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dc.contributor.authorYañez, Andrea
dc.contributor.authorDuggan, Jim
dc.contributor.authorJilani, Musfira
dc.contributor.authorConnolly, Maire
dc.contributor.authorHayes, Conor
dc.date.accessioned2017-11-07T11:25:40Z
dc.date.available2017-11-07T11:25:40Z
dc.date.issued2017-10-01
dc.identifier.citationYanez, Andrea, Duggan, Jim, Hayes, Conor, Jilani, Musfira, & Connolly, Maire. (2017). PandemCap: decision support tool for epidemic management. Paper presented at the VAHC 2017 (8th workshop on Visual Analytics in Healthcare) - Affiliated with IEEE VIS 2017, Phoenix, Arizona. DOI: 10.13025/S8QW7Men_IE
dc.identifier.urihttp://hdl.handle.net/10379/6953
dc.description.abstractPandemics or high impact epidemics are one of the biggest threats facing humanity today. While a complete elimination of the occurrence of such threats is improbable, it is possible to contain their impact by efficient management which in turn depends on effective decision-making. In the event of a pandemic the data flows are enormous and pose severe cognitive overload to the public health decision-makers. In this context, this paper presents PandemCap, an innovative decision support tool that can be used by the public health officials for making better and well informed decisions in the event of pandemics or high impact epidemics. PandemCap provides an interactive, flexible platform to public health decision-makers by making extensive use of techniques from the domains of visual analytics and epidemic modeling. In addition, the tool also allows for the study of the impact of various interventions or control measures such as the use of vaccines, anti-virals, hospital beds, and ventilators.en_IE
dc.description.sponsorshipThis publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight). Part of the research was conducted by the PANDEM project which has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no 652868). The authors also want to thank Andrea Barraza-Urbina for her comments on our work.en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherNUI Galwayen_IE
dc.relation.ispartofVAHC 2017 (8th workshop on Visual Analytics in Healthcare) - Affiliated with IEEE VIS 2017en
dc.subjectPandemCapen_IE
dc.subjectDecision support toolen_IE
dc.subjectEpidemic managementen_IE
dc.titlePandemCap: decision support tool for epidemic managementen_IE
dc.typeConference Paperen_IE
dc.date.updated2017-11-07T11:11:07Z
dc.identifier.doi10.13025/S8QW7M
dc.local.publishedsourcehttps://doi.org/10.13025/S8QW7M
dc.description.peer-reviewedpeer-reviewed
dc.internal.rssid12774351
dc.local.contactConor Hayes, Information Technology, School Of Engineering &, Informatics, Nui Galway. 5077 Email: conor.hayes@nuigalway.ie
dc.local.copyrightcheckedNo
dc.local.versionACCEPTED
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