Open Access

ARTICLE

Fractional Analysis of Dynamical Novel COVID-19 by Semi-Analytical Technique

S. Iqbal¹, D. Baleanu^2,3, Javaid Ali⁴, H. M. Younas⁵, M. B. Riaz^6,7,*

1 School of Systems and Technology, University of Management and Technology, Lahore, 54770, Pakistan
2 Department of Mathematics, Cankaya University, Ankara, 06530, Turkey
3 Institute of Space Sciences, Magurele, Bucharest, 077125, Romania
4 Department of Mathematics, Govt. College Township, Punjab Higher Education Department, Lahore, 54770, Pakistan
5 Department of Mathematics, Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan
6 Department of Mathematics, University of Management and Technology, Lahore, 54770, Pakistan
7 Institute for Groundwater Studies, University of the Free State, Bloemfontein, 9300, South Africa

* Corresponding Author: M. B. Riaz. Email:

(This article belongs to the Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)

Computer Modeling in Engineering & Sciences 2021, 129(2), 705-727. https://doi.org/10.32604/cmes.2021.015375

Received 14 December 2020; Accepted 24 June 2021; Issue published 08 October 2021

Abstract

This study employs a semi-analytical approach, called Optimal Homotopy Asymptotic Method (OHAM), to analyze a coronavirus (COVID-19) transmission model of fractional order. The proposed method employs Caputo's fractional derivatives and Reimann-Liouville fractional integral sense to solve the underlying model. To the best of our knowledge, this work presents the first application of an optimal homotopy asymptotic scheme for better estimation of the future dynamics of the COVID-19 pandemic. Our proposed fractional-order scheme for the parameterized model is based on the available number of infected cases from January 21 to January 28, 2020, in Wuhan City of China. For the considered real-time data, the basic reproduction number is R₀ ≈ 2.48293 that is quite high. The proposed fractional-order scheme for solving the COVID-19 fractional-order model possesses some salient features like producing closed-form semi-analytical solutions, fast convergence and non-dependence on the discretization of the domain. Several graphical presentations have demonstrated the dynamical behaviors of subpopulations involved in the underlying fractional COVID-19 model. The successful application of the scheme presented in this work reveals new horizons of its application to several other fractional-order epidemiological models.

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Keywords

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