Analysis to Inform Decisions: Evaluating BSE

1. Analysis to Inform Decisions:Evaluating BSE Joshua Cohen and George Gray Harvard Center for Risk Analysis Harvard School of Public Health

2. Contributors • Harvard Center for Risk Analysis • Joshua T. Cohen • Keith Duggar • George M. Gray • Silvia Kreindel • Center for Computational Epidemiology, College of Veterinary Medicine, Tuskegee University • Hatim Gubara • Tsegaye HabteMariam • David Oryang • Berhanu Tameru

3. What USDA Asked Us to Do • Identify and characterize possible sources for BSE (or a TSE disease with similar clinical and pathologic signs as BSE - will refer to as BSE for brevity) infectivity in U.S. cattle • Identify and characterize pathways for cattle-derived BSE infectivity in the U.S. cattle herd or human food supply • Evaluate implications over time of possible introduction of BSE into US system

4. Why We Chose a Simulation Approach • No historical data - build understanding up from biology, agriculture, etc. • Time matters - e.g., incubation period of BSE • Allow quantitative comparison of importance of different pathways of spread and different risk management • Can help focus collection of information

5. Learning from UK Experience We assume the prevailing hypothesis of UK BSE spread is correct:

6. Infectivity Sources Cattle Population Number Infected Number Clinical Death and Disposal Feed Administered to Cattle Slaughter Disposal Human Food Death / Rendering Rendering and Feed Production Other Uses and Elimination from System Other Protein Sources Model Overview

7. Cattle Dynamics

8. Key Assumptions - Susceptibility

9. Infectivity Level in Bovine vs. Time Since Infection

10. Distribution of Infectivity Relative Infectivity of Specific Tissues Specified from an Infected Bovine(Based on [SSC, 1999a])a

11. Out Out Out Antemortem Inspection Sick Animal Characteristics Stunning Exsanguination Disposition of Brain Tissues for Possible Human Consumption AMR/ Spinal Cord/DRG Postmortem Inspection Splitting Tissues to rendering Processing Out Out Slaughter Process

12. 6 12 3 Prohibited MBM production Prohibited feed production 7 2 1 13 4 9 10 5 Tissues to rendering Feeding of cattle on farm 14 Non-prohibited MBM production Non-Prohibited feed production 8 3 11 6 12 Blood 12 Rendering and Feed Production

13. Analyses • Base Case • Assume BSE not currently present in U.S. • Introduce 10 BSE infected animals (also simulated importation of 1 to 500 BSE infected cows) • Follow for 20 years • Example Risk management Options • Ban on rendering cattle that die on farm • UK-style “Specified Risk Material” ban • Test with introduction of 10 infected animals and follow for 20 years • Others • Potential for pre-1989 imports from England to introduce BSE to U.S. • Switzerland • Spontaneous • Scrapie as source

14. Initialize Model Run 1000 Run Simulation … Run 3 Record Results Run 2 Run 1 Model is Probabilistic Number of Infected Cattle over 20 Years

15. Results: Base Case • Few new cases of BSE • mean = 3 and 95th percentile = 11 • Primarily through feed ban leaks • 40% of animals predicted to die on farm introduce 96% of infectivity to system • BSE gone within 20 years of introduction

16. Base Case Results(continued) • Little infectivity for potential human exposure (mean 35 cattle oral ID50s, 95th 170) • Brain 26% • Beef on bone 11% • AMR meat 56% • Spinal cord 5% • Conservative assumptions (e.g., no change if case detected)

17. Base Case – Summary

18. Base Case - Summary

19. Base Case - Summary Number of Cattle Infected: Probability of Prevalence Value Exceeding Zero

20. Base Case - Summary Number of Cattle Infected: Range of Prevalence Values

21. Base Case – Summary Number of Cattle Clinical: Probability of Prevalence Exceeding Zero

22. Base Case – Changes Over Time Number of Cattle Clinical: Range of Prevalence Values

23. Model Predictions for More Substantial Imports of Infected Cattle 250 Additional Infected Cattle 200 150 100 50 0 0 100 200 300 400 500 600 Number of BSE-Infected Cattle Imported

24. 2500 2000 1500 1000 500 0 0 100 200 300 400 500 600 Model Predictions for More Substantial Imports of Infected Cattle Number of ID50s Available for Potential Human Consumption Number of BSE-Infected Cattle Imported

25. Key Sources of Uncertainty Influencing the Predicted Number of Infected Cattle

26. Key Sources of Uncertainty Influencing Predicted Human Exposure(ID50s Available for Human Consumption)

27. Key Management Points • Spread in cattle herd • Mostly due to leaks in FDA feed ban and some maternal transmission • Animals that die on farm with provide greatest infectivity to animal feed system • Potential human exposure • Handling of brain and spinal cord in processing very important • Primary routes of exposure are cattle brain, spinal cord, beef on bone and AMR meat

28. Imports from England Before 1989 • Evaluated potential for 173 (of 334) English imports not known to have been destroyed to introduce infectivity to U.S. cattle and implications • Used information on birth year, export year, animal type and sex, last sighting and more to estimate likelihood and potential magnitude of introductions of BSE infectivity to U.S. cattle feed • Used model to look at new BSE cases if introduction of different sizes did occur

29. Cumulative Distribution for the U.S. Cattle Exposure to Cattle Oral ID50s from Animals Imported from the UK During the 1980s

30. Cumulative Distribution for the Number of BSE-Clinical Cattle in the Year 2000 for Different Levels of Infectivity Introduced via Import of UK Cattle During the 1980s

31. Strengths of Analytic Approach • Identify key assumptions and data • Understand relative importance of different paths • Compare relative effectiveness of different risk management measures • Facilitates value of information (VOI) analysis to identify critical research areas

32. Weaknesses of Analytic Approach • Overconfidence in results? • Dependent on underlying structure and assumptions • Difficulty in calibration/validation • What is the alternative?