7. Time Series Analysis

Analysis of epidemic time series is a large endeavor because of the richness of dynamical patterns and a plentitude of historical data (Rohani & King, 2010). A wide range of tools are used, some of which are borrowed from mainstream statistics and other of which are custom-made. The classic “mainstream” methods belong to two categories: the so-called time-domain and frequency-domain methods. The autocorrelation function and ARIMA models belong to the former class and spectral analysis, and the periodogram belongs to the latter. Hybrid time/frequency methods have become increasingly prominent in the form of wavelet analysis because it allows the study of changes in disease dynamics through time (Grenfell et al., 2001).