Modelling the spread of a viral infection in equine populations managed in Thoroughbred racehorse training yards.

A Monte Carlo model that simulates the management life cycle of a horse population in training on a Thoroughbred flat racing yard (i.e. stable) was developed for computer implementation. Each horse was characterised by several state variables. Discrete events at the horse level were triggered stochastically to reflect uncertainty about some input assumptions and heterogeneity of the horse population in a particular yard. This mathematical model was subsequently used to mimic the spread of equine influenza (EI) within a typical yard following the introduction of one or several infectious horses. Different scenarios were simulated to demonstrate the value of strategies for preventing outbreaks of EI. Under typical UK management conditions and vaccination protocols, the model showed that EI would propagate and that the timing of vaccination in connection with the racing season and the arrival of new horses was a critical factor. The predicted outcomes (based on published characteristics of one EI vaccine) suggested that vaccination in mid-December with boosters in June and September was a viable and successful strategy in preventing the spread of EI in a training establishment.