2020 OPEN SESSION OF THE STANDING TECHNICAL COMMITTEE OF THE EUFMD
CONCLUSIONS AND RECOMMENDATIONS FROM THE OPEN SESSION 2020 Session 1: Measuring animal movements and drivers for FAST disease risk mapping Conclusions • • •
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Predictive modelling of animal mobility has an important role in supporting decision-making. However, modelling is only one of the tools to assist in the decision process. Reliable and regular input data needs to be collected and aggregated, to simplify the complexity of systems, and to determine targeted key risk locations/areas where efficient control measures can be implemented for FAST diseases. For efficient control of livestock diseases in areas with limited data and resources, any available livestock movement data is essential to inform targeting interventions, and needs to be prioritized to complement the inherent local risk of transmission related to environmental and ecological factors. Methods and decision-support tools can contribute to risk-based disease surveillance and control, in particular in scarce data environments where animal mobility has a major role in disease spread. These methods can consider: - The application of collaborative platforms using a “bring the code to the data” approach to perform analysis of animal mobility in settings where data confidentiality and regulations preventing data availability and sharing is an issue; - The use of participative qualitative risk assessment frameworks to define and identify hotspots for risk of introduction and spread of transboundary infectious animal disease at national level; - A digital and interactive interface to facilitate data collection and mapping of epidemiologically significant locations such as markets, abattoirs, and border points, in addition to seasonal and quantified animal movement flows; - The design of sentinel surveillance approaches for early warning using animal transport data, and targeting livestock markets to complement existing farm risk-based and syndromic surveillance approaches. The key challenges are mainly associated with: 1) lack of investment in animal identification and traceability systems, 2) adequate data collection, availability and quality and 3) technical competencies and skills for adequate uptake and implementation.
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