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

Abstract:

: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.

journal_name

Stat Methods Med Res

authors

Mwambi H,Ramroop S,White Lj,Okiro E,Nokes Dj,Shkedy Z,Molenberghs G

doi

10.1177/0962280210385749

subject

Has Abstract

pub_date

2011-10-01 00:00:00

pages

551-70

issue

5

eissn

0962-2802

issn

1477-0334

pii

20/5/551

journal_volume

20

pub_type

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