Open Access

ARTICLE

New Trends in the Modeling of Diseases Through Computational Techniques

Nesreen Althobaiti¹, Ali Raza^2,*, Arooj Nasir^3,4, Jan Awrejcewicz⁵, Muhammad Rafiq⁶, Nauman Ahmed⁷, Witold Pawłowski⁸, Muhammad Jawaz⁷, Emad E. Mahmoud¹

1 Department of Mathematics and Statistics, College of Science, Taif University, P. O. Box 11099, Taif, 21944, Saudi Arabia
2 Department of Mathematics, Govt. Maulana Zafar Ali Khan Graduate College Wazirabad, Punjab Higher Education Department (PHED), Lahore, 54000, Pakistan
3 Baqai Medical University, Karachi, 75340, Pakistan
4 Shalamar Medical and Dental College, Lahore, 54000, Pakistan
5 Department of Automation, Biomechanics and Mechatronics, Lodz University of Technology, 1/15 Stefanowskiego St., 90-924, Lodz, Poland
6 Department of Mathematics, Faculty of Sciences and Technology, University of Central Punjab, Lahore, 54000, Pakistan
7 Department of Mathematics and Statistics, University of Lahore, Lahore, 54590, Pakistan
8 Institute of Machine Tools and Production Engineering, Lodz University of Technology, 1/15 Stefanowskiego St., 90-537, Lodz, Poland

* Corresponding Author: Ali Raza. Email:

Computer Systems Science and Engineering 2023, 45(3), 2935-2951. https://doi.org/10.32604/csse.2023.033935

Received 01 July 2022; Accepted 22 August 2022; Issue published 21 December 2022

Abstract

The computational techniques are a set of novel problem-solving methodologies that have attracted wider attention for their excellent performance. The handling strategies of real-world problems are artificial neural networks (ANN), evolutionary computing (EC), and many more. An estimated fifty thousand to ninety thousand new leishmaniasis cases occur annually, with only 25% to 45% reported to the World Health Organization (WHO). It remains one of the top parasitic diseases with outbreak and mortality potential. In 2020, more than ninety percent of new cases reported to World Health Organization (WHO) occurred in ten countries: Brazil, China, Ethiopia, Eritrea, India, Kenya, Somalia, South Sudan, Sudan, and Yemen. The transmission of visceral leishmaniasis is studied dynamically and numerically. The study included positivity, boundedness, equilibria, reproduction number, and local stability of the model in the dynamical analysis. Some detailed methods like Runge Kutta and Euler depend on time steps and violate the physical relevance of the disease. They produce negative and unbounded results, so in disease dynamics, such developments have no biological significance; in other words, these results are meaningless. But the implicit nonstandard finite difference method does not depend on time step, positive, bounded, dynamic and consistent. All the computational techniques and their results were compared using computer simulations.

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Keywords

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