Date Published: June 8, 2018
Publisher: Public Library of Science
Author(s): Trevelyan J. McKinley, Debby Lipschutz-Powell, Andrew P. Mitchell, James L. N. Wood, Andrew J. K. Conlan, Willem F. de Boer.
Slaughterhouse surveillance through post-mortem meat inspection provides an important mechanism for detecting bovine tuberculosis (bTB) infections in cattle herds in Great Britain (GB), complementary to the live animal skin test based programme. We explore patterns in the numbers of herd breakdowns detected through slaughterhouse surveillance and develop a Bayesian hierarchical regression model to assess the associations of animal-level factors with the odds of an infected animal being detected in the slaughterhouse, allowing us to highlight slaughterhouses that show atypical patterns of detection. The analyses demonstrate that the numbers and proportions of breakdowns detected in slaughterhouses increased in GB over the period of study (1998–2013). The odds of an animal being a slaughterhouse case was strongly associated with the region of the country that the animal spent most of its life, with animals living in high-frequency testing areas of England having on average 21 times the odds of detection compared to animals living in Scotland. There was also a strong effect of age, with animals slaughtered at > 60 months of age having 5.3 times the odds of detection compared to animals slaughtered between 0–18 months of age. Smaller effects were observed for cattle having spent time on farms with a history of bTB, quarter of the year that the animal was slaughtered, movement and test history. Over-and-above these risks, the odds of detection increased by a factor of 1.1 for each year of the study. After adjustment for these variables, there were additional variations in risk between slaughterhouses and breed. Our framework has been adopted into the routine annual surveillance reporting carried out by the Animal Plant Health Agency and may be used to target more detailed investigation of meat inspection practices.
Bovine tuberculosis (bTB) is the most economically important disease of livestock currently affecting cattle in Great Britain (GB), estimated to cost the UK government >£100 million per year in direct costs . Slaughterhouse surveillance of cattle, where every animal slaughtered is examined for signs of disease, is an essential part of the control program in GB, particularly in low-risk areas. Historically, the proportion of bTB incidents disclosed at the slaughterhouse has been lower in GB than other high-risk countries such as Ireland . A recent increase in this proportion  is of concern to policy makers, as it may equally well reflect a reduction in the effectiveness of skin testing as an increase in the effectiveness of slaughterhouse surveillance. The rates of bTB submissions from different slaughterhouses vary considerably, but will depend on various factors including the effectiveness of meat inspection but also the risk profile of the input population. In this paper we explore these patterns in detail and identify risk factors for the disclosure of bTB incidents in herds through slaughterhouse tracebacks. However, our primary aim is to develop a robust statistical tool that can identify atypical slaughterhouses for further investigation, to contribute towards a better understanding of the effectiveness of slaughterhouse surveillance in GB.
Bovine TB is a notifiable infectious disease in GB. Surveillance data recording the results of all testing and slaughterhouse cases are collated by the Animal and Plant Health Agency (APHA) in the Sam database and linked with cattle movement records from the Cattle Tracing System (CTS). Data downloads from the Sam system were used to construct local databases using PostgreSQL (https://www.postgresql.org/) with subsequent analysis and modelling carried out using the open-source statistical language R .
We describe an increase in both the absolute number and proportion of breakdowns disclosed through slaughterhouse surveillance in Great Britain between 1998 and 2013. This increase remains even when accounting for changes in confirmation rates and changes in the proportion of herds subject to different testing frequencies.