Investigating Gaps For Novel Animal Health Surveillance Data Within Scotland

Introduction: Sensors have become ubiquitous in our current world and the livestock farming sector offers multiple research avenues for the application of sensor technology, from early disease detection to virtual fencing. Animal health surveillance in Scotland currently relies on post-mortem examinations of animals and on data derived from laboratory submitted samples. Sensor-derived syndromic surveillance of livestock has been identified as a gap in Scotland’s current animal health surveillance capabilities. Real-time data from on-farm herds has the potential to underpin improved production and endemic disease detection and the earlier identification and investigation of potential outbreaks. Using the data journeys approach, the aim of this project is to elucidate the conceptual journey of thermal imagery and drone-derived data from farm to policy. This approach aims to situate data across interconnected sites of practice, highlighting the movement of data in and between sites and exposing areas of potential ‘data friction’. The term ‘data friction’ is used to describe the complex factors (political, ethical, legal, social and economic) that come together to slow down and restrict data generation, movement and use. Materials and methods: To investigate potential barriers to taking sensor-derived data from the farm and utilizing this data to develop actionable animal health policy at the state level, a preliminary ‘data journeys’ exercise was undertaken to map stakeholders and sites of practice through which data is collected, transformed, stored, managed and used. From this map, stakeholders were identified and engaged to participate in qualitative interviews to gauge concerns and attitudes towards precision and smart farming uptake, data sharing, data protection regulations, perceptions of data sharing and of algorithms in animal health decision making. Results: Qualitative interviews were undertaken with stakeholders from commercial, academic, policy, legal, farming and animal health technology sectors to gather information concerning five main areas: (i) background and general understanding of sensor-derived data and precision livestock farming; (ii) position on data use and access; (iii) position on data usage; (vi) data storage and privacy implications; and (v) other considerations. A thematic analysis was carried out to build a hypothesis/picture around what data is currently in use and where sensor-derived data could fit in the scheme of veterinary surveillance data in Scotland and further afield. The project identifies a realistic pathway for novel data within the Scottish and UK animal health surveillance landscape, ensuring its utility for multiple stakeholders. Discussion: Previous research has explored potential future scenarios with regards to trade policy, data collection and sharing, and resourcing for surveillance in order to better prepare a resilient surveillance model for Scotland post-Brexit. As we have now entered the post-Brexit era, it is of the utmost importance to not only research new technologies in the agricultural sector, but to ensure that these technologies are developed with future use and application in mind from the outset, fostering resilience at both the farm level and the surveillance level.