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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8401

Title: Modelling multisera data: The estimation of new joint and conditional epidemiological parameters
Authors: HENS, Niel
Theeten, H.
Van Damme, P.
Beutels, P.
Issue Date: 2008
Citation: STATISTICS IN MEDICINE, 27(14). p. 2651-2664
Abstract: Testing humans for infectious diseases is often done by assessing the presence or absence of disease-specific antibodies in serum samples. For feasibility and economical reasons, these sera are often tested for more than one antigen. Studying diseases with similar transmission routes can govern new insights for disease dynamics. We use flexible marginal and conditional models to model multisera data on the Varicella-Zoster virus and the Parvo B19-virus in Belgium. Next form the derivation of the age-dependent marginal force of infection (FOI), we introduce new epidemiological parameters: the age-dependent joint and conditional FOI. These parameters allow us to study the association among the occurrence and acquisition of both infections. Furthermore, we show how to test for association and whether the infection-specific age-dependent FOI curves are proportional and consequently whether separable mixing in the population holds. Copyright (C) 2007 John Wiley & Sons, Ltd.
Notes: Hasselt Univ, Ctr Stat, B-3590 Diepenbeek, Belgium. Univ Antwerp, Ctr Evaluat Vaccinat Epidemiol & Community Med, B-2000 Antwerp, Belgium.
URI: http://hdl.handle.net/1942/8401
DOI: 10.1002/sim.3089
ISI #: 000256764300010
ISSN: 0277-6715
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

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