Although inference for β and γ is difficult for real applications (see below), it turns out that making inference on R 0 (as a function of β and γ) is rather more straightforward. Heffernan et al. [151] summarise various methods for estimating R 0 from epidemiological data based on endemic equilibrium, average age at infection, epidemic final size, and intrinsic growth rate [114, 152, 153] . However, these methods all rely on observing a complete epidemic, and hence for real-time analysis during an epidemic, we must make strong assumptions concerning the number of currently undetected infections. An example of inference for R 0 based upon complete epidemic data is provided by Stegeman et al. [154] , where data from the 2003 outbreak of High Pathogenicity Avian Influenza H7N7 is fitted to a chain-binomial model using a generalised linear model.