P1-174 A Quantitative Meta-analysis of Existing Foodborne Pathogen Transfer Data

Monday, July 23, 2012
Exhibit Hall (Rhode Island Convention Center)
Amanda Benoit, Michigan State University, East Lansing, MI
Bradley Marks, Michigan State University, East Lansing, MI
Elliot Ryser, Michigan State University, East Lansing, MI
Introduction:   Bacterial cross-contamination between various food products and surfaces has been a major ongoing problem leading to numerous outbreaks and recalls. The number of papers published on bacterial transfer to/from food has increased approximately ten-fold over the past two decades, reflecting an increasing attention to this important issue.  However, there has been no standardization of methods or aggregation of data in this field.

Purpose:   Therefore, the objective was to conduct a quantitative meta-analysis of the published literature from the past ~40 years on transfer of foodborne pathogens, in order to evaluate the characteristics of the existing data, critical gaps, and the opportunity to aggregate these data for future analyses and modeling.

Methods:   Data sources were collected initially via a keyword search in the ISI Web of Science database, to identify all studies including transfer data for key foodborne pathogens (Listeria, Salmonella, Escherichia coli, and Campylobacter). Published transfer data were characterized in terms of pathogen, product type, surface, and other variables.

Results:   The total analysis yielded ~55 distinct publications on foodborne pathogen transfer, of which 43 contained numerical data, with a total of 756 data sets, ~1,194 individual replicate curves, and over 14,456 individual observations quantifying pathogen transfer between food products and contact surfaces, including: meat/poultry (n = 29) and produce (n = 11), with transfer to metals (n = 19), plastics (n = 16), hands/gloves (n =10), and several other surfaces.  These studies included a wide variety of other variables, such as contact time (n = 10), temperature (n = 12), inoculation level (n = 6), inoculated surface (n = 7), material composition (n = 9), and surface roughness (n = 4).  These papers have been organized into a preliminary database defining the characteristics of each study, which will serve as the foundation for a broader, publicly-available database in this domain.

Significance:   A unified database that aggregates pathogen transfer data, and becomes a repository for future data, will help advance linkages between fundamental research and the observed transfer outcomes, while also improving the design of future studies to fill critical data gaps.