Abstract

In this paper, we propose a modified fractional diffusive SEAIR epidemic model with a nonlinear incidence rate. A constructed model of fractional partial differential equations (PDEs) is more general than the corresponding model of fractional ordinary differential equations (ODEs). The Caputo fractional derivative is considered. Linear stability analysis of the disease-free equilibrium state of the epidemic model (ODEs) is presented by employing Routh–Hurwitz stability criteria. In order to solve this model, a fractional numerical scheme is proposed. The proposed scheme can be used to find conditions for obtaining positive solutions for diffusive epidemic models. The stability of the scheme is given, and convergence conditions are found for the system of the linearized diffusive fractional epidemic model. In addition to this, the deficiencies of accuracy and consistency in the nonstandard finite difference method are also underlined by comparing the results with the standard fractional scheme and the MATLAB built-in solver pdepe. The proposed scheme shows an advantage over the fractional nonstandard finite difference method in terms of accuracy. In addition, numerical results are supplied to evaluate the proposed scheme’s performance.

Highlights

  • Nowadays, the world faces the contagious outcomes of a fatal pathogen called coronavirus [1], which belongs to the family of SARS-CoV-2

  • The main aim of this work is to propose a numerical scheme for solving time-dependent epidemic models

  • The numerical experiments show the effectiveness of the proposed fractional scheme

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Summary

Introduction

The world faces the contagious outcomes of a fatal pathogen called coronavirus [1], which belongs to the family of SARS-CoV-2. Viruses of this family can transfer their pathogenicity to humans and animals. Precautionary and preventive measures have been taken at the government level to contain the virus to save the economy and health system from collapse. This situation of uncertainty between life and death has opened a new gospel in the field of quantitative mathematical modeling. In 1927, Kermack and McKendrick developed an epidemic modeling technique

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