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Essential Features Preserving Dynamics of Stochastic Dengue Model

Wasfi Shatanawi1,2,3, Ali Raza4,5,*, Muhammad Shoaib Arif4, Muhammad Rafiq6, Mairaj Bibi7, Muhammad Mohsin8

1 Department of Mathematics and General Sciences, Prince Sultan University, Riyadh, Saudi Arabia
2 Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40402, Taiwan
3 Department of Mathematics, Hashemite University, Zarqa, Jordan
4 Stochastic Analysis & Optimization Research Group, Department of Mathematics, Air University, Islamabad, 44000, Pakistan
5 Department of Mathematics, National College of Business Administration and Economics, Lahore, Pakistan
6 Department of Mathematics, Faculty of Sciences, University of Central Punjab, Lahore, 54500, Pakistan
7 Department of Mathematics, Comsats University Islamabad, Islamabad, Pakistan
8 Department of Mathematics, Uppsala University, Uppsala, Sweden

* Corresponding Author: Ali Raza. Email:

Computer Modeling in Engineering & Sciences 2021, 126(1), 201-215.


Nonlinear stochastic modelling plays an important character in the different fields of sciences such as environmental, material, engineering, chemistry, physics, biomedical engineering, and many more. In the current study, we studied the computational dynamics of the stochastic dengue model with the real material of the model. Positivity, boundedness, and dynamical consistency are essential features of stochastic modelling. Our focus is to design the computational method which preserves essential features of the model. The stochastic non-standard finite difference technique is most efficient as compared to other techniques used in literature. Analysis and comparison were explored in favour of convergence. Also, we address the comparison between the stochastic and deterministic models.


Cite This Article

Shatanawi, W., Raza, A., Arif, M. S., Rafiq, M., Bibi, M. et al. (2021). Essential Features Preserving Dynamics of Stochastic Dengue Model. CMES-Computer Modeling in Engineering & Sciences, 126(1), 201–215.


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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