A Microbial Risk Assessor Looks at Food Fraud Don Schaffner, Ph.D. Distinguished Professor and Extension Specialist in Food Science Rutgers, The State University of NJ

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Why is food fraud hard? Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don't know we don't know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones. United States Secretary of Defense Donald Rumsfeld ABRAPA, Brazil, June 2019

Another reason why it might be hard ABRAPA, Brazil, June 2019

Food Fraud vs. Food Safety Manning and Soon (2016) ABRAPA, Brazil, June 2019

Outline Why this topic? Risk based approaches should be applicable I know about QRMA, but not much about food fraud Risk based approaches should be applicable Focus on what is important ABRAPA, Brazil, June 2019

Food Safety Examples (Scallan et al.) 88% of US foodborne disease cases come from 13% of pathogens Norovirus (5.5 M) Salmonella (1.0 M) C. perfringens (965 K) Campylobacter (845 K) 82% of US foodborne disease deaths come from 13% of pathogens Salmonella (378) Toxoplasma (327) L. monocytogenes (255) Norovirus (149) ABRAPA, Brazil, June 2019

Food Fraud Example (Johnson 2014) 61% of reported types come from 24% of types Oils Spices Milk Sweeteners ABRAPA, Brazil, June 2019

Food Fraud Example 57% of EMA incidents come from 21% of ingredient categories Fish/seafood Oils, fats Alcoholic beverages Meat, meat products ABRAPA, Brazil, June 2019

Food Fraud Example 78% of EMA incidents come from 29% of adulteration types Substitution/ dilution Unapproved additive ABRAPA, Brazil, June 2019

Definitions ABRAPA, Brazil, June 2019

Hypothetical Examples Microbiology Hazard: Pathogen XYZ Risk: probability and severity One in every 1,000 servings contains 1 cell of Organism XYZ, and one cell has a 1/300 chance of causing diarrhea, a 1/20,000 chance of causing hospitalization, and a 1/500,00 chance of causing death Food Fraud Hazard: Customer is cheated Risk: Specifies probability and severity One in every 100 containers of product X contain a substituted ingredient, where the actual ingredient costs z, and the substituted ingredient cost z/10. ABRAPA, Brazil, June 2019

Risk Analysis Components (Quantitative) Risk Assessment How big is the risk, what factors control the risk? Scientific process Risk Communication How can we talk about the risk with affected individuals? Social and psychological process Risk Management What can we do about the risk? Policy-making process, small “p” political Not scientific, but informed by science ABRAPA, Brazil, June 2019

Step in Risk Assessment ABRAPA, Brazil, June 2019

Published examples ABRAPA, Brazil, June 2019

Food Control 2016 results… 80% correct given 52% correct without fraud type country food category 52% correct without country of origin product-country combo ABRAPA, Brazil, June 2019

Benefits of membership ;) ABRAPA, Brazil, June 2019

Unpublished Example ABRAPA, Brazil, June 2019

The future? Prediction is very difficult, especially about the future Niels Bohr? Yogi Berra? Mark Twain? Earliest attribution seems to be Danish politician Karl Kristian Steincke ABRAPA, Brazil, June 2019