The use of trade data to predict the source and spread of food safety outbreaks: An innovative mathematical modelling approach. (September 2019)
- Record Type:
- Journal Article
- Title:
- The use of trade data to predict the source and spread of food safety outbreaks: An innovative mathematical modelling approach. (September 2019)
- Main Title:
- The use of trade data to predict the source and spread of food safety outbreaks: An innovative mathematical modelling approach
- Authors:
- Garre, Alberto
Fernandez, Pablo S.
Brereton, Paul
Elliott, Chris
Mojtahed, Vahid - Abstract:
- 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 withAbstract: 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. Graphical abstract: Unlabelled Image Highlights: A mathematical model has been developed to describe the global food trade network. The network structure has a significant impact on the movement of food products. The network structure is product-dependent, so they must be analysed individually. The model has been applied to identify the possible origin of a recent outbreak. It can be a tool for regulatory agencies, aiding in risk prediction and mitigation … (more)
- Is Part Of:
- Food research international. Volume 123(2019)
- Journal:
- Food research international
- Issue:
- Volume 123(2019)
- Issue Display:
- Volume 123, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 123
- Issue:
- 2019
- Issue Sort Value:
- 2019-0123-2019-0000
- Page Start:
- 712
- Page End:
- 721
- Publication Date:
- 2019-09
- Subjects:
- Mathematical modelling -- Food safety -- Surveillance systems -- Network theory
Food -- Analysis -- Periodicals
Food industry and trade -- Periodicals
Food industry and trade -- Canada -- Periodicals
Food Technology -- Periodicals
Food -- Periodicals
Food-Processing Industry -- Periodicals
Aliments -- Industrie et commerce -- Périodiques
Aliments -- Industrie et commerce -- Canada -- Périodiques
Aliments -- Recherche -- Périodiques
Food industry and trade
Canada
Periodicals
Electronic journals
664.005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09639969 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.foodres.2019.06.007 ↗
- Languages:
- English
- ISSNs:
- 0963-9969
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3982.120000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 10999.xml