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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18299

Title: Modeling individual heterogeneity in the acquisition of recurrent infections: an application to parvovirus B19
Authors: Abrams, Steven
Hens, Niel
Issue Date: 2015
Citation: BIOSTATISTICS, 16 (1), p. 129-142
Abstract: In recent years, it has been shown that individual heterogeneity in the acquisition of infectious diseases has a large impact on the estimation of important epidemiological parameters such as the (basic) reproduction number. Therefore, frailty modeling has become increasingly popular in infectious disease epidemiology. However, so far, using frailty models, it was assumed infections confer lifelong immunity after recovery, an assumption which is untenable for non-immunizing infections. Our work concentrates on refining the existing frailty models to encompass complexities of waning immunity and consequently recurrent infections while accounting for individual heterogeneity. Univariate and shared gamma frailty models, frequently used in practice, and correlated gamma frailty models that have proven to be a valuable alternative are considered. We show that incorrectly assuming lifelong immunity when applying frailty models introduces substantial bias in the estimation of both the baseline hazard and the frailty parameters, and consequently of the basic and effective reproduction number. We illustrate our work using cross-sectional serological data on parvovirus B19 (PVB19) from Belgium for which the link with varicella zoster virus is exploited.
Notes: [Abrams, Steven; Hens, Niel] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Hens, Niel] Univ Antwerp, Vaccine & Infect Dis Inst, Ctr Hlth Econ Res & Modeling Infect Dis, B-2610 Antwerp, Belgium. [Hens, Niel] Univ Antwerp, Vaccine & Infect Dis Inst, Ctr Evaluat Vaccinat, B-2610 Antwerp, Belgium.
URI: http://hdl.handle.net/1942/18299
DOI: 10.1093/biostatistics/kxu031
ISI #: 000347417500012
ISSN: 1465-4644
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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