The use of trade data to predict the source and spread of food safety outbreaks An innovative mathematical modelling approach

    Research output: Contribution to journalArticle


    View graph of relations

    Food is traded across the global markets to satisfy consumer demands, mainly from developed countries, for year-round access to a wide range of foods. This has resulted in an increasingly complex network of food trade and has made importing countries vulnerable to the spread of foodborne disease outbreaks originating from “foreign” food networks. Analysis of these networks can provide information on potential food safety risks and also on the potential spread of these risks through the food network in question. In this study, network theory has been used to analyse global trade. A mathematical model was developed enabling a simulation of the distribution of food products based on the publicly available data on international imports, exports and production provided by the Food and Agriculture Organization of the United Nations. Through numerical simulations we demonstrate, for the first time, the impact that the network structure has on the distribution of food products in terms of food safety risks. As a case study, a recent trans-national food safety incident was analysed, illustrating the potential application of the model in a foodborne pathogen outbreak. Using only the type of contaminated food and the countries where the outbreak was reported, the model was used to identify the most likely origin of the contaminated eggs, narrowing down the options to three countries (including the actual origin). Furthermore, it is used to identify those countries with significant food safety risks, due to imports of food produced in these three countries. The approach can help regulatory agencies and the food industry to design improved surveillance and risk mitigation actions against transnational food safety risks.


    • The use of trade data to predict the source and spread of food safety outbreaks An innovative mathematical modelling approach

      Rights statement: Copyright 2019 Elsevier. This manuscript is distributed under a Creative Commons Attribution-NonCommercial-NoDerivs License (, which permits distribution and reproduction for non-commercial purposes, provided the author and source are cited.

      Accepted author manuscript, 1 MB, PDF-document

      Embargo ends: 06/06/2020


    Original languageEnglish
    Pages (from-to)712-721
    JournalFood Research International
    Journal publication date01 Sep 2019
    Early online date06 Jun 2019
    Publication statusPublished - 01 Sep 2019

      Research areas

    • Food safety, Mathematical modelling, Network theory, Surveillance systems

    ID: 174145008