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A study to identify factors associated with the detection of new TB breakdowns via abattoir surveillance in GB. - SE3133

Description
Bovine tuberculosis (bTB) currently costs the UK taxpayer around £100 million per year in surveillance testing and compensation. Despite this, the incidence of bTB breakdowns (i.e. herds in which movement restrictions are enforced due to suspected bTB infection) has increased dramatically over the past 30 years. Detection of some cases in slaughterhouses is important, in particular in areas where testing is only conducted on farms every four years. However, in the past couple of years the proportion of bTB breakdowns disclosed by slaughterhouse surveillance (as opposed to routine skin testing) has increased significantly. The reasons for this are not at all clear, and elucidating why these cases are being missed will provide important information, not only for policy makers trying to control the spread of the disease, but also to help improve our knowledge about the biological mechanisms involved in bTB spread, and how these interact with the routine testing structure.

This project aims to tackle these issues in various ways. Although herds are tested routinely, it is not necessarily the case that individual animals are routinely tested. One possible reason why more cases are being disclosed at the SLH is if a higher proportion of infected animals are not being tested due to trade movements. We will determine what proportion of the increase in slaughterhouse detection might be due to differences in the degree to which animals are skin tested during routine surveillance and pre-movement skin testing.

Our specific objectives include:
1) Collation and assessment of the utility of all available slaughterhouse data on bTB diagnoses, from a range of different sources, including the TB50 system, the TB System and the TB Laboratory Management System. We will also assess the utility of lesion data collected by the Food Standards Agency.

2) Identification of factors associated with detecting bTB by finding visible lesions in slaughterhouses using a detailed and longitudinal statistical framework. We will do this by linking all available current and historic cattle movement and testing datasets in order to extract demographic information, testing history and location/movement information of individual cattle. Dependent on the output of Objective 1, we will also combine this with more detailed slaughterhouse surveillance information.

3) Assessment of the degree of change in the level of undisclosed infection in the cattle population over time, using a longitudinal statistical transmission modelling approach. We will use this model to identify factors associated with the observed increase in the detection of infected cattle in slaughterhouses. We will account for the geographical and temporal variations in background incidence in these analyses, as this may drive many of the underlying patterns. If possible, we will evaluate the performance of some individual slaughterhouses over time.

4) We will use data that are available from slaughterhouses in order to determine risk factors for detecting bTB in other farmed livestock species, such as sheep, goats and pigs.
Objective
1) Assessment and collation of all available slaughterhouse data, but with substantial focus on historical lesion data, currently held in three sources: the TB50 system (pre-2007), The TB System (2007–2010), and the Laboratory Management System (LIMS; post-2010). In addition, we will also assess the utility of the lesion data collected by the Food Standards Agency.

2) Identification of factors associated with disclosing bTB via visible lesions detection in slaughterhouses using a longitudinal statistical regression framework. We will do this by linking the CTS, Vebus/TBMaster and VetNet/SAM data sets in order to extract demographic information, testing history and location/movement information. Dependent on the output of Objective 1, we will also combine this with more detailed slaughterhouse surveillance information. Repeated measures and explicit spatio-temporal structure will be incorporated using random effects.

3) Assessment of the degree of change in the level of undisclosed infection in the cattle population over time, using a longitudinal statistical transmission modelling approach. We will use this model to elucidate factors associated with the observed increase in slaughterhouse detection. The model will include an explicit spatio-temporal correlation structure in order to account for geographical and temporal variations in background risk-of-infection, which is critical in understanding the underlying data, and also (if possible) to monitor the performance of individual slaughterhouses over time.

4) We will use data from slaughterhouses to determine risk factors for detecting bTB in other farmed livestock species, such as sheep, goats and pigs.
Time-Scale and Cost
From: 2013

To: 2016

Cost: £323,596
Contractor / Funded Organisations
University of Cambridge
Keywords
Animal Diseases              
Animal Health              
Control              
Plants and Animals              
Tuberculosis              
Fields of Study
Animal Health