Journal article
Modelling seasonal variations in the age and incidence of Kawasaki disease to explore possible infectious aetiologies
VE Pitzer, D Burgner, C Viboud, L Simonsen, V Andreasen, CA Steiner, M Lipsitch
Proceedings of the Royal Society B Biological Sciences | ROYAL SOC | Published : 2012
Abstract
The average age of infection is expected to vary during seasonal epidemics in a way that is predictable from the epidemiological features, such as the duration of infectiousness and the nature of population mixing. However, it is not known whether such changes can be detected and verified using routinely collected data. We examined the correlation between the weekly number and average age of cases using data on pre-vaccination measles and rotavirus. We show that age-incidence patterns can be observed and predicted for these childhood infections. Incorporating additional information about important features of the transmission dynamics improves the correspondence between model predictions and..
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Awarded by National Institute of General Medical Sciences
Funding Acknowledgements
V.E.P. was supported by training grant T32 AI07535 and the RAPIDD programme of the Science & Technology Directorate, Department of Homeland Security, and the Fogarty International Center, National Institutes of Health. V.E.P. and M.L. were supported by cooperative agreement 5U01GM076497 and 5U54GM088558-02 (Models of Infectious Disease Agent Study) from the National Institutes of Health. D.B. was supported by a National Health and Medical Research Council Career Development Award and by the Victorian Government's Operational Infrastructure Support Programme. V.A. was supported by grant 271-07-0555 from the Danish Medical Research Council. We thank Christina Mills Astley for helpful comments, Jessica Jacobs for assistance with data retrieval, and all the states that provided hospitalization-discharge data to support the Healthcare Cost and Utilization Project. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health.