Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14249
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dc.contributor.authorBOLLAERTS, Kaatje-
dc.contributor.authorAERTS, Marc-
dc.contributor.authorSHKEDY, Ziv-
dc.contributor.authorFAES, Christel-
dc.contributor.authorVan der Stede, Y.-
dc.contributor.authorBeutels, P.-
dc.contributor.authorHENS, Niel-
dc.date.accessioned2012-10-12T09:34:48Z-
dc.date.available2012-10-12T09:34:48Z-
dc.date.issued2012-
dc.identifier.citationSTATISTICAL MODELLING, 12 (5), p. 441-462-
dc.identifier.issn1471-082X-
dc.identifier.urihttp://hdl.handle.net/1942/14249-
dc.description.abstractThe use of threshold values in order to diagnose individual subjects as being 'susceptible' or 'infected or recovered/immune' for a specific infection is virtually always prone to false positive, false negative or inconclusive classifications. Such misclassifications might lead to biased estimates for epidemiological parameters, such as the prevalence and the force of infection. In this article, we propose to estimate these epidemiological parameters directly from antibody titres, using an underlying mixture model. The method is applied to estimate the Salmonella serological prevalence in pigs and the age-dependent force of infection using serological data on the Varicella-Zoster virus (VZV) in humans. The threshold and direct method are compared through a simulation study.-
dc.language.isoen-
dc.publisherSAGE PUBLICATIONS LTD-
dc.subject.otherforce of infection; mixture model; serological data; test misclassification; prevalence-
dc.subject.otherStatistics & Probability; force of infection; mixture model; serological data; test misclassification, prevalence-
dc.titleEstimating the population prevalence and force of infection directly from antibody titres-
dc.typeJournal Contribution-
dc.identifier.epage462-
dc.identifier.issue5-
dc.identifier.spage441-
dc.identifier.volume12-
local.format.pages22-
local.bibliographicCitation.jcatA1-
dc.description.notes[Bollaerts, K.] Sci Inst Publ Hlth, Brussels, Belgium. [Aerts, M.; Shkedy, Z.; Faes, C.; Hens, N.] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Aerts, M.; Shkedy, Z.; Faes, C.; Hens, N.] Katholieke Univ Leuven, Diepenbeek, Belgium. [Beutels, P.; Hens, N.] Univ Antwerp, Ctr Evaluat Vaccinat, Vaccine & Infect Dis Inst, Ctr Hlth Econ Res & Modeling Infect Dis, B-2020 Antwerp, Belgium. [Van der Stede, Y.] Vet & Agrochem Res Ctr, Brussels, Belgium.-
local.publisher.placeLONDON-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1177/1471082X12457495-
dc.identifier.isi000308652200003-
item.accessRightsRestricted Access-
item.validationecoom 2013-
item.fulltextWith Fulltext-
item.fullcitationBOLLAERTS, Kaatje; AERTS, Marc; SHKEDY, Ziv; FAES, Christel; Van der Stede, Y.; Beutels, P. & HENS, Niel (2012) Estimating the population prevalence and force of infection directly from antibody titres. In: STATISTICAL MODELLING, 12 (5), p. 441-462.-
item.contributorBOLLAERTS, Kaatje-
item.contributorAERTS, Marc-
item.contributorSHKEDY, Ziv-
item.contributorFAES, Christel-
item.contributorVan der Stede, Y.-
item.contributorBeutels, P.-
item.contributorHENS, Niel-
crisitem.journal.issn1471-082X-
crisitem.journal.eissn1477-0342-
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