A farm-to-fork stochastic simulation model of pork-borne salmonellosis in humans: Lessons for risk ranking

Paul McNamara, Gay Y. Miller, Xuanli Liu and David A. Barber
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Gay Y. Miller: Departments of Veterinary Pathobiology and Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, Urbana, IL 61802, Postal: Departments of Veterinary Pathobiology and Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, Urbana, IL 61802
Xuanli Liu: Agricultural Research Station, Fort Valley State University, Fort Valley, GA 31030, Postal: Agricultural Research Station, Fort Valley State University, Fort Valley, GA 31030
David A. Barber: Animal and Plant Health Inspection Service, United States Department of Agriculture, Springfield, IL 62704, Postal: Animal and Plant Health Inspection Service, United States Department of Agriculture, Springfield, IL 62704

Agribusiness, 2007, vol. 23, issue 2, 157-172

Abstract: A food systems perspective offers many appealing analytic features to food safety researchers with an interest in the design and targeting of effective and efficient policy responses to the risks posed by foodborne pathogens. These features include the ability to examine comparative questions such as whether it is more efficient to target food safety interventions on-farm or in the food processing plant. Using the example of a farm-to-fork stochastic simulation model of Salmonella in the pork production and consumption system, the authors argue the feasibility of such a food systems approach for food-safety risk assessment and policy analysis. They present an overview of the farm-to-fork model and highlight key assumptions and methods employed. Lessons from their experience in constructing a farm-to-fork stochastic simulation model are derived for consideration in other food safety risk assessment efforts and for researchers interested in developing “best practice” benchmarks in the area of food safety risk assessments. [EconLit Citations: Q18, I18, I12]. © 2007 Wiley Periodicals, Inc. Agribusiness 23: 157-172, 2007.

Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:wly:agribz:v:23:y:2007:i:2:p:157-172

DOI: 10.1002/agr.20115

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