This quantity multiplied by the average duration of infectiousness of a farm (time from end of latency to culling) gives the reproduction number R 0j of the farm j. We divided the UK into 5 km squares and then calculated the average transmission risk of all farms in each square (local R 0 ). Figure 4 shows how geographic risk changed before and after 23 rd February for our best fit model conditioned on the first infection. The kernel shape has a major influence on the average risk distribution throughout the country. Figure 5 shows the corresponding risk maps for the estimates inferred from our best fit model conditioned on 23 rd February. A slightly higher risk is predicted after 31 st March by the model conditioned on 23 rd February due to the increase in the cattle infectivity after this date. The risk estimates after 23 rd February from the first set of models appear consistent with those obtained from the models conditioned on 23 rd February, though a rigorous statistical comparison is not appropriate. 