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Stochastic Numerical Analysis for Impact of Heavy Alcohol Consumption on Transmission Dynamics of Gonorrhoea Epidemic

Kamaleldin Abodayeh1, Ali Raza2, *, Muhammad Shoaib Arif2, Muhammad Rafiq3, Mairaj Bibi4, Muhammad Mohsin5

1 Department of Mathematics and General Sciences, Prince Sultan University, Riyadh, Saudi Arabia.
2 Stochatic Analysis & Optimization Research Group, Department of Mathematics, Air University, PAF Complex E-9, Islamabad, 44000, Pakistan.
3 Faculty of Engineering University of Central Punjab, Lahore, Pakistan.
4 Department of Mathematics, Comsats University, Chak Shahzad Campus park road, Islamabad, Pakistan.
5 Department of Mathematics, Uppsala University, Uppsala, Sweden.

* Corresponding Author: Kamaleldin Abodayeh. Email: email.

Computers, Materials & Continua 2020, 62(3), 1125-1142. https://doi.org/10.32604/cmc.2020.08885

Abstract

This paper aims to perform a comparison of deterministic and stochastic models. The stochastic modelling is a more realistic way to study the dynamics of gonorrhoea infection as compared to its corresponding deterministic model. Also, the deterministic solution is itself mean of the stochastic solution of the model. For numerical analysis, first, we developed some explicit stochastic methods, but unfortunately, they do not remain consistent in certain situations. Then we proposed an implicitly driven explicit method for stochastic heavy alcohol epidemic model. The proposed method is independent of the choice of parameters and behaves well in all scenarios. So, some theorems and simulations are presented in support of the article.

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Cite This Article

K. Abodayeh, A. Raza, M. Shoaib Arif, M. Rafiq, M. Bibi et al., "Stochastic numerical analysis for impact of heavy alcohol consumption on transmission dynamics of gonorrhoea epidemic," Computers, Materials & Continua, vol. 62, no.3, pp. 1125–1142, 2020. https://doi.org/10.32604/cmc.2020.08885

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cc 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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