Open Access

ARTICLE

Bio-Inspired Computational Methods for the Polio Virus Epidemic Model

by Fatimah Abdulrahman Alrawajeh¹, F. M. Allehiany², Ali Raza^3,*, Shaimaa A. M. Abdelmohsen⁴, Tahir Nawaz Cheema⁵, Muhammad Rafiq⁶, Muhammad Mohsin⁷

1 Department of Mathematics, Faculty of Science College, Imam Abdulrahman Bin Faisal University (IAU), Dammam, 31441, Saudi Arabia
2 Department of Mathematical Sciences, College of Applied Sciences, Umm Al-Qura University, P.O. Box 715, Makkah, 21955, Saudi Arabia
3 Department of Mathematics, Govt. Maulana Zafar Ali Khan Graduate College Wazirabad, 52000, Punjab Higher Education Department (PHED) Lahore, 54000, Pakistan
4 Department of Physics, College of Science, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia
5 Department of Mathematics, University of Gujrat, Gujrat, 50700, Pakistan
6 Department of Mathematics, Faculty of Sciences, University of Central Punjab, Lahore, 54600, Pakistan
7 Department of Mathematics, Technische Universitat Chemnitz, 6209111, Germany

* Corresponding Author: Ali Raza. Email:

Computers, Materials & Continua 2022, 72(2), 2357-2374. https://doi.org/10.32604/cmc.2022.024604

Received 24 October 2021; Accepted 24 January 2022; Issue published 29 March 2022

Abstract

In 2021, most of the developing countries are fighting polio, and parents are concerned with the disabling of their children. Poliovirus transmits from person to person, which can infect the spinal cord, and paralyzes the parts of the body within a matter of hours. According to the World Health Organization (WHO), 18 million currently healthy people could have been paralyzed by the virus during 1988–2020. Almost all countries but Pakistan, Afghanistan, and a few more have been declared polio-free. The mathematical modeling of poliovirus is studied in the population by categorizing it as susceptible individuals (S), exposed individuals (E), infected individuals (I), and recovered individuals (R). In this study, we study the fundamental properties such as positivity and boundedness of the model. We also rigorously study the model’s stability and equilibria with or without poliovirus. For numerical study, we design the Euler, Runge–Kutta, and nonstandard finite difference method. However, the standard techniques are time-dependent and fail to present the results for an extended period. The nonstandard finite difference method works well to study disease dynamics for a long time without any constraints. Finally, the results of different methods are compared to prove their effectiveness.

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Keywords

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