Assessment of antemortem tests used in the control of an outbreak of tuberculosis in llamas (Lama glama).

An outbreak of tuberculosis (TB) caused by Mycobacterium bovis in a llama herd is described. Over a 25-month period, a total of 70 llamas were selected for postmortem examination using four distinct criteria: clinical suspicion of disease (15 animals), positive tuberculin skin test result (three animals), antibody positive using a novel serological test (Rapid Test, 54 animals) and elective cull (five animals). Some animals qualified on more than one criterion. Gross lesions of TB were detected in 15 animals, with lung and lymph node lesions consistently observed. Samples were collected from 14 of 15 animals with visible lesions as well as those with no visible lesions, for histopathology and mycobacterial culture. All 14 llamas with visible lesions had caseonecrotic granulomatous lesions associated with acid-fast bacteria and variable mineralisation, and M bovis was isolated from 13. There were no histopathological lesions of TB in llamas with no grossly visible lesions, and M bovis was not isolated from any of these. The predictive value of suspicious gross lesions at postmortem examination was therefore high in the herd. Molecular typing results indicated that the outbreak was caused by a single strain likely to have originated from a local reservoir, probably cattle or wildlife. Antemortem indicators of infection assisted control of the outbreak, but no single test accurately identified all TB cases. Visible lesions were detected in nine of 15 llamas with clinical suspicion of disease, in two of three that had positive tuberculin skin test results and in 10 of 54 that were antibody positive; there was none (zero out of five) in llamas that were electively culled.

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.