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http://hdl.handle.net/10261/174096
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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Fernández-Gracia, Juan | es_ES |
dc.contributor.author | Onnela, Jukka-Pekka | es_ES |
dc.contributor.author | Barnett, Michael L. | es_ES |
dc.contributor.author | Eguíluz, Víctor M. | es_ES |
dc.contributor.author | Christakis, Nicholas A. | es_ES |
dc.date.accessioned | 2019-01-15T09:53:42Z | - |
dc.date.available | 2019-01-15T09:53:42Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2017 (2017) | es_ES |
dc.identifier.isbn | 978-3-319-60239-4 | - |
dc.identifier.isbn | 978-3-319-60240-0 (online) | - |
dc.identifier.uri | http://hdl.handle.net/10261/174096 | - |
dc.description | International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation.-- Lee D., Lin YR., Osgood N., Thomson R. (eds). | es_ES |
dc.description.abstract | Antibiotic-resistant organisms, an increasing source of morbidity and mortality, have a natural reservoir in hospitals, and recent estimates suggest that almost 2 million people develop hospital-acquired infections each year in the US alone. We investigate the temporal network of transfers of Medicare patients across US hospitals over a 2-year period to learn about the possible role of hospital-to-hospital transfers of patients in the spread of infections. We analyze temporal, geographical, and topological properties of the transfer network and show that this network may serve as a substrate for the spread of infections. Finally, we study different strategies for the early detection of incipient epidemics on the temporal transfer network as a function of activation time of a subset of sensor hospitals. We find that using approximately 2% of hospitals as sensors, chosen based on their network in-degree, with an activation time of 7 days results in optimal performance for this early warning system, enabling the early detection of 80% of the C. difficile. cases with the hospitals in the sensor set activated for only a fraction of 40% of the time. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer Nature | es_ES |
dc.rights | closedAccess | es_ES |
dc.subject | Nosocomial Infection | es_ES |
dc.subject | Medicare Patient | es_ES |
dc.subject | Temporal Network | es_ES |
dc.subject | Patient Transfer | es_ES |
dc.subject | Network Neighbor | es_ES |
dc.title | Spread of Pathogens in the Patient Transfer Network of US Hospitals | es_ES |
dc.type | comunicación de congreso | es_ES |
dc.identifier.doi | 10.1007/978-3-319-60240-0_33 | - |
dc.description.peerreviewed | Peer reviewed | es_ES |
dc.relation.publisherversion | https://doi.org/10.1007/978-3-319-60240-0_33 | es_ES |
dc.relation.csic | Sí | es_ES |
oprm.item.hasRevision | no ko 0 false | * |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | es_ES |
item.languageiso639-1 | en | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.openairetype | comunicación de congreso | - |
Aparece en las colecciones: | (IFISC) Libros y partes de libros |
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