1 / 34

USDA, ARS Workshop Poultry Food Assess Risk Model (Poultry FARM)

USDA, ARS Workshop Poultry Food Assess Risk Model (Poultry FARM). What is Poultry FARM?. A quantitative microbial risk assessment model (QMRA) for Listeria, Salmonella, Campylobacter and chicken meat. What does Poultry FARM do?.

stella
Download Presentation

USDA, ARS Workshop Poultry Food Assess Risk Model (Poultry FARM)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. USDA, ARS Workshop Poultry Food Assess Risk Model (Poultry FARM)

  2. What is Poultry FARM? A quantitative microbial risk assessment model (QMRA) for Listeria, Salmonella, Campylobacterand chicken meat.

  3. What does Poultry FARM do? Predicts the public health impact of chicken meat destined for specific distribution channels and consumer populations

  4. What is the goal of Poultry FARM? Packaging Unsafe Cooking Safe Distribution Channel Consumption To maximize the public health benefit of chicken by ensuring its safety & consumption

  5. What is QMRA? • Hazard Identification • Exposure Assessment • Hazard Characterization • Risk Characterization Holistic How many people will get sick and die?

  6. Hazard Identification Initial distribution of pathogens among servings Campylobacter (Cj) Listeria (Lm) Salmonella (Se)

  7. Pathogen levels on chicken meat(mean log MPN/carcass) Cj levels are higher than Lm and Se, which are similar Waldroup et al. (1992) J. Appl. Poultry Res. 1:226-234.

  8. Simon Sez!!! Relative differences among pathogens are simulated in Poultry FARM

  9. Exposure Assessment Plant Packaging Contamination Distribution Abuse Growth/Death Preparation Contamination Transfer Cooling Abuse Growth/Death Cooking Under-cooking Survival Predicts how pathogen levels change from farm-to-table Serving Contamination Transfer Table Consumption Dose-response Key: Unit Operation _ Human Action _ Pathogen Event

  10. Physiological Differences Se grows, whereas Cj dies at ambient temperatures Burnette and Yoon (2004) Food Sci. Biotechnol. 13:796-800

  11. Simon Sez!!! Predictive models can be developed for each pathogen event

  12. Hazard Characterization No response Infection Mild illness Illness Determines whether or not an illness occurs

  13. Simon Sez!!! Depends on the outcome of the interaction between the pathogen, food and host Disease Triangle Pathogen Host Food

  14. Risk Characterization Illness Hospital Death Determines the severity of illness

  15. Simon Sez!!! There are important differences in severity among pathogens Mead et al. (1999) http://www.cdc.gov/ncidod/eid/vol5no5/mead.htm

  16. Severity Assessment Illness (C1) Hospital (C2) Death (C3) Severity = C1 + 2C2 + 10C3 Cases Weight factor

  17. Simon Sez!!! Foodborne illness is a random event

  18. Simon Sez!!! Monte Carlo simulation is a good method for modeling foodborne illness

  19. What is Monte Carlo Simulation? A + B = C

  20. Simon Sez!!! Foodborne illness is a rare event

  21. Rare Events' Modeling Pathogen Number Incidence Extent Discrete 1 0 0 : 0 Iteration 1 2 3 : 10,000 Pert (0,2,4) 1.8 1.2 0.2 : 2.2 Antilog 63.1 0 0 : 0 Round 63 0 0 : 0 =IF(RiskDiscrete=0,0,RiskPert) Poultry FARM simulates pathogen-free servings

  22. Poultry FARM Tour

  23. Scenario Analysis What IF?

  24. Which is higher risk? Lot A Lot B

  25. Scenario Settings Waldroup et al (1992) J. Appl. Poultry Res. 1:226-234.

  26. Scenario Settings

  27. Simulation Settings QMRA Model = Poultry FARM 3.0 Iterations = 10,000 servings Simulations = 100 Sampling = Latin Hypercube Random Number Generator Seed = Random Selection

  28. Simon Sez!!! Each random number generator seed produces a unique outcome of the scenario

  29. Listeria monocytogenes

  30. Salmonella enterica

  31. Campylobacter jejuni

  32. Lm + Se + Cj

  33. Simon Sez!!! It is important to consider multiple pathogens and post-process risk factors when assessing food safety

  34. The End

More Related