Pattern Formation Induced by Fuzzy Fractional-Order Model of COVID-19

A novel coronavirus infection system is established for the analytical and computational aspects of this study, using a fuzzy fractional evolution equation (FFEE) stated in Caputo's sense for order (1,2). It is constructed using the FFEE formulated in Caputo's meaning. The model consist of six components illustrating the coronavirus outbreak, involving the susceptible people K-l(omega), the exposed population L-l(omega), total infected strength C-l(omega), asymptotically infected population M-l(omega), total number of humans recovered E-l(omega), and reservoir Q(l)(omega). Numerical results using the fuzzy Laplace approach in combination with the Adomian decomposition transform are developed to better understand the dynamical structures of the physical behavior of COVID-19. For the controlling model, such behavior on the generic characteristics of RNA in COVID-19 is also examined. The findings show that the proposed technique of addressing the uncertainty issue in a pandemic situation is effective.