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Related Experiment Video

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Development of an Electrochemical DNA Biosensor to Detect a Foodborne Pathogen

Development of an Electrochemical DNA Biosensor to Detect a Foodborne Pathogen

Published on: June 3, 2018

Emerging risks identification on food and feed - EFSA.

, Terry Donohoe, Kenisha Garnett

EFSA Journal. European Food Safety Authority

|July 7, 2020

Summary

This summary is machine-generated.

The European Food Safety Authority

Keywords:

big data drivers of change emerging risks food systems horizon scanning prioritisation risk communication

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Area of Science:

Food safety science
Risk assessment methodologies
Emerging risk identification

Background:

The European Food Safety Authority (EFSA) has procedures for identifying emerging risks in food and feed.
A Standing Working Group on Emerging Risks (SWG-ER) collaborated with EFSA to review its Emerging Risks Identification (ERI) procedure.
The review identified strengths in expert networks but highlighted weaknesses in data handling and governance.

Purpose of the Study:

To evaluate EFSA's current Emerging Risks Identification (ERI) procedure.
To provide strategic direction for improving EFSA's approach to emerging risks.
To address identified weaknesses in data collection, analysis, and communication.

Main Methods:

Systematic review of EFSA's ERI methodologies and results.
Analysis of strengths and weaknesses of the existing procedure.
Expert consultation and collaborative review by the SWG-ER.

Main Results:

EFSA's ERI procedure effectively uses expert networks but lacks a systematic approach for weighting/ranking risks and clear governance.
Significant weaknesses were identified in data collection, analysis, integration, and the absence of a risk avoidance value estimation methodology.
There is an urgent need for improved communication strategies addressing data gaps, uncertainty, and risk perception.

Conclusions:

EFSA's ERI procedure requires revision to enhance transparency and communication.
Recommendations include adopting a food system-based approach with social science integration and developing horizon scanning protocols.
Improving data processing for big data analytics, implementing data validation, and fostering data sharing agreements are crucial for future risk identification.