Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9528
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dc.contributor.authorOGUNJIMI, Benson-
dc.contributor.authorHENS, Niel-
dc.contributor.authorGOEYVAERTS, Nele-
dc.contributor.authorAERTS, Marc-
dc.contributor.authorVan Damme, Pierre-
dc.contributor.authorBeutels, Philippe-
dc.date.accessioned2009-04-29T12:51:06Z-
dc.date.issued2009-
dc.identifier.citationMATHEMATICAL BIOSCIENCES, 218(2). p. 80-87-
dc.identifier.issn0025-5564-
dc.identifier.urihttp://hdl.handle.net/1942/9528-
dc.description.abstractWith the aim to improve dynamic models for infections transmitted predominantly through non-sexual social contacts, we compared three popular model estimation methods in how well they fitted seroprevalence data and produced estimates for the basic reproduction number R0 and the effective vaccination level required for elimination of varicella. For two of these methods, interactions between age groups were parameterized using empirical social contact data whereas for the third method we used the current standard approach of imposing a simplifying structure on the ‘Who Acquires Infection From Whom’ (WAIFW) matrix. The first method was based on solving a set of differential equations to obtain an equilibrium value of the proportion of susceptibles. The second method was based on finding a solution for the age-specific force of infection using the formula of the mass action principle by means of iteration. Both solutions were contrasted with observed age-specific seroprevalence data. The best fit of the WAIFW matrix was obtained with contacts involving touching, and lasting longer than 15 min per day. Plausible values for R0 for varicella in Belgium ranged from 7.66 to 13.44. Both approaches based on empirical social contact data provided a better fit to seroprevalence data than the current standard approach.-
dc.description.sponsorshipThis study was made as part of ‘SIMID’, a strategic basic research project funded by the institute for the Promotion of Innovation by Science and Technology in Flanders (IWT), project number 060081. We also gratefully acknowledge support from IAP research Network P6/03 of the Belgian Government (Belgian Science Policy). The work benefited from discussions held as part of POLYMOD, a European Commission project funded within the Sixth Framework Programme, Contract No. SSP22-CT-2004-502084.-
dc.language.isoen-
dc.publisherElsevier Inc.-
dc.rights2009 Elsevier Inc. All rights reserved.-
dc.subject.otherDynamic model-
dc.subject.otherVaricella-
dc.subject.otherMass action-
dc.subject.otherAirborne infection-
dc.subject.otherWAIFW matrix-
dc.titleUsing empirical social contact data to model person to person infectious disease transmission: An illustration for varicella-
dc.typeJournal Contribution-
dc.identifier.epage87-
dc.identifier.issue2-
dc.identifier.spage80-
dc.identifier.volume218-
local.bibliographicCitation.jcatA1-
local.publisher.placeSTE 800, 230 PARK AVE, NEW YORK, NY 10169-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1016/j.mbs.2008.12.009-
dc.identifier.isi000265362200002-
dc.identifier.eissn1879-3134-
local.uhasselt.internationalyes-
item.accessRightsRestricted Access-
item.fullcitationOGUNJIMI, Benson; HENS, Niel; GOEYVAERTS, Nele; AERTS, Marc; Van Damme, Pierre & Beutels, Philippe (2009) Using empirical social contact data to model person to person infectious disease transmission: An illustration for varicella. In: MATHEMATICAL BIOSCIENCES, 218(2). p. 80-87.-
item.fulltextWith Fulltext-
item.validationecoom 2010-
item.contributorOGUNJIMI, Benson-
item.contributorHENS, Niel-
item.contributorGOEYVAERTS, Nele-
item.contributorAERTS, Marc-
item.contributorVan Damme, Pierre-
item.contributorBeutels, Philippe-
crisitem.journal.issn0025-5564-
crisitem.journal.eissn1879-3134-
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