On nonlinear dynamics of COVID-19 disease model corresponding to nonsingular fractional order derivative

Autor: Muhammad Arfan, Maha M. A. Lashin, Pongsakorn Sunthrayuth, Kamal Shah, Aman Ullah, Kulpash Iskakova, M. R. Gorji, Thabet Abdeljawad
Rok vydání: 2022
Předmět:
Zdroj: Medical & Biological Engineering & Computing. 60:3169-3185
ISSN: 1741-0444
0140-0118
DOI: 10.1007/s11517-022-02661-6
Popis: This manuscript is devoted to investigate the mathematical model of fractional-order dynamical system of the recent disease caused by Corona virus. The said disease is known as Corona virus infectious disease (COVID-19). Here we analyze the modified SEIR pandemic fractional order model under nonsingular kernel type derivative introduced by Atangana, Baleanu and Caputo ([Formula: see text]) to investigate the transmission dynamics. For the validity of the proposed model, we establish some qualitative results about existence and uniqueness of solution by using fixed point approach. Further for numerical interpretation and simulations, we utilize Adams-Bashforth method. For numerical investigations, we use some available clinical data of the Wuhan city of China, where the infection initially had been identified. The disease free and pandemic equilibrium points are computed to verify the stability analysis. Also we testify the proposed model through the available data of Pakistan. We also compare the simulated data with the reported real data to demonstrate validity of the numerical scheme and our analysis.
Databáze: OpenAIRE
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