to solve the non-linear differential equations and also to derive approximate analytical series of solutions. In addition to fuzzy lower and upper bound solutions, is introduced to provide a representative trajectory under uncertainty. Numerical experiments are conducted to compare fuzzy and normal (non-fuzzy) solutions, supported by 3D visualizations. The results reveal the influence of fractional order and fuzzy parameters on epidemic progression, demonstrating the model’s capability to capture realistic variability and to provide a flexible framework for analyzing infectious disease dynamics.