From 2005 to 2010 many large nationwide foodborne illness outbreaks were associated with commercially distributed food. In some of these outbreaks the source was not immediately identifiable because product distribution information was incomplete or difficult to collect or interpret and the outbreak vehicle could not be traced to its source. The primary objective of this research is to characterize and propose how data could be more systematically defined and collected throughout the food supply chain to more rapidly determine the source of foodborne illness outbreaks. This research proposes a conceptual framework for addressing the food traceability challenge. While specific technical solutions exist, none are capable of satisfying all needs of the various food supply chains. What has been missing is a common conceptual framework within which a variety of solutions can co-exist. Any such framework must preserve flexibility, scalability and adaptability. Individual technical solutions must be capable of satisfying requirements of the food industry while simplifying and improving aggregation and interpretation of key data for both industry and regulators faced with outbreak investigations. To understand the development of the conceptual framework, traceback methods by state regulatory agencies were used to complement traditional epidemiological cluster investigation methods and confirmed hazelnuts as the vehicle in a multi-state outbreak of E. coli O157:H7 infections. This outbreak investigation demonstrates the use of product traceback data to rapidly test an epidemiological hypothesis. This conceptual framework was validated during an outbreak of 6 cases of Salmonella Newport infection, which identified fresh blueberries as the cause. Initially, traditional traceback methods involving the review of invoices and bills-of-lading were used to attempt to identify the source of the outbreak. When these methods failed, novel traceback methods were used. This investigation demonstrates the emerging concepts of Critical Tracking Events (CTEs) and Key Data Elements (KDE) related for food product tracing. The use of these shopper-cased data and the event data that were queried by investigators demonstrates the potential utility of consciously designed CTEs and KDEs at critical points in the supply chain to better facilitate product tracing.
University of Minnesota Ph.D. dissertation. December 2013. Major: Environmental Health. Advisor: Craig Hedberg. 1 computer file (PDF); ix, 143 pages.
Miller, Benjamin David.
The use of critical tracking events and key data elements to improve the traceability of food throughout the supply chain to reduce the burden of foodborne illnesses.
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