There are more than 500,000 cases of food poisoning each year in the UK, according to a recent article in Food Quality News that discusses findings from a report from the UK Food Standards Agency (FSA). This study used Monte Carlo simulation and a Bayesian approach to model and estimate the burden of foodborne disease in the UK. Analysts used data from a 2011 infectious intestinal disease study alongside data from other outbreaks and a literature review of roughly 200 international study.
The main culprits for the illnesses are Camplyobacter bacteria, which caused 280,000 cases of reported food poisoning every year; Clostridium perfringens, with 80,000 outbreaks, and norovirus, which cause an estimated 74,000 incidents. These, however do not include hospitalizations— in that category, Salmonella takes the top spot, causing roughly 2,500 food poisoning hospital admissions every year.
Poultry meat was the most typical source of harmful bacteria, with fruit, nuts and seeds causing the second highest number of illnesses. Eggs, on the other hand, caused only 5% of foodborne illness, but more than 30% of hospital admissions.
Palisade has helped many clients assess food safety risk–In China, the Shanghai Food and Drug Administration also relied on @RISK’s Monte Carlo simulation to assess nitrite contamination in cooked meat. Based on the results from the model, the Shanghai FDA proposed that businesses in the food service industry be forbidden from using nitrite, which eliminated the possibility of nitrite poisoning at its root.
@RISK has also been used in an academic postgraduate program for risk analysis in health and food safety at the University of London-Royal Veterinary College. The certificate was the first recognized qualification in risk analysis in health and food safety. The program used @RISK to facilitate the teaching of complex risk analysis concepts to professionals, enabling them to learn how to conduct probabilistic analysis and use modeling techniques to model biological processes relevant to health and food safety problems regardless of their prior modeling expertise.