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Foodborne transmission of norovirus: mechanism modelling, seasonality and policy implications (2020 System Dynamics Applications Award paper)

Lane, D. C., Husemann, E., Holland, D. and Khaled, A. (2022) Foodborne transmission of norovirus: mechanism modelling, seasonality and policy implications (2020 System Dynamics Applications Award paper). System Dynamics Review. ISSN 1099-1727

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To link to this item DOI: 10.1002/sdr.1719

Abstract/Summary

The article describes a study of the foodborne transmission mechanisms for norovirus. It was undertaken for the U.K. Food Standards Agency and received the System Dynamics Society's 2020 “System Dynamics Applications Award”. The article opens with descriptions of norovirus, the organisational context and the aims of the study. The first phase involved the construction of a large, fully formulated SD simulation model which included person-to-person mechanisms and, newly built, food-related mechanisms for norovirus transmission. The group modelling process and the model structure are described. The model's existence demonstrated that enough was known about foodborne mechanisms to create an explicit and carefully documented representation that specialists recognised, understood, and accepted. Additionally, a framework for analysing the model's parameters—some currently unknown—helped organise FSA thinking on future research and potential policy levers. A second phase used mathematical analysis of a simplified SD model to assess the relative scale of the foodborne effects. In terms of contributions, this generated insights into possible sources of seasonality and insights into whether the most effective leverage points in the system lay solely within the remit of the FSA or were also within the remits of other government departments. The article closes by summarising the findings and then exploring their policy implications and recording the client's reactions to them.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > Business Informatics, Systems and Accounting
ID Code:106670
Publisher:Wiley

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