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dc.contributor.authorScatà, Men
dc.contributor.authorDi Stefano, Alessandroen
dc.contributor.authorLio, Pietroen
dc.contributor.authorLa Corte, Aen
dc.date.accessioned2017-02-14T15:48:13Z
dc.date.available2017-02-14T15:48:13Z
dc.date.issued2016-11-16en
dc.identifier.issn2045-2322
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/262510
dc.description.abstractIn the real world, dynamic processes involving human beings are not disjoint. To capture the real complexity of such dynamics, we propose a novel model of the coevolution of epidemic and awareness spreading processes on a multiplex network, also introducing a preventive isolation strategy. Our aim is to evaluate and quantify the joint impact of heterogeneity and awareness, under different socioeconomic conditions. Considering, as case study, an emerging public health threat, Zika virus, we introduce a data-driven analysis by exploiting multiple sources and different types of data, ranging from Big Five personality traits to Google Trends, related to different world countries where there is an ongoing epidemic outbreak. Our findings demonstrate how the proposed model allows delaying the epidemic outbreak and increasing the resilience of nodes, especially under critical economic conditions. Simulation results, using data-driven approach on Zika virus, which has a growing scientific research interest, are coherent with the proposed analytic model.
dc.description.sponsorshipThis work was partially supported by the following Research Grant: Italian Ministry of University and Research - MIUR “Programma Operativo Nazionale Ricerca e Competitività 2007–2013” within the project “PON-03PE-00132-1” - Servify.
dc.languageengen
dc.language.isoenen
dc.publisherNature Publishing Group
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleThe Impact of Heterogeneity and Awareness in Modeling Epidemic Spreading on Multiplex Networks.en
dc.typeArticle
prism.endingPage13
prism.number37105en
prism.publicationDate2016en
prism.publicationNameScientific Reportsen
prism.startingPage1
prism.volume6en
dc.identifier.doi10.17863/CAM.7619
dcterms.dateAccepted2016-10-25en
rioxxterms.versionofrecord10.1038/srep37105en
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2016-11-16en
dc.contributor.orcidDi Stefano, Alessandro [0000-0003-4905-3309]
dc.contributor.orcidLio, Pietro [0000-0002-0540-5053]
dc.identifier.eissn2045-2322
rioxxterms.typeJournal Article/Reviewen


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International