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SIS reaction-diffusion model with risk-induced dispersal under free boundary

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dc.contributor.authorChoi, Wonhyung-
dc.contributor.authorLin, Zhigui-
dc.contributor.authorAhn, Inkyung-
dc.date.accessioned2022-09-23T07:41:07Z-
dc.date.available2022-09-23T07:41:07Z-
dc.date.created2022-09-23-
dc.date.issued2022-10-
dc.identifier.issn1468-1218-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/143726-
dc.description.abstractA spatial susceptible-infected-susceptible epidemic model with a free boundary, where infected individuals disperse non-uniformly, is investigated in this study. Spatial heterogeneity and movement of individuals are essential factors that affect pandemics and the eradication of infectious diseases. Our goal is to investigate the effect of a dispersal strategy for infected individuals, known as risk-induced dispersal (RID), which represents the motility of infected individuals induced by risk depending on whether they are in a high- or a low-risk region. We first construct the basic reproduction number and then understand the manner in which a nonuniform movement of infected individuals affects the spreading-vanishing dichotomy of a disease in a one-dimensional domain. We conclude that even though the infected individuals reside in a high-risk initial domain, the disease can be eradicated from the region if the infected individuals move with a high sensitivity of RID as they disperse. Finally, we demonstrate our results via simulations for a one-dimensional case. (C) 2022 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectPOSITIVE STEADY-STATE-
dc.subjectASYMPTOTIC PROFILES-
dc.subjectSPREADING SPEED-
dc.subjectLOGISTIC MODEL-
dc.subjectEPIDEMIC MODEL-
dc.subjectCOMPETITION MODEL-
dc.subjectTRAVELING-WAVES-
dc.subjectDYNAMICS-
dc.subjectDISEASE-
dc.subjectEQUATION-
dc.titleSIS reaction-diffusion model with risk-induced dispersal under free boundary-
dc.typeArticle-
dc.contributor.affiliatedAuthorChoi, Wonhyung-
dc.contributor.affiliatedAuthorAhn, Inkyung-
dc.identifier.doi10.1016/j.nonrwa.2022.103605-
dc.identifier.scopusid2-s2.0-85129277527-
dc.identifier.wosid000831269800001-
dc.identifier.bibliographicCitationNONLINEAR ANALYSIS-REAL WORLD APPLICATIONS, v.67-
dc.relation.isPartOfNONLINEAR ANALYSIS-REAL WORLD APPLICATIONS-
dc.citation.titleNONLINEAR ANALYSIS-REAL WORLD APPLICATIONS-
dc.citation.volume67-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryMathematics, Applied-
dc.subject.keywordPlusPOSITIVE STEADY-STATE-
dc.subject.keywordPlusASYMPTOTIC PROFILES-
dc.subject.keywordPlusSPREADING SPEED-
dc.subject.keywordPlusLOGISTIC MODEL-
dc.subject.keywordPlusEPIDEMIC MODEL-
dc.subject.keywordPlusCOMPETITION MODEL-
dc.subject.keywordPlusTRAVELING-WAVES-
dc.subject.keywordPlusDYNAMICS-
dc.subject.keywordPlusDISEASE-
dc.subject.keywordPlusEQUATION-
dc.subject.keywordAuthorFree boundary-
dc.subject.keywordAuthorRisk-induced dispersal-
dc.subject.keywordAuthorSpreading-vanishing dichotomy-
dc.subject.keywordAuthorSpreading speed-
dc.subject.keywordAuthorInfective disease-
dc.subject.keywordAuthorSpatial SIS model-
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과학기술대학 (응용수리과학부 데이터계산과학전공)
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