A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort

This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection...

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Bibliographic Details
Published in:Statistical methods in medical research 2011-10, Vol.20 (5), p.551-570
Main Authors: Mwambi, H, Ramroop, S, White, LJ, Okiro, EA, Nokes, DJ, Shkedy, Z, Molenberghs, G
Format: Article
Language:English
Subjects:
Cohort Studies
Female
Humans
Immunity
Infection
Male
Measurement
Parameters
Respiratory diseases
Respiratory Syncytial Viruses - isolation & purification
Respiratory Tract Infections - complications
Respiratory Tract Infections - epidemiology
Respiratory Tract Infections - physiopathology
Rotavirus
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Summary:This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection with respiratory syncytial virus. The force of infection and the recovery rate or per capita loss of infection are the parameters of interest. However, because of the limitation arising from the study design and subsequently, the data generated only the force of infection is estimable. The problem of dealing with time-varying disease parameters is also addressed in the article by fitting piecewise constant parameters over time via the GLM approach. The current model formulation is based on that published in White LJ, Buttery J, Cooper B, Nokes DJ and Medley GF. Rotavirus within day care centres in Oxfordshire, UK: characterization of partial immunity. Journal of Royal Society Interface 2008; 5: 1481-1490 with an application to rotavirus transmission and immunity.
ISSN:0962-2802
1477-0334
DOI:10.1177/0962280210385749