Pathogenic and Non-Pathogenic Microorganisms in the Rapid Alert System for Food and Feed

Int J Environ Res Public Health. 2019 Feb 6;16(3):477. doi: 10.3390/ijerph16030477.

Abstract

The most frequently notified pathogenic microorganisms in the RASFF in 1980⁻2017 were Salmonella sp., Listeria, Escherichia and Vibrio, whereas, among the notified non-pathogenic microorganisms were unspecified microorganisms, Enterobacteriaceae, Salmonella sp. and Coliforms. Microorganisms were reported mainly in poultry meat, meat, fish, molluscs, crustaceans, fruits, vegetables, herbs, spices, nuts, milk, cereals (in food) and in feed materials and pet food (in feed). The number of notifications decreased at the turn of 2005 and 2006, but has steadily increased since then. The notification basis were official controls, border controls and company's checks. Products were notified mainly by Italy, France, United Kingdom, Germany and Netherlands. The reported products originated from Brazil, European Union countries and India, Thailand and Vietnam. The notification types were alerts, information and border rejections. The distribution status was often not specified or distribution on the market was possible. The risk decision was usually not made. Products were re-dispatched, import was not authorised or products were withdrawn from the market, destroyed and recalled from the market. Proper cooperation within the framework of the RASFF can contribute to shaping public health law and reducing outbreaks associated with microorganisms.

Keywords: European Union; RASFF; cluster analysis; food safety; pathogens; pivot tables.

MeSH terms

  • Animal Feed / microbiology*
  • Animals
  • Asia
  • Disease Outbreaks / statistics & numerical data*
  • Environmental Monitoring
  • Europe
  • European Union
  • Food Contamination / analysis*
  • Food Microbiology / statistics & numerical data*
  • Food Safety / methods*
  • Foodborne Diseases / microbiology*
  • Fruit / microbiology
  • Humans
  • Meat / microbiology
  • Risk Assessment / statistics & numerical data*
  • Seafood / microbiology
  • South America
  • Vegetables / microbiology