Periodic Reporting for period 3 - DECIDE (Data-driven control and prioritisation of non-EU-regulated contagious animal diseases)
Período documentado: 2024-07-01 hasta 2025-06-30
Farmers, veterinarians and other animal health managers in the livestock sector need adequate tools for risk assessment and for prioritisation of control measures for endemic contagious animal diseases.
The DECIDE project develops data-driven decision support tools, which present robust and early signals of disease emergence and options for control.
DECIDE focuses on respiratory and gastro-intestinal syndromes in pigs, poultry, and cattle; and on growth reduction and mortality in salmonids. For each of these species, we aim to (i) develop data sharing frameworks; (ii) identify the stakeholder needs; (iii) determine the burden of disease and costs of control measures; (iv) build multivariate and multi-level models for creating early warning systems. These elements will be included in decision support tools and to be evaluated in several pilot implementations across Europe.
To achieve these goals, DECIDE has assembled a unique multidisciplinary consortium of experts which includes several stakeholders with ample access to data, such as national animal health agencies, providers of veterinary services or farm equipment suppliers.
The DECIDE project develops data-driven decision support tools, which present robust and early signals of disease emergence and options for control.
DECIDE focuses on respiratory and gastro-intestinal syndromes in pigs, poultry, and cattle; and on growth reduction and mortality in salmonids. For each of these species, we aim to (i) develop data sharing frameworks; (ii) identify the stakeholder needs; (iii) determine the burden of disease and costs of control measures; (iv) build multivariate and multi-level models for creating early warning systems. These elements will be included in decision support tools and to be evaluated in several pilot implementations across Europe.
To achieve these goals, DECIDE has assembled a unique multidisciplinary consortium of experts which includes several stakeholders with ample access to data, such as national animal health agencies, providers of veterinary services or farm equipment suppliers.
Initially, data sharing agreements with data providers were made bilaterally to ensure access to relevant data streams. A Joint Controller Agreement was set up by those project partners that share data from sources outside the project. Guidelines and training material were developed on data stewardship in veterinary epidemiology to facilitate data access and re-use. Species-specific ontologies for data integration were created and updated when new data became available. Federated data access through both centralized and decentralized setups were implemented and tested using formatted veterinary diagnostic data of cattle and pigs aligned with species-specific ontology. The federated access infrastructure is scalable and adaptable across DECIDE use cases, through successful execution of cross-species (horizontal) and within-species (vertical) federated queries.
Various approaches were utilised to assess the need for, usefulness and use of data-driven tools in general and those developed within DECIDE, utilising social science concepts and methodologies, including focus group discussions and surveys. As some of the tools are potentially made public, consumer perceptions were also investigated in surveys to consider contextual factors of the use of the data tool. Two scenario- and game-based online experiments were developed to test the effect of design features of the tools on stakeholder decision making, regarding effectiveness and experience (i.e. alert levels and colours, comparisons to other nearby farms, type of information shown in the tool).
Frameworks for the biomass and animal health loss calculations were developed in collaboration with the GBADs (Global Burden of Animal Diseases) programme. The use of loss-expenditure frontiers to map out routes to more economically efficient disease control for endemic disease was explored. Frontiers position every farm relative to high performers and therefore provide a benchmarking system that could be integrated into decision-making tools. This also provides a structure for peer-to-peer knowledge transfer from high performing farms to others. Case studies were carried out for a specific endemic disease or disease complex in each of the four species.
An inventory within the consortium showed that a combination of welfare and disease data is rarely available. Only for poultry and veal calves such data were available and analysed. For pigs, the welfare quality protocol is applied to obtain such data. In addition, expert elicitation is applied for the welfare impact of BRD in dairy calves and will also be applied for porcine respiratory disease complex (PRDC) in pigs.
Multivariate dynamic linear models for early detection of diseases were built for data relating to each species in the project and multi-level (i.e. hierarchical) models for salmon and calves. Using the EMULSION software package, mechanistic models were developed for bovine respiratory disease (BRD) in calves and several respiratory pathogens in pigs. Software was developed to link monitoring data for early disease detection to the model that simulates disease spread and control options. The model is now validated on field data from calves and evaluated with stakeholders to verify its effectiveness for decision support.
Tool prototypes for technology demonstration, stakeholder co-creation, and data analysis innovation have been developed in DECIDE. A full description of their context, targeted user, data sources, tool architecture, user interface, content, and functions has been created. The sustainability aspects and tool developers’ plans for the work with their tools in the remainder of the project are assessed. Tool developers are supported in establishing a business plan for the tools.
Many activities were carried out to communicate about DECIDE and to ensure that its results were widely disseminated. This included the publication of practice abstracts and training materials in local languages, the project website and newsletters. A cluster event was organised with participants from related projects to discuss data re-use and stakeholder needs in the development and implementation of decision support tools for animal health professionals.
Various approaches were utilised to assess the need for, usefulness and use of data-driven tools in general and those developed within DECIDE, utilising social science concepts and methodologies, including focus group discussions and surveys. As some of the tools are potentially made public, consumer perceptions were also investigated in surveys to consider contextual factors of the use of the data tool. Two scenario- and game-based online experiments were developed to test the effect of design features of the tools on stakeholder decision making, regarding effectiveness and experience (i.e. alert levels and colours, comparisons to other nearby farms, type of information shown in the tool).
Frameworks for the biomass and animal health loss calculations were developed in collaboration with the GBADs (Global Burden of Animal Diseases) programme. The use of loss-expenditure frontiers to map out routes to more economically efficient disease control for endemic disease was explored. Frontiers position every farm relative to high performers and therefore provide a benchmarking system that could be integrated into decision-making tools. This also provides a structure for peer-to-peer knowledge transfer from high performing farms to others. Case studies were carried out for a specific endemic disease or disease complex in each of the four species.
An inventory within the consortium showed that a combination of welfare and disease data is rarely available. Only for poultry and veal calves such data were available and analysed. For pigs, the welfare quality protocol is applied to obtain such data. In addition, expert elicitation is applied for the welfare impact of BRD in dairy calves and will also be applied for porcine respiratory disease complex (PRDC) in pigs.
Multivariate dynamic linear models for early detection of diseases were built for data relating to each species in the project and multi-level (i.e. hierarchical) models for salmon and calves. Using the EMULSION software package, mechanistic models were developed for bovine respiratory disease (BRD) in calves and several respiratory pathogens in pigs. Software was developed to link monitoring data for early disease detection to the model that simulates disease spread and control options. The model is now validated on field data from calves and evaluated with stakeholders to verify its effectiveness for decision support.
Tool prototypes for technology demonstration, stakeholder co-creation, and data analysis innovation have been developed in DECIDE. A full description of their context, targeted user, data sources, tool architecture, user interface, content, and functions has been created. The sustainability aspects and tool developers’ plans for the work with their tools in the remainder of the project are assessed. Tool developers are supported in establishing a business plan for the tools.
Many activities were carried out to communicate about DECIDE and to ensure that its results were widely disseminated. This included the publication of practice abstracts and training materials in local languages, the project website and newsletters. A cluster event was organised with participants from related projects to discuss data re-use and stakeholder needs in the development and implementation of decision support tools for animal health professionals.
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.
Data science:
Guidelines, training materials and contract templates developed in DECIDE facilitate access and re-use of animal health data and improve good data management. The species-specific ontologies and code for federated access to data are publicly available.
Modelling:
Multivariate dynamic linear models are applied to longitudinal data from salmon, cattle, pigs and poultry for early detection of disease. Mechanistic models in EMULSION are developed and validated for BRD in calves and pathogens of the PRDC in pigs. The transmission and the effectiveness of disease control options are modelled. Based on the multidimensional burden, disease control can be optimized.
Decision support tools:
The tools developed in DECIDE were initially focusing on specific animal species in specific countries. However, several tools are already adapted such that they can be used for other species and countries. The deliverables can serve as a framework for the design and evaluation of data-driven decision support tools in co-creation with the users.
Burden of animal disease:
The methodology for determining the disease burden can be applied to any animal species and any disease. The loss-expenditure frontiers can be used as a benchmark tool to support peer-to-peer knowledge transfer from high performing farms to those not achieving good results. The multidimensionality of including welfare and medicine use in the burden of disease is an innovative approach that recognises externalities from livestock production supporting sustainable and ethical management of animals.
Social Sciences:
The insight gained on psychological and social preconditions of the use of data tools and the quantitative approaches to investigate stakeholders’ drivers, barriers and willingness-to-implement and -use data tools can be used for other animal species but also for users of such tools outside veterinary medicine.
Data science:
Guidelines, training materials and contract templates developed in DECIDE facilitate access and re-use of animal health data and improve good data management. The species-specific ontologies and code for federated access to data are publicly available.
Modelling:
Multivariate dynamic linear models are applied to longitudinal data from salmon, cattle, pigs and poultry for early detection of disease. Mechanistic models in EMULSION are developed and validated for BRD in calves and pathogens of the PRDC in pigs. The transmission and the effectiveness of disease control options are modelled. Based on the multidimensional burden, disease control can be optimized.
Decision support tools:
The tools developed in DECIDE were initially focusing on specific animal species in specific countries. However, several tools are already adapted such that they can be used for other species and countries. The deliverables can serve as a framework for the design and evaluation of data-driven decision support tools in co-creation with the users.
Burden of animal disease:
The methodology for determining the disease burden can be applied to any animal species and any disease. The loss-expenditure frontiers can be used as a benchmark tool to support peer-to-peer knowledge transfer from high performing farms to those not achieving good results. The multidimensionality of including welfare and medicine use in the burden of disease is an innovative approach that recognises externalities from livestock production supporting sustainable and ethical management of animals.
Social Sciences:
The insight gained on psychological and social preconditions of the use of data tools and the quantitative approaches to investigate stakeholders’ drivers, barriers and willingness-to-implement and -use data tools can be used for other animal species but also for users of such tools outside veterinary medicine.