T3-08 Foodborne Contamination Consequence Modeling

Monday, July 23, 2012: 3:45 PM
Room 553 (Rhode Island Convention Center)
David Luedeke, Battelle, Columbus, OH
David Buchta, Battelle, Columbus, OH
Brian Hawkins, Battelle, Columbus, OH
Jessica Cox, Department of Homeland Security, Aberdeen, MD
Mark Whitmire, Department of Homeland Security, Aberdeen, MD
David McGarvey, Department of Homeland Security, Aberdeen, MD
Introduction:  Intentional foodborne contaminations have been attempted in the United States and abroad.  Several online tools, software packages, and approaches have been developed and are available for evaluating potential vulnerabilities within the food supply chain. However, there remains a need for robust, risk-based consideration of various threats to the U.S. food supply (from ‘farm-to-fork’).

Purpose:  As part of the Chemical Terrorism Risk Assessment (CTRA), a DHS CSAC funded program, Battelle has developed a foodborne contamination consequence model that estimates human health consequences of various intentional food contamination scenarios.

Methods:  Knowledge from published literature and subject matter expertise on agent stability, food processing technologies, and supply chain vulnerabilities were applied to evaluate the impact of chemical threats on public health. Foodborne contamination scenarios were  mathematically simulated from the point of contamination (e.g., a storage silo), through food processing (e.g., pasteurization), packaging or bottling, distribution to retail or quick service restaurant (QSR) outlets, to points of sales of contaminated product, consumer and QSR preparation methods (e.g., cooking), and consumption patterns. A recall or public announcement component considered the time to the appearance of illnesses or injuries, and applied a rate of information diffusion to calculate the amount of contaminated product removed from retail outlets and consumer homes.

Results:  Contaminant-specific data, such as that for dose-response, hydrolysis rate, temperature-dependent decay, and time to symptom onset, were utilized to provide estimates of potential consequences in terms of injuries of varying severity. Results were generated, illustrating the effect of various contamination points and mitigation steps on public health consequences.

Significance:  These modeling capabilities can be applied to prioritize investments in mitigating a food contamination event and have other potential applications such as determining optimal, risk-based contaminant sampling schemes for naturally occurring or accidental contamination events.