Attempts to control tuberculosis in cattle by removing infected badgers: constraints imposed by live test sensitivity.
When tuberculosis outbreaks have occurred in cattle in the UK, the Ministry of Agriculture, Fisheries and Food (MAFF) has culled badgers (Meles meles) to try to avert further outbreaks. To limit the number of badgers killed, MAFF assessed a possible new strategy (the 'live test strategy') that used a serological test to identify and remove infected badgers. However, because the test correctly identified only 41% of truly infected badgers, individuals were pooled according to the setts at which they were sampled. All badgers were culled at setts where one or more seropositive animals were caught. On average, 1.9±1.4 badgers were sampled at each sett. Using a simple model, it is shown that this level of sampling still gives a low (24-37%) probability of detecting infection at a given sett. Badger social groups typically occupy more than one sett. Setts were allocated to social groups by using Dirichlet tessellations and field signs to predict territory borders. On average, 3.3±2.8 badgers were sampled in each group. The model shows that this increase in sample size gives probabilities of detecting M. bovis in truly infected groups of 43-62%, which is still likely to be unacceptably low. Culling badgers according to the setts where they were trapped led to incomplete removal of social groups; some seronegative badgers were released in 61% of groups containing seropositive animals. As infection is clustered within groups, it is likely that some infected animals were released even though they tested seronegative. Incomplete removal might also cause social disruption that could accelerate the transmission of M. bovis between social groups. It is concluded that the live test strategy, as implemented, would be unlikely to reduce the overall prevalence of M. bovis infection in badgers, and thus the risk to cattle. Furthermore, the poor sensitivity of the serological test makes it unlikely that modifications to the live test protocol could increase its cost-effectiveness.