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Research Article | Open Access

Fractional modeling of COVID-19 pandemic model with real data from Pakistan under the ABC operator

Rahat Zarin1Amir Khan2,3 Aurangzeb2Ali Akgül4Esra Karatas Akgül4Usa Wannasingha Humphries3( )
Department of Basic Sciences, University of Engineering and Technology Peshawar, Khyber Pakhtunkhwa, Pakistan
Department of Mathematics and Statistics, University of Swat, Khyber Pakhtunkhawa, Pakistan
Department of Mathematics, Faculty of Science, King Mongkut's University of Technology Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thrung Khru, Bangkok 10140, Thailand
Siirt University, Art and Science Faculty of Science, Department of Mathematics, TR-56100 Siirt, Turkey
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Abstract

In this study, the COVID-19 epidemic model is established by incorporating quarantine and isolation compartments with Mittag-Leffler kernel. The existence and uniqueness of the solutions for the proposed fractional model are obtained. The basic reproduction number, equilibrium points, and stability analysis of the COVID-19 model are derived. Sensitivity analysis is carried out to elaborate the influential parameters upon basic reproduction number. It is obtained that the disease transmission parameter is the most dominant parameter upon basic reproduction number. A convergent iterative scheme is taken into account to simulate the dynamical behavior of the system. We estimate the values of variables with the help of the least square curve fitting tool for the COVID-19 cases in Pakistan from 04 March to May 10, 2020, by using MATLAB.

CLC number: 37G05, 37G15, 39A28, 92B05

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AIMS Mathematics
Pages 15939-15964

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Cite this article:
Zarin R, Khan A, Aurangzeb, et al. Fractional modeling of COVID-19 pandemic model with real data from Pakistan under the ABC operator. AIMS Mathematics, 2022, 7(9): 15939-15964. https://doi.org/10.3934/math.2022872

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Received: 27 February 2022
Revised: 18 April 2022
Accepted: 27 April 2022
Published: 15 September 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)