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Food Res Int. 2019 Sep;123:712-721. doi: 10.1016/j.foodres.2019.06.007. Epub 2019 Jun 6.

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

Author information

1
Departamento de Ingeniería de Alimentos y del Equipamiento Agrícola, Instituto de Biotecnología Vegetal, Universidad Politécnica de Cartagena (ETSIA), Paseo Alfonso XIII, 48, 30203 Cartagena, Spain. Electronic address: alberto.garre@upct.es.
2
Departamento de Ingeniería de Alimentos y del Equipamiento Agrícola, Instituto de Biotecnología Vegetal, Universidad Politécnica de Cartagena (ETSIA), Paseo Alfonso XIII, 48, 30203 Cartagena, Spain.
3
Institute for Global Food Security, School of Biological Sciences, Queen's University, Belfast, United Kingdom.

Abstract

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.

KEYWORDS:

Food safety; Mathematical modelling; Network theory; Surveillance systems

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