Farmers, veterinarians and other animal health managers in the livestock sector are currently missing information on prevalence and burden of non-EU-regulated contagious animal diseases. They are in need of adequate tools for risk assessment and for prioritisation of control measures for these diseases.
The DECIDE project will develop data-driven decision support tools, which present (i) robust and early signals of disease emergence and options for diagnostic confirmation; and (ii) options for controlling the disease along with their implications in terms of disease spread, economic burden and animal welfare.
DECIDE will focus on respiratory and gastro-intestinal syndromes in the three most important terrestrial livestock species (pigs, poultry, cattle) and on growth reduction and mortality in salmonids, the most important aquaculture species. For each of these, we will (i) identify the stakeholder needs; (ii) determine the burden of disease and costs of control measures; (iii) develop data sharing frameworks based on federated data access and federated learning; (iv) build multivariate and multi-level models for creating an early warning system. Together, all of this will form the decision support tools to be integrated in existing farm management systems wherever possible and to be evaluated in several pilot implementations in farms across Europe.
To achieve these ambitious goals, DECIDE has assembled a unique multidisciplinary consortium of experts in veterinary epidemiology and diagnostics, data science, mechanistic and predictive modelling, economics, animal welfare and social sciences. The consortium also includes several representatives of stakeholders with ample access to data, such as national animal health agencies, providers of veterinary services or farm equipment suppliers.
The results of DECIDE will lead to improved decisions on disease control to increase animal health and welfare and protect human health and the food chain in Europe and beyond.
Fields of science
Call for proposal
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Funding SchemeRIA - Research and Innovation action
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