Modelling and predicting low count child asthma hospital readmissions using General Additive Models

Copyright © 2013 Don Vicendese et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Daily paediatric asthma readmissions within 28 days are a good example of a low count time series and not easily amenable to common time series methods used in studies of asthma seasonality and time trends. We sought to model and predict daily trends of childhood asthma readmissions over time in Victoria, Australia. Methods: We used a database of 75,000 childhood asthma admissions from the De-partment of Health, Victoria, Australia in 1997-2009. Daily admissions over time were modeled using a semi parametric Generalized Additive Model (GAM) and by sex and age group. Predictions were also esti