Seasonal patterns have been found in a remarkable range of health
conditions, including birth defects, respiratory infections and
cardiovascular disease. Accurately estimating the size and timing of
seasonal peaks in disease incidence is an aid to understanding the
causes and possibly to developing interventions. With global warming
increasing the intensity of seasonal weather patterns around the world,
a review of the methods for estimating seasonal effects on health is
timely.
This is the first book on statistical methods for seasonal data written
for a health audience. It describes methods for a range of outcomes
(including continuous, count and binomial data) and demonstrates
appropriate techniques for summarising and modelling these data. It has
a practical focus and uses interesting examples to motivate and
illustrate the methods. The statistical procedures and example data sets
are available in an R package called 'season'.