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Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment

Fazal Dayan1,*, Dumitru Baleanu2,3,4, Nauman Ahmed5, Jan Awrejcewicz6, Muhammad Rafiq7, Ali Raza8, Muhammad Ozair Ahmad5

1 Department of Mathematics, School of Science, University of Management and Technology, Lahore, 54000, Pakistan
2 Department of Mathematics, Cankaya University, Balgat, Ankara, 06530, Turkey
3 Department of Medical Research, China Medical University, Taichung, 40402, Taiwan
4 Institute of Space Sciences, Magurele-Bucharest, 077125, Romania
5 Department of Mathematics and Statistics, University of Lahore, Lahore, 54000, Pakistan
6 Department of Automation, Biomechanics and Mechatronics, Lodz University of Technology, 1/15 Stefanowskiego St., 90-924, Lodz, Poland
7 Department of Mathematics, Faculty of Science & Technology, University of Central Punjab, Lahore, 54000, Pakistan
8 Department of Mathematics, Govt. Maulana Zafar Ali Khan Graduate College Wazirabad, Punjab Higher Education Department (PHED), Lahore, 54000, Pakistan

* Corresponding Author: Fazal Dayan. Email:

Computers, Materials & Continua 2023, 74(2), 2345-2361.


The application of fuzzy theory is vital in all scientific disciplines. The construction of mathematical models with fuzziness is little studied in the literature. With this in mind and for a better understanding of the disease, an SEIR model of malaria transmission with fuzziness is examined in this study by extending a classical model of malaria transmission. The parameters and , being function of the malaria virus load, are considered fuzzy numbers. Three steady states and the reproduction number of the model are analyzed in fuzzy senses. A numerical technique is developed in a fuzzy environment to solve the studied model, which retains essential properties such as positivity and dynamic consistency. Moreover, numerical simulations are carried out to illustrate the analytical results of the developed technique. Unlike most of the classical methods in the literature, the proposed approach converges unconditionally and can be considered a reliable tool for studying malaria disease dynamics.


Cite This Article

F. Dayan, D. Baleanu, N. Ahmed, J. Awrejcewicz, M. Rafiq et al., "Numerical investigation of malaria disease dynamics in fuzzy environment," Computers, Materials & Continua, vol. 74, no.2, pp. 2345–2361, 2023.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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