Endemic cattle diseases present financial and welfare issues to farmers, however for many of these diseases, farmers’ differing perspectives and knowledge can hinder and prevent uptake of control measures.  In addition, farming systems are highly variable and what may be an effective control for one farm may not be well suited for another.  BioSS is working with researchers from Scotland’s Rural College (SRUC) to design a framework that combines data from epidemiology, applied agricultural economics, and behavioural science in a multi-disciplinary approach to biosecurity.  As part of this exercise, BioSS has developed livestock trading models to quantify how disease control measures can yield meaningful reductions in on-farm prevalence and reductions in financial losses from livestock disease.

Mathematical modelling has been a key research theme in BioSS for decades, but it has consistently been demanding to convert this methodological expertise into consultancy activity.  Given the focus on large scale modelling in the current SRP, BioSS has sought to develop a consultancy approach for mathematical modelling.  This case study describes one of the first of these approaches. 

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While it is well-known that endemic livestock diseases, such as Johne’s disease, lead to production losses on farms, farmers’ attitudes to controlling these diseases vary.  These attitudes include the perceptions: that Johne’s disease is not damaging enough to warrant intervention; that common controls, such as animal testing, are ineffective (see item 2.2.2) and negatively impact controls for more important diseases; that success can only be achieved if all farms participate; and that the benefits of achieving control do not outweigh the costs required.

Using detailed cattle movement data, we have developed a dynamic, agent-based model of the Scottish cattle trading industry in which individual farm trading behaviours are determined by their current business requirements.  Using this model, we have shown the adaptive nature of cattle trading and how individual business requirements can potentially hinder otherwise valuable controls.  In addition, exploiting the heterogeneous nature of the real-world system, novel targeted disease controls making use of trade to supplement traditional control measures have been shown to be particularly effective in reducing endemic disease burden.  The results indicate that controls that are currently deemed ineffective, such as low sensitivity animal tests, can be effective in reducing prevalence when intelligently combined with novel trade-based controls.  In collaboration with SRUC scientists, this systems-level model will be adapted and tailored to model the specifics of on-farm dynamics of Johne’s disease.  The outputs from this adapted model will be used to communicate the benefits of controlling diseases such as Johne’s disease to farmers.  The model is intended to be integrated into an interactive dashboard for farmers to use to calculate the costs of Johne’s disease under current trading and biosecurity practices, plus the potential benefits from adopting new biosecurity control measures.

This work was done in collaboration with Mike Hutchings and Ross Davidson at SRUC and was funded under the Scottish Government's Strategic Research Programme for environment, agriculture and food.