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Research Article | Open Access

On a SEIR-type model of COVID-19 using piecewise and stochastic differential operators undertaking management strategies

Mdi Begum Jeelani1( )Kamal Shah2,3Hussam Alrabaiah4,5Abeer S. Alnahdi1
Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
Department of Mathematics, University of Malakand, Chakdara Dir (Lower), Khyber Pakhtunkhawa, Pakistan
Department of Computer Science and Mathematics, Lebanese American University, Byblos Lebanon
College of Engineering, Al Ain University, Al Ain, UAE
Department of Mathematics, Tafila Technical University, Tafila, Jordan
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Abstract

In this work, an epidemic model of a susceptible, exposed, infected and recovered SEIR-type is established for the distinctive dynamic compartments and epidemic characteristics of COVID-19 as it spreads across a population with a heterogeneous rate. The proposed model is investigated using a novel approach of fractional calculus known as piecewise derivatives. The existence theory is demonstrated through the establishment of sufficient conditions. In addition, result related to Hyers-Ulam stability is also derived for the considered model. A numerical method based on modified Euler procedure is also constructed to simulate the approximate solutions of the proposed model by employing various values of fractional orders. We testified the numerical results by using real available data of Japan. In addition, some results for the SEIR-type model are also presented graphically using the stochastic process, and the obtained results are discussed.

CLC number: 03C65, 26A33, 34A08

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AIMS Mathematics
Pages 27268-27290

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Cite this article:
Jeelani MB, Shah K, Alrabaiah H, et al. On a SEIR-type model of COVID-19 using piecewise and stochastic differential operators undertaking management strategies. AIMS Mathematics, 2023, 8(11): 27268-27290. https://doi.org/10.3934/math.20231395

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Received: 03 August 2023
Revised: 23 August 2023
Accepted: 28 August 2023
Published: 15 November 2023
©2023 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)