Table 1.
Mean epidemic impact for epidemics seeded within a given county for the true clustered location data (T) and for an equivalent dataset with random farm locations (R) within each county; epidemic impact is also given for random farm locations but with the model reparameterized to provide a best fit to epidemics simulated on the true location data (RR)
| Region |
Epidemic impact, T |
Epidemic impact, R |
Epidemic impact, RR |
| Cumbria, UK | 2,505 (2,121–2,976) | 1,765 (101–2,287) | 2,429 (1,432–3,054) |
| Devon, UK | 519 (27–1,998) | 190 (31–561) | 545 (34–981) |
| Clwyd, UK | 679 (475–1,131) | 388 (52–798) | 641 (148–1,355) |
| Aberdeenshire, UK | 80 (20–263) | 25 (16–41) | 76 (21–121) |
| Lancaster, PA | 1,284 (954–1,634) | 75 (20–216) | 1,197 (576–1,545) |
| Cuming, NE | 454 (443–461) | 441 (423–453) | 453 (437–463) |
| Wright/Humboldt, IA | 134 (78–171) | 121 (60–152) | 133 (75–165) |
| Franklin, TX | 244 (20–318) | 118 (15–182) | 220 (16–304) |
Values in brackets give the 95% prediction intervals; all results are from 10,000 stochastic simulations.