It is instructive to compare our results with those of previous papers fitting simple models to influenza incidence data. Work by Xia et al. [15] used a simple single strain SIRS, but with a more detailed description of temporal variation in contact rate and loss of immunity post-recovery. In addition, the infection rate was described by the phenomenological term b I a g(S). Exponents of this type are well known to facilitate fitting [5] , but are hard to interpret. We note that both the form of this term and the non-exponentially distributed duration of immunity in that study affect epidemic attack rates as a function of transmissibility and the periodicity of epidemics, and hence may play an equivalent role to age structure and the incorporation of two subtypes in our model in allowing a good fit to the data.