DRIVING PREDICTIVE MODELING ON A RISK ASSESSMENT PATH FOR ENHANCED FOOD SAFETY

How do we best protect our citizens to allow the highest quality of li fe? Where do we put our food safety resources so that we gain the grea test positive impact? Risk assessment provides the critical scientific basis for these types of important risk management decisions. Increas ingly, risk assessment is used to guide legislated and voluntary chang es intended to improve safety, yet its formal application for enhanced food safety is in its infancy. Risk assessment includes disease chara cterization, dose-response assessment, exposure assessment, and risk c haracterization. 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. Pred ictive modelling should help to improve estimates and thereby allow qu antitation of food safety risks. Predictive modelling will also find a pplication for assessing prevention strategies in risk management. (C) 1997 Elsevier Science B.V.