Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model
Autor
Din, Anwarud
Khan, Amir
Baleanu, Dumitru
Institución
Resumen
Similar to other epidemics, the novel coronavirus (COVID-19) spread very fast and infected almost two
hundreds countries around the globe since December 2019. The unique characteristics of the COVID-19
include its ability of faster expansion through freely existed viruses or air molecules in the atmosphere.
Assuming that the spread of virus follows a random process instead of deterministic. The continuous time
Markov Chain (CTMC) through stochastic model approach has been utilized for predicting the impending
states with the use of random variables. The proposed study is devoted to investigate a model consist
of three exclusive compartments. The first class includes white nose based transmission rate (termed
as susceptible individuals), the second one pertains to the infected population having the same perturbation occurrence and the last one isolated (quarantined) individuals. We discuss the model’s extinction as well as the stationary distribution in order to derive the the sufficient criterion for the persistence and disease’ extinction. Lastly, the numerical simulation is executed for supporting the theoretical
findings.