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ARTICLE
Dynamical Analysis of the Stochastic COVID-19 Model Using Piecewise Differential Equation Technique
Yu-Ming Chu1, Sobia Sultana2, Saima Rashid3,*, Mohammed Shaaf Alharthi4
1
Department of Mathematics, Huzhou University, Huzhou, 313000, China
2
Department of Mathematics, Imam Mohammad Ibn Saud Islamic University, Riyadh, 12211, Saudi Arabia
3
Department of Mathematics, Government College University, Faisalabad, 38000, Pakistan
4
Department of Mathematics and Statistics, College of Science, Taif University, P.O.Box 11099, Taif, 21944, Saudi Arabia
* Corresponding Author: Saima Rashid. Email:
(This article belongs to the Special Issue: Recent Developments on Computational Biology-I)
Computer Modeling in Engineering & Sciences 2023, 137(3), 2427-2464. https://doi.org/10.32604/cmes.2023.028771
Received 06 January 2023; Accepted 20 March 2023; Issue published 03 August 2023
Abstract
Various data sets showing the prevalence of numerous viral diseases have demonstrated that the transmission is
not truly homogeneous. Two examples are the spread of Spanish flu and COVID-19. The aim of this research is to
develop a comprehensive nonlinear stochastic model having six cohorts relying on ordinary differential equations
via piecewise fractional differential operators. Firstly, the strength number of the deterministic case is carried out.
Then, for the stochastic model, we show that there is a critical number
that can predict virus persistence
and infection eradication. Because of the peculiarity of this notion, an interesting way to ensure the existence
and uniqueness of the global positive solution characterized by the stochastic COVID-19 model is established by
creating a sequence of appropriate Lyapunov candidates. A detailed ergodic stationary distribution for the stochastic
COVID-19 model is provided. Our findings demonstrate a piecewise numerical technique to generate simulation
studies for these frameworks. The collected outcomes leave no doubt that this conception is a revolutionary
doorway that will assist mankind in good perspective nature.
Keywords
Cite This Article
APA Style
Chu, Y., Sultana, S., Rashid, S., Alharthi, M.S. (2023). Dynamical analysis of the stochastic COVID-19 model using piecewise differential equation technique. Computer Modeling in Engineering & Sciences, 137(3), 2427-2464. https://doi.org/10.32604/cmes.2023.028771
Vancouver Style
Chu Y, Sultana S, Rashid S, Alharthi MS. Dynamical analysis of the stochastic COVID-19 model using piecewise differential equation technique. Comput Model Eng Sci. 2023;137(3):2427-2464 https://doi.org/10.32604/cmes.2023.028771
IEEE Style
Y. Chu, S. Sultana, S. Rashid, and M.S. Alharthi "Dynamical Analysis of the Stochastic COVID-19 Model Using Piecewise Differential Equation Technique," Comput. Model. Eng. Sci., vol. 137, no. 3, pp. 2427-2464. 2023. https://doi.org/10.32604/cmes.2023.028771