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Stationary Distribution and Extinction of Stochastic Coronavirus (covid-19) Epidemic Model

dc.contributor.author Khan, Amir
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Din, Anwarud
dc.contributor.authorID 56389 tr_TR
dc.contributor.other 02.02. Matematik
dc.contributor.other 02. Fen-Edebiyat Fakültesi
dc.contributor.other 01. Çankaya Üniversitesi
dc.date.accessioned 2023-01-16T07:53:52Z
dc.date.accessioned 2025-09-18T13:26:43Z
dc.date.available 2023-01-16T07:53:52Z
dc.date.available 2025-09-18T13:26:43Z
dc.date.issued 2020
dc.description.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. en_US
dc.description.publishedMonth 10
dc.description.sponsorship This work was supported by the HEC. en_US
dc.description.sponsorship HEC en_US
dc.identifier.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. en_US
dc.identifier.doi 10.1016/j.chaos.2020.110036
dc.identifier.issn 0960-0779
dc.identifier.issn 1873-2887
dc.identifier.scopus 2-s2.0-85087202895
dc.identifier.uri https://doi.org/10.1016/j.chaos.2020.110036
dc.identifier.uri https://hdl.handle.net/123456789/12700
dc.language.iso en en_US
dc.publisher Pergamon-elsevier Science Ltd en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Stochastic Epidemic Model en_US
dc.subject Covid-19 en_US
dc.subject Threshold Value en_US
dc.subject Global Stability en_US
dc.subject Real Data en_US
dc.subject Stationary Distribution en_US
dc.title Stationary Distribution and Extinction of Stochastic Coronavirus (covid-19) Epidemic Model en_US
dc.title Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model tr_TR
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Baleanu, Dumitru
gdc.author.scopusid 57201196587
gdc.author.scopusid 56106981700
gdc.author.scopusid 7005872966
gdc.author.wosid Baleanu, Dumitru/B-9936-2012
gdc.author.wosid Din, Anwarud/Caj-3276-2022
gdc.description.department Çankaya University en_US
gdc.description.departmenttemp [Din, Anwarud] Univ Malakand KPK, Dept Math, Lower Dir, Pakistan; [Khan, Amir] Univ Swat, Dept Math & Stat, Swat, Khyber Pakhtunk, Pakistan; [Baleanu, Dumitru] Cankaya Univ, Art & Sci Fac, Dept Math & Comp Sci, TR-06300 Ankara, Turkey; [Baleanu, Dumitru] Inst Space Sci, Dept Math, Bucharest, Romania; [Baleanu, Dumitru] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung, Taiwan en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.volume 139 en_US
gdc.description.woscitationindex Science Citation Index Expanded
gdc.description.wosquality Q1
gdc.identifier.openalex W3036775721
gdc.identifier.pmid 32834596
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gdc.openalex.fwci 2.8834079
gdc.openalex.normalizedpercentile 0.94
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 87
gdc.plumx.crossrefcites 93
gdc.plumx.mendeley 69
gdc.plumx.pubmedcites 18
gdc.plumx.scopuscites 106
gdc.scopus.citedcount 106
gdc.wos.citedcount 99
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