International Journal of Nonlinear Analysis and Applications

Treatment of dynamical nonlinear Measles model: An evolutionary approach

Document Type : Research Paper

Authors

1 Department of Mathematics, University of Management and Technology, Lahore, Pakistan

2 Art and Science Faculty, Department of Mathematics, Siirt University, 56100 Siirt, Turkey

3 Department of Mathematics and Statistics, University of Lahore, Lahore, Pakistan

4 Department of Sports Sciences, Faculty of Allied Health Science, University of Lahore, Lahore, Pakistan

Abstract

Measles is a respiratory system infection caused by a Morbillivirus genus virus. The disease spreads directly or indirectly through respiration from the infected person's nose and mouth after contact with fluids. The vast population of infects in developing countries is yet at risk. Generally, the mathematical model of Measles virus propagation is nonlinear and therefore changeable to solve by traditional analytical and finite difference schemes by processing all properties of the model like boundedness, positivity feasibility. In this paper, an unconditionally convergent semi-analytical approach based on modern Evolutionary computational technique and Padé- Approximation (EPA) has been implemented for the treatment of non-linear Measles model. The convergence solution of EPA scheme on population: susceptible people, infective people, and recovered people have been studied and found to be significant. Eventually, EPA reduces contaminated levels very rapidly and no need to supply step size. A robust and durable solution has been established with the EPA in terms of the relationship between disease-free equilibrium in the population. When comparing the Non-Standard Finite Difference (NSFD) approach, the findings of EPA have shown themselves to be far superior.

Keywords

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International Journal of Nonlinear Analysis and Applications
Volume 13, Issue 1
March 2022
Pages 1629-1638
  • Receive Date: 24 May 2020
  • Revise Date: 30 July 2020
  • Accept Date: 28 September 2020