Fractional-Order SEIRD Model for Global COVID-19 Outbreak

Rana Yousif (), Aref Jeribi and Saad Al-Azzawi
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Rana Yousif: Department of Mathematics, Faculty of Sciences of Sfax, University of Sfax, Road of Soukra Km 3.5, B.P. 1171, Sfax 3000, Tunisia
Aref Jeribi: Department of Mathematics, Faculty of Sciences of Sfax, University of Sfax, Road of Soukra Km 3.5, B.P. 1171, Sfax 3000, Tunisia
Saad Al-Azzawi: Department of Mathematics, College of Science for Women, Baghdad University, Baghdad 10071, Iraq

Mathematics, 2023, vol. 11, issue 4, 1-19

Abstract: With the identification of new mutations in the coronavirus with greater transmissibility and pathogenicity, the number of infected people with COVID-19 worldwide has increased as from 22 June 2021, and a new wave has been created. Since the spread of the coronavirus, many studies have been conducted on different groups. The current research was adopted on the implementations of fractional-order (SEIRD: Susceptible, Exposed, Infected, Recovered, Died) people model with a Caputo derivative for investigating the spread of COVID-19. The characteristics of the system, such as the boundedness, existence, uniqueness and non-negativity of the solutions, the equilibrium points of system, and the basic reproduction number, were analyzed. In the numerical part, a simulation for the spread of the virus is presented, which shows that this wave of spread will continue for the next few months and an increasing number of people becoming infected. Furthermore, the numerical results obtained from several types of fractional-order derivatives are compared with real data, which subsequently shows that the Caputo fractional-order derivative follows real data better than others. In addition, the obtained reproduction number has a value greater than one, indicating a continuation of the disease outbreak and the necessity of taking more control decisions.

Keywords: coronavirus; fractional-order; reproduction number; SEIRD model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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