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<p>Food safety remains a core priority in the European Union, where dense trade networks demand rapid detection and coordinated response. The Rapid Alert System for Food and Feed (RASFF) enables near-real-time exchange of hazard information among EU member states and associated countries. This study analyses 14,562 RASFF notifications from January 2022 to December 2024, combining descriptive statistics with a role-aware directed network constructed from origin, distribution, and destination fields. The resulting network shows a clear core–periphery structure; it is weakly connected (single undirected component), sparse yet locally cohesive (121 nodes, 869 edges, density = 0.05, average clustering = 0.48). Centrality profiles indicate high-accessibility nodes (closeness), decentralised mediation with uniformly low betweenness (multiple routing paths rather than single brokers), and context-dependent influence (eigenvector). These patterns support network analysis as a preliminary screening tool to prioritise surveillance, cross-border coordination, and follow-up assessment before deploying finer-grained risk models. Addressing gaps in prior work that relied on partial exports, we use complete extraction for the study window and release a freely accessible, analysis-ready dataset for 2022–2024 with full role fields, alongside an integrated resource harmonising recent and historical RASFF notifications. The findings provide actionable guidance for improving surveillance coverage, shortening inter-module pathways, strengthening local cohesion, and enhancing transparency and cooperation in EU agri-food safety governance.</p>

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Network analysis as a preliminary screening tool for food safety risk assessment using European Union RASFF notifications from 2022 to 2024

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月20日

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  • Shinyclimensa C,
  • Parthiban A

摘要

Food safety remains a core priority in the European Union, where dense trade networks demand rapid detection and coordinated response. The Rapid Alert System for Food and Feed (RASFF) enables near-real-time exchange of hazard information among EU member states and associated countries. This study analyses 14,562 RASFF notifications from January 2022 to December 2024, combining descriptive statistics with a role-aware directed network constructed from origin, distribution, and destination fields. The resulting network shows a clear core–periphery structure; it is weakly connected (single undirected component), sparse yet locally cohesive (121 nodes, 869 edges, density = 0.05, average clustering = 0.48). Centrality profiles indicate high-accessibility nodes (closeness), decentralised mediation with uniformly low betweenness (multiple routing paths rather than single brokers), and context-dependent influence (eigenvector). These patterns support network analysis as a preliminary screening tool to prioritise surveillance, cross-border coordination, and follow-up assessment before deploying finer-grained risk models. Addressing gaps in prior work that relied on partial exports, we use complete extraction for the study window and release a freely accessible, analysis-ready dataset for 2022–2024 with full role fields, alongside an integrated resource harmonising recent and historical RASFF notifications. The findings provide actionable guidance for improving surveillance coverage, shortening inter-module pathways, strengthening local cohesion, and enhancing transparency and cooperation in EU agri-food safety governance.