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dc.contributor.authorMann, Peter Stephen
dc.contributor.authorSmith, V.A.
dc.contributor.authorMitchell, John B. O.
dc.contributor.authorDobson, Simon Andrew
dc.date.accessioned2021-08-04T16:30:09Z
dc.date.available2021-08-04T16:30:09Z
dc.date.issued2021-08-03
dc.identifier.citationMann , P S , Smith , V A , Mitchell , J B O & Dobson , S A 2021 , ' Symbiotic and antagonistic disease dynamics on clustered networks using bond percolation ' , Physical Review. E, Statistical, nonlinear, and soft matter physics , vol. 104 , no. 2 , 024303 . https://doi.org/10.1103/PhysRevE.104.024303en
dc.identifier.issn1539-3755
dc.identifier.otherPURE: 275040462
dc.identifier.otherPURE UUID: 68f940d8-e913-4993-8597-bce2a6b49ca8
dc.identifier.otherORCID: /0000-0002-0379-6097/work/98196435
dc.identifier.otherORCID: /0000-0002-0487-2469/work/98196639
dc.identifier.otherORCID: /0000-0001-9633-2103/work/98196733
dc.identifier.otherScopus: 85112379273
dc.identifier.urihttp://hdl.handle.net/10023/23717
dc.description.abstractIn this paper we introduce a description of the equilibrium state of a bond percolation process on random graphs using the exact method of generating functions. This allows us to find the expected size of the giant connected component (GCC) of two sequential bond percolation processes in which the bond occupancy probability of the second process is modulated (increased or decreased) by a node being inside or outside of the GCC created by the first process. In the context of epidemic spreading this amounts to both an antagonistic partial immunity and a synergistic partial coinfection interaction between the two sequential diseases. We examine configuration model networks with tunable clustering. We find that the emergent evolutionary behavior of the second strain is highly dependent on the details of the coupling between the strains. Contact clustering generally reduces the outbreak size of the second strain relative to unclustered topologies; however, positive assortativity induced by clustered contacts inverts this conclusion for highly transmissible disease dynamics.
dc.format.extent9
dc.language.isoeng
dc.relation.ispartofPhysical Review. E, Statistical, nonlinear, and soft matter physicsen
dc.rightsCopyright © 2021 American Physical Society. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the final published version of the work, which was originally published at https://doi.org/10.1103/PhysRevE.104.024303.en
dc.subjectComplex networksen
dc.subjectPercolation theoryen
dc.subjectEpidemic spreadingen
dc.subjectCoinfectionen
dc.subjectClustered networksen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectRA0421 Public health. Hygiene. Preventive Medicineen
dc.subjectT-NDASen
dc.subject.lccQA75en
dc.subject.lccRA0421en
dc.titleSymbiotic and antagonistic disease dynamics on clustered networks using bond percolationen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.contributor.institutionUniversity of St Andrews.Sir James Mackenzie Institute for Early Diagnosisen
dc.contributor.institutionUniversity of St Andrews.School of Chemistryen
dc.contributor.institutionUniversity of St Andrews.Office of the Principalen
dc.contributor.institutionUniversity of St Andrews.St Andrews Centre for Exoplanet Scienceen
dc.contributor.institutionUniversity of St Andrews.Centre for Biological Diversityen
dc.contributor.institutionUniversity of St Andrews.Centre for Higher Education Researchen
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews.Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews.School of Biologyen
dc.contributor.institutionUniversity of St Andrews.EaSTCHEMen
dc.contributor.institutionUniversity of St Andrews.Biomedical Sciences Research Complexen
dc.identifier.doihttps://doi.org/10.1103/PhysRevE.104.024303
dc.description.statusPeer revieweden


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