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Emerging risk identification in the food chain – A systematic procedure and data analytical options

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Date
2023-06
Author
Farkas, Zsuzsa
Országh, Erika
Engelhardt, Tekla
Zentai, Andrea
Süth, Miklós
Csorba, Szilveszter
Jóźwiak, Ákos
DOI link
10.1016/j.ifset.2023.103366
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Abstract
Systematic screening for risks emerging in the food chain is essential for the protection of consumer health, however, timely identification of risks is not a trivial task because of the data and information gaps. By creating automated or semi-automated algorithms, a large amount of information can be pre-processed which helps experts to filter for the actual emerging risks that need further assessment. The present study gives an overview on the possible data analytical approaches that can be used for emerging risk screening and presents a practically applicable process management system. By using these methods, 58 emerging risks classified into 10 topics have been identified in 2020 and 2021 with the focus on Hungary and the European Union. The main goal is to aid authorities and industry in preparedness and timely acting to avoid or mitigate future risks. Experiences and limitations of the system and future directions are also presented.
URI
http://hdl.handle.net/10832/4026
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  • National Laboratory of Infectious Animal Diseases, Antimicrobial Resistance, Veterinary Public Health and Food Chain Safety

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