title: Driving predictive modelling on a risk assessment path for enhanced food safety.
abstract: How do we best protect our citizens to allow the highest quality of life? Where do we put our food safety resources so that we gain the greatest positive impact? Risk assessment provides the critical scientific basis for these types of important risk management decisions. Increasingly, risk assessment is used to guide legislated and voluntary changes intended to improve safety, yet its formal application for enhanced food safety is in its infancy. Risk assessment includes disease characterization. dose-response assessment, exposure assessment, and risk characterization. Quantitative data is critical for risk assessment to realize its full value, yet much of our knowledge about the incidence of pathogens or toxins in foods, dose-response knowledge, incidence of acute food-borne illness, incidence of chronic sequelae, and cost of food-borne illness is qualitative or estimates are controversial. Predictive modelling should help to improve estimates and thereby allow quantitation of food safety risks. Predictive modelling will also find application for assessing prevention strategies in risk management.
authors.affiliation: Department of Food Science, North Carolina State University, Raleigh 27695-7624, USA. peggymf@unity.ncsu.edu
authors.forename: P M
authors.initials: PM
authors.lastname: Foegeding
mesh_terms: D005506:Food Contamination; D005516:Food Microbiology; D006801:Humans; D018570:Risk Assessment