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A farm‐to‐fork stochastic simulation model of pork‐borne salmonellosis in humans: Lessons for risk ranking
Author(s) -
McNamara Paul E.,
Miller Gay Y.,
Liu Xuanli,
Barber David A.
Publication year - 2007
Publication title -
agribusiness
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.57
H-Index - 43
eISSN - 1520-6297
pISSN - 0742-4477
DOI - 10.1002/agr.20115
Subject(s) - econlit , fork (system call) , food safety , ranking (information retrieval) , risk analysis (engineering) , computer science , food systems , key (lock) , agribusiness , business , food security , agriculture , political science , computer security , food science , geography , medline , machine learning , chemistry , archaeology , law , operating system
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.