The Analysis of a Time Delay Fractional COVID-19 Model via Caputo Type Fractional Derivative - Kumar, Pushpendra; Suat Erturk, Vedat (Wiley, 2023)
Novel coronavirus (COVID-19), a global threat whose source is not correctly yet known, was firstly recognised in the city of Wuhan, China, in December 2019. Now, this disease has been spread out to many countries in all over the world. In this paper, we solved a time delay fractional COVID-19 SEIR epidemic model via Caputo fractional derivatives using a predictor-corrector method. We provided numerical simulations to show the nature of the diseases for different classes. We derived existence of unique global solutions to the given time delay fractional differential equations (DFDEs) under a mild Lipschitz condition using properties of a weighted norm, Mittag-Leffler functions and the Banach fixed point theorem. For the graphical simulations, we used real numerical data based on a case study of Wuhan, China, to show the nature of the projected model with respect to time variable. We performed various plots for different values of time delay and fractional order. We observed that the proposed scheme is highly emphatic and easy to implementation for the system of DFDEs.
Kumar, Pushpena/0000-0002-7755-2837;
Keywords: Caputo Fractional Derivative; COVID-19 Epidemic; Fixed Point Theory; Predictor-Corrector Scheme; SEIR Model; Time Delay