@Article{cmes.2023.028771,
AUTHOR = {Yu-Ming Chu, Sobia Sultana, Saima Rashid, Mohammed Shaaf Alharthi},
TITLE = {Dynamical Analysis of the Stochastic COVID-19 Model Using Piecewise Differential Equation Technique},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {137},
YEAR = {2023},
NUMBER = {3},
PAGES = {2427--2464},
URL = {http://www.techscience.com/CMES/v137n3/53737},
ISSN = {1526-1506},
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 <img src="http://www.techscience.com/files/CMES/rs.png" width="20px"> 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.},
DOI = {10.32604/cmes.2023.028771}
}