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2008-10-01Zeitschriftenartikel DOI: 10.25646/454
Automatic outbreak detection algorithm versus electronic reporting system.
dc.contributor.authorStraetemans, Masja
dc.contributor.authorAltmann, Doris
dc.contributor.authorEckmanns, Tim
dc.contributor.authorKrause, Gérard
dc.date.accessioned2018-05-07T13:32:19Z
dc.date.available2018-05-07T13:32:19Z
dc.date.created2009-12-15
dc.date.issued2008-10-01none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/re3skmKiGsOVk/PDF/28oC2K00Th7k.pdf
dc.identifier.urihttp://edoc.rki.de/176904/529
dc.description.abstractTo determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA signals and 4,427 reports of outbreaks caused by Campylobacter spp. or norovirus during 2005-2006 in Germany. Local health departments reported local outbreaks with higher sensitivity and positive predictive value than did AODAs.eng
dc.language.isoeng
dc.publisherRobert Koch-Institut, Infektionsepidemiologie
dc.subjectHumanseng
dc.subjectGastroenteritis/epidemiologyeng
dc.subjectGermany/epidemiologyeng
dc.subjectPopulation Surveillance/methodseng
dc.subjectDisease Outbreaks/statistics & numerical dataeng
dc.subjectDisease Notification/statistics & numerical dataeng
dc.subjectCaliciviridae Infections/epidemiologyeng
dc.subjectNoroviruseng
dc.subjectAlgorithmseng
dc.subjectCampylobacter Infections/epidemiologyeng
dc.subject.ddc610 Medizin
dc.titleAutomatic outbreak detection algorithm versus electronic reporting system.
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-1003540
dc.identifier.doihttp://dx.doi.org/10.25646/454
local.edoc.container-titleEmerging Infectious Diseases
local.edoc.fp-subtypeArtikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttp://cdc.gov/eid/content/14/10/1610.htm
local.edoc.container-publisher-nameCenters for Disease Control and Prevention
local.edoc.container-volume14
local.edoc.container-issue10
local.edoc.container-year2008

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