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dc.contributor.authorHuang, CYen_US
dc.contributor.authorSun, CTen_US
dc.contributor.authorHsieh, JLen_US
dc.contributor.authorChen, YMAen_US
dc.contributor.authorLin, HLen_US
dc.date.accessioned2014-12-08T15:18:13Z-
dc.date.available2014-12-08T15:18:13Z-
dc.date.issued2005-10-01en_US
dc.identifier.issn0037-5497en_US
dc.identifier.urihttp://dx.doi.org/10.1177/0037549705061519en_US
dc.identifier.urihttp://hdl.handle.net/11536/13175-
dc.description.abstractThe authors propose a small-world network model that combines cellular automata with the social mirror identities of daily-contact networks for purposes of performing epidemiological simulations. The social mirror identity concept was established to integrate human long-distance movement and daily visits to fixed locations. After showing that the model is capable of displaying such small-world effects as low degree of separation and relatively high degree of clustering on a societal level, the authors offer proof of its ability to display R-o properties-considered central to all epidemiological studies. To test their model, they simulated the 2003 severe acute respiratory syndrome (SARS) outbreak.en_US
dc.language.isoen_USen_US
dc.subjectsocial mirror identityen_US
dc.subjectsmall-world network modelen_US
dc.subjectmultiagent systemen_US
dc.subjectcellular automataen_US
dc.subjectpublic health policyen_US
dc.subjectnetwork-based epidemic simulationsen_US
dc.titleA novel small-world model: Using social mirror identities for epidemic simulationsen_US
dc.typeArticleen_US
dc.identifier.doi10.1177/0037549705061519en_US
dc.identifier.journalSIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONALen_US
dc.citation.volume81en_US
dc.citation.issue10en_US
dc.citation.spage671en_US
dc.citation.epage699en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000234408100001-
dc.citation.woscount20-
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