Equine influenza causes disease that, while similar to human infection caused by Influenza A H1N1 and H3N2, at least in terms of the pathogenesis, transmission and population level phylogeny, is markedly different in terms of seasonality in that there are no obvious consistent winter peaks of transmission.
The talk will focus around a programme of work directed at better understanding of the epidemiology and control of equine influenza infection. The programme has used stochastic versions of SEIR models, parameterised from experimental and epidemiological data of the disease in the natural host. Optimising the use of vaccination is of particular interest. Empirical data have allowed the extension of the basic models into those assessing the impact of virus selection (antigenic drift) and explain how rather small differences observed experimentally scale up to substantial population level effects. More recent developments of explore the extension of a basic model into a one involved variably connected patches. Practical issues which face all those working in similar fields relating to parameterisation of more complex stochastic epidemiological models will be discussed and comparison will be made with other epidemiological work.