Dynamical analysis of a stochastic delayed epidemic model with lévy jumps and regime switching
•Study of the epidemic model for SARS-CoV-2 virus spread in a stochastic framework.•Transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process.•Dynamics of model that contains white and telegraph noise, Lévy jump and time delay.•Mathematical tool for constructing strategies for the co...
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Veröffentlicht in: | Journal of the Franklin Institute 2023-01, Vol.360 (2), p.1252-1283 |
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description | •Study of the epidemic model for SARS-CoV-2 virus spread in a stochastic framework.•Transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process.•Dynamics of model that contains white and telegraph noise, Lévy jump and time delay.•Mathematical tool for constructing strategies for the control of diseases.•Numerical simulations based on the real data illustrate the main theoretical results.
In this paper a delayed stochastic SLVIQR epidemic model, which can be applied for modeling the new coronavirus COVID-19 after a calibration, is derived. Model is constructed by assuming that transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process and, besides a standard Brownian motion, another two driving processes are considered: a stationary Poisson point process and a continuous finite-state Markov chain. For the constructed model, the existence and uniqueness of positive global solution is proven. Also, sufficient conditions under which the disease would lead to extinction or be persistent in the mean are established and it is shown that constructed model has a richer dynamic analysis compared to existing models. In addition, numerical simulations are given to illustrate the theoretical results. |
doi_str_mv | 10.1016/j.jfranklin.2022.12.009 |
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In this paper a delayed stochastic SLVIQR epidemic model, which can be applied for modeling the new coronavirus COVID-19 after a calibration, is derived. Model is constructed by assuming that transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process and, besides a standard Brownian motion, another two driving processes are considered: a stationary Poisson point process and a continuous finite-state Markov chain. For the constructed model, the existence and uniqueness of positive global solution is proven. Also, sufficient conditions under which the disease would lead to extinction or be persistent in the mean are established and it is shown that constructed model has a richer dynamic analysis compared to existing models. In addition, numerical simulations are given to illustrate the theoretical results.</description><identifier>ISSN: 0016-0032</identifier><identifier>EISSN: 1879-2693</identifier><identifier>EISSN: 0016-0032</identifier><identifier>DOI: 10.1016/j.jfranklin.2022.12.009</identifier><identifier>PMID: 36533206</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><ispartof>Journal of the Franklin Institute, 2023-01, Vol.360 (2), p.1252-1283</ispartof><rights>2022 The Franklin Institute</rights><rights>2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.</rights><rights>info:eu-repo/semantics/openAccess</rights><rights>2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved. 2022 The Franklin Institute</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c500t-d18d41ef70756e48c035cee923721449899829ce2e5f15120f376b7f5a31388f3</citedby><cites>FETCH-LOGICAL-c500t-d18d41ef70756e48c035cee923721449899829ce2e5f15120f376b7f5a31388f3</cites><orcidid>0000-0001-6788-307X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jfranklin.2022.12.009$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,885,3550,26567,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36533206$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dordevic, Jasmina</creatorcontrib><creatorcontrib>Jovanović, Bojana</creatorcontrib><title>Dynamical analysis of a stochastic delayed epidemic model with lévy jumps and regime switching</title><title>Journal of the Franklin Institute</title><addtitle>J Franklin Inst</addtitle><description>•Study of the epidemic model for SARS-CoV-2 virus spread in a stochastic framework.•Transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process.•Dynamics of model that contains white and telegraph noise, Lévy jump and time delay.•Mathematical tool for constructing strategies for the control of diseases.•Numerical simulations based on the real data illustrate the main theoretical results.
In this paper a delayed stochastic SLVIQR epidemic model, which can be applied for modeling the new coronavirus COVID-19 after a calibration, is derived. Model is constructed by assuming that transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process and, besides a standard Brownian motion, another two driving processes are considered: a stationary Poisson point process and a continuous finite-state Markov chain. For the constructed model, the existence and uniqueness of positive global solution is proven. Also, sufficient conditions under which the disease would lead to extinction or be persistent in the mean are established and it is shown that constructed model has a richer dynamic analysis compared to existing models. In addition, numerical simulations are given to illustrate the theoretical results.</description><issn>0016-0032</issn><issn>1879-2693</issn><issn>0016-0032</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>3HK</sourceid><recordid>eNqFkUuO1DAQhi0EYpqBK4CXbBLKdhzHG6TR8JRGYgNry-NUuh0Su7HTjXIkzsHF8KhnWrBiZZXrq78ePyGvGNQMWPtmrMch2fB98qHmwHnNeA2gH5EN65SueKvFY7KBglYAgl-QZzmPJVQM4Cm5EK0UgkO7IebdGuzsnZ2oDXZas880DtTSvES3s3nxjvY42RV7invfY2HpHMsX_emXHZ1-_zqudDzM-1wEeppw62ekuSTdzoftc_JksFPGF_fvJfn24f3X60_VzZePn6-vbionAZaqZ13fMBwUKNli0zkQ0iFqLhRnTaM7rTuuHXKUA5OMwyBUe6sGaQUTXTeIS_L2pLs_3M7YOwxLspPZJz_btJpovfk3E_zObOPRaNU0UuoiQE8CLvmydTAhJmsYdJIbxoA3siCv73uk-OOAeTGzzw6nyQaMh2y4krIDLkAUVD2oxZwTDudJGJg7B81ozg6aOwcN46Y4WCpf_r3Iue7BsgJcnQAs5zx6TCY7j8Fh7xO6xfTR_7fJH8l1sYA</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Dordevic, Jasmina</creator><creator>Jovanović, Bojana</creator><general>Elsevier Inc</general><general>The Franklin Institute. Published by Elsevier Ltd</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>3HK</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6788-307X</orcidid></search><sort><creationdate>20230101</creationdate><title>Dynamical analysis of a stochastic delayed epidemic model with lévy jumps and regime switching</title><author>Dordevic, Jasmina ; Jovanović, Bojana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c500t-d18d41ef70756e48c035cee923721449899829ce2e5f15120f376b7f5a31388f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dordevic, Jasmina</creatorcontrib><creatorcontrib>Jovanović, Bojana</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>NORA - Norwegian Open Research Archives</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of the Franklin Institute</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dordevic, Jasmina</au><au>Jovanović, Bojana</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamical analysis of a stochastic delayed epidemic model with lévy jumps and regime switching</atitle><jtitle>Journal of the Franklin Institute</jtitle><addtitle>J Franklin Inst</addtitle><date>2023-01-01</date><risdate>2023</risdate><volume>360</volume><issue>2</issue><spage>1252</spage><epage>1283</epage><pages>1252-1283</pages><issn>0016-0032</issn><eissn>1879-2693</eissn><eissn>0016-0032</eissn><abstract>•Study of the epidemic model for SARS-CoV-2 virus spread in a stochastic framework.•Transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process.•Dynamics of model that contains white and telegraph noise, Lévy jump and time delay.•Mathematical tool for constructing strategies for the control of diseases.•Numerical simulations based on the real data illustrate the main theoretical results.
In this paper a delayed stochastic SLVIQR epidemic model, which can be applied for modeling the new coronavirus COVID-19 after a calibration, is derived. Model is constructed by assuming that transmission rate satisfies the mean-reverting Ornstain-Uhlenbeck process and, besides a standard Brownian motion, another two driving processes are considered: a stationary Poisson point process and a continuous finite-state Markov chain. For the constructed model, the existence and uniqueness of positive global solution is proven. Also, sufficient conditions under which the disease would lead to extinction or be persistent in the mean are established and it is shown that constructed model has a richer dynamic analysis compared to existing models. In addition, numerical simulations are given to illustrate the theoretical results.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>36533206</pmid><doi>10.1016/j.jfranklin.2022.12.009</doi><tpages>32</tpages><orcidid>https://orcid.org/0000-0001-6788-307X</orcidid><oa>free_for_read</oa></addata></record> |
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title | Dynamical analysis of a stochastic delayed epidemic model with lévy jumps and regime switching |
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