Tackling bottlenecks to the use of data for enhanced Johne's Disease control

Johne's disease has been rated by dairy farmers in the UK as the number one endemic disease affecting productivity. It causes chronic illness, which progressively, worsens and can spread throughout the herd. To tackle the disease effectively, vet practices and farmers need to optimise the use of existing data, whilst also making evidence-based risk assessments about their herds.

Our multi-disciplinary project aims to make use of existing data sources and trial environmental sampling for risk assessments with the aim of enhancing Johne's Disease control. Our specific questions are:
1. What factors explain the differences in the success of Johne's control between herds? (WP1)
2. What are the major bottlenecks to farmer and veterinarian engagement in using disease test data and what are the solutions? (WP1)
3. Why are some veterinary practices markedly more successful in controlling the disease in their client base than other practices? (WP1)
4. What measures undertaken by farmers are most likely to be associated with successful control in infection? (WP1)
5. What risk factors identified in on-farm risk assessments are associated with the presence of infection? (WP2)
6. What level of confidence would environmental sampling give as a means of estimating the probability of infection or freedom from infection? (WP2)

This proposal brings together a uniquely multidisciplinary team from across the UK to tackle Johne's disease. It combines a farmer (Abi Reader, project partner) with veterinary expertise in Johne's disease control (Peter Orpin, sub-contractor), specialists in data management (James Hanks, subcontractor), a stakeholder engagement specialist (David Rose), a veterinary epidemiologist (Abel Ekiri) and a veterinary microbiologist (Nick Wheelhouse). Within Northern Ireland AHWNI leads on the control of Johne's Disease. The proposal will work in each country of the United Kingdom. Strain (subcontractor and project partner), CEO of AHWNI has a long-standing involvement with Johne's Disease control through managing the NI control programme and his involvement in the all-island (Ireland) Technical Working Group for the infection. Findings from this study will identify relevant herd risk factors and biomarkers to use for prediction of Johne's disease risk. Subsequently, in the next phase after the 12 months, these data will be used to develop prediction models and a practical and cost-effective surveillance tool for Johne's risk assessment at the herd level.

Johne's disease is an infectious wasting condition of cattle and other ruminants caused by Mycobacterium avium subspecies paratuberculosis (Map). The disease progressively damages the intestines of affected animals and can eventually result in severe weight loss, loss of condition and infertility.

Through the main UK milk recording organisations there are now thousands of herds across the UK that have the necessary routine data at the individual animal level. While there are growing numbers of examples where herds have brought the disease down to low levels, the routine interpretation and use of these data by vets and farmers has been sporadic and often the existing data are under-utilised, in part because of a lack of know-how. Improving the use and demonstrating the value of existing data has potential to enhance farmer decision-making with respect to Johne's disease control at the farm level. Recruitment to Johne's control programmes can be hampered by the associated costs of whole herd testing. Novel herd level testing that provides farmers with a simple, cost-effective means of identifying infection or providing assurance of infection freedom would greatly improve herd engagement in control programmes. Preliminary evidence from other countries suggests that farm environmental sampling may provide an effective way of identifying infected herds (Lavers, 2013). However this approach has not been validated within the UK context.

Our multi-disciplinary project aims to make use of existing data sources by bringing together experts, vet practices, and farmers, whilst also trialling environmental sampling for risk assessments with the aim of enhancing Johne's Disease control. Subsequently, in the next phase after the 12 months, these data will be used to develop prediction models and a practical and cost-effective surveillance tool for Johne's risk assessment at the herd level.