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Developing food chain templates for AMR risk assessment

Start date
2020
End date
2022
Objective
The FSA has funded several research projects to reinforce the evidence base for AMR in the food chain. However, specific tools are yet to be created using this information to aid in the quantitative risk assessment to determine the risk to consumers of AMR in the food chain. The proposed study will review the literature and use the information gathered (in addition to data from previous published FSA studies) to create a set of templates of risk of AMR within the chicken and lettuce supply chain. These templates will be focused on all the processing stages, and consultation with industry will be necessary in order to achieve a thorough understanding of the farm-to-fork processes. The models will be created in a user-editable form including graphical user interface and comprehensive annotation to allow for their adaption to new and emerging risks. The challenge is to develop flexible modules that can be used “off the shelf” with minimum to no modification needed once adapted. To facilitate their use by non-experts, the templates will include a user-friendly interface where users will be able to input important information into the model. They will also include comprehensive annotation and additional training materials, allowing for their adaptation to other food chains as well as new and emerging risks. The models should therefore also be flexible in terms of the training/input data that users can upload to assess risk. This work will enable the production of more efficient and reproducible AMR risk assessments, as relevant steps in the food chain are available "off the shelf” and will allow the FSA to facilitate collaborative working and inform more complex, multi-factorial risk assessments. The use of these models will also allow for better prioritisation of risk management interventions, and establishment of better food production techniques to limit the spread of AMR and promote good practice in the food chain.
Project source
View this project
Project number
FS307037