Stationary Distribution and Extinction of Stochastic Coronavirus (covid-19) Epidemic Model
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Date
2020
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Pergamon-elsevier Science Ltd
Open Access Color
HYBRID
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
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. (C) 2020 Published by Elsevier Ltd.
Description
Keywords
Stochastic Epidemic Model, Covid-19, Threshold Value, Global Stability, Real Data, Stationary Distribution, SARS-CoV-2, General Mathematics, Applied Mathematics, COVID-19, General Physics and Astronomy, Statistical and Nonlinear Physics, Global stability, Real data, Article, Coronavirus, Stationary distribution, Síndrome respiratorio agudo grave, Stochastic epidemic model, Threshold value, Epidemiology, threshold value, stochastic epidemic model, Dynamical systems in biology, global stability, Stochastic ordinary differential equations (aspects of stochastic analysis), stationary distribution, real data
Fields of Science
01 natural sciences, 0103 physical sciences
Citation
Din, Anwarud; Khan, Amir; Baleanu, Dumitru (2020). "Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model", Chaos, Solitons and Fractals, Vol. 139.
WoS Q
Q1
Scopus Q
Q1

OpenCitations Citation Count
94
Source
Chaos, Solitons & Fractals
Volume
139
Issue
Start Page
110036
End Page
PlumX Metrics
Citations
CrossRef : 93
Scopus : 105
PubMed : 19
Captures
Mendeley Readers : 68
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