Analysis to Inform Analysis to Inform Decisions:Decisions:

Evaluating BSEEvaluating BSE

Joshua CohenJoshua Cohen

andand

George GrayGeorge Gray

Harvard Center for Risk AnalysisHarvard Center for Risk Analysis

Harvard School of Public HealthHarvard School of Public Health

ContributorsContributors Harvard Center for Risk AnalysisHarvard Center for Risk Analysis

Joshua T. CohenJoshua T. Cohen Keith DuggarKeith Duggar George M. GrayGeorge M. Gray Silvia KreindelSilvia Kreindel

Center for Computational Epidemiology, College Center for Computational Epidemiology, College of Veterinary Medicine, Tuskegee Universityof Veterinary Medicine, Tuskegee University

Hatim GubaraHatim Gubara Tsegaye HabteMariamTsegaye HabteMariam David OryangDavid Oryang Berhanu TameruBerhanu Tameru

Harvard Center for Risk AnalysisHarvard Center for Risk Analysis Joshua T. CohenJoshua T. Cohen Keith DuggarKeith Duggar George M. GrayGeorge M. Gray Silvia KreindelSilvia Kreindel

Center for Computational Epidemiology, College Center for Computational Epidemiology, College of Veterinary Medicine, Tuskegee Universityof Veterinary Medicine, Tuskegee University

Hatim GubaraHatim Gubara Tsegaye HabteMariamTsegaye HabteMariam David OryangDavid Oryang Berhanu TameruBerhanu Tameru

What USDA Asked Us to DoWhat USDA Asked Us to Do Identify and characterize possible sources for Identify and characterize possible sources for

BSE (or a TSE disease with similar clinical and BSE (or a TSE disease with similar clinical and pathologic signs as BSE - will refer to as BSE for pathologic signs as BSE - will refer to as BSE for brevity) infectivity in U.S. cattlebrevity) infectivity in U.S. cattle

Identify and characterize pathways for cattle-Identify and characterize pathways for cattle-derived BSE infectivity in the U.S. cattle herd or derived BSE infectivity in the U.S. cattle herd or human food supplyhuman food supply

Evaluate implications over time of possible Evaluate implications over time of possible introduction of BSE into US systemintroduction of BSE into US system

Why We Chose a Simulation Why We Chose a Simulation ApproachApproach

No historical data - build understanding up No historical data - build understanding up from biology, agriculture, etc. from biology, agriculture, etc.

Time matters - Time matters - e.g.,e.g., incubation period of BSE incubation period of BSE

Allow quantitative comparison of importance Allow quantitative comparison of importance of different pathways of spread and different of different pathways of spread and different risk managementrisk management

Can help focus collection of informationCan help focus collection of information

Learning from UK Learning from UK ExperienceExperienceWe assume the prevailing hypothesis of UK BSE We assume the prevailing hypothesis of UK BSE

spread is correct:spread is correct:

RenderingFeedBSE

Cattle Scrapie?Spontaneous?

Model OverviewModel Overview

Cattle PopulationNumber InfectedNumber Clinical

Slaughter

Rendering andFeed Production

Infectivity Sources

Human Food

Disposal

Death and Disposal

Other Uses and Elimination from System

Other Protein Sources

Feed Administered to Cattle

Death / Rendering

Cattle Cattle DynamicsDynamics

Healthy

Animal

Infected Animal(incubating)

ClinicalAnimal

Slaughter

Death

Infection Rate Feeding Susceptibility Maternal

Transmission Spontaneous

All rates depend on Age Type Gender

Key Assumptions - Key Assumptions - SusceptibilitySusceptibility

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 50 100 150 200 250

Age (Months)

Infectivity Level in Bovine vs. Time Infectivity Level in Bovine vs. Time Since InfectionSince Infection

Total ID50s

0

2000

4000

6000

8000

10000

12000

0 10 20 30 40

Months Since Infection

Total ID50s

Relative Infectivity of Specific Tissues Specified From an Infected Bovine (Based on (SSC, 1999a))a

Tissue Fraction of Total Infectivity Brain No infectivity in cattle < 32 months post-inoculation (PI)

32 months PI and over: 64.1% Trigeminal Ganglia No infectivity in cattle < 32 months post-inoculation.

32 months PI and over: 2.6% Other Head (eyes, etc.) No infectivity in cattle < 32 months post-inoculation.

32 months PI and over: 0.04% Distal Ileum 6-18 months post inoculation: 100%

18-31: No Infectivity 32 months PI and over 3.3%

Spinal Cord No infectivity in cattle < 32 months post-inoculation.

32 months PI and over: 25.6% infectivity Dorsal Root Ganglia No infectivity in cattle < 32 months post-inoculation.

32 months PI and over: 3.8 % infectivity

Notes: a. The post-inoculation time values in this table reflect the assumption that the incubation period is 36

months. See text for explanation.

Distribution of InfectivityDistribution of InfectivityRelative Infectivity of Specific Tissues Specified from an Infected Bovine

(Based on [SSC, 1999a])a

Slaughter Slaughter ProcessProcess

Sick Animal Characteristics

Antemortem Inspection

Disposition of Brain

Stunning Exsanguination

Tissues to rendering

SplittingPostmortem Inspection

Tissues for Possible Human Consumption

AMR/ Spinal Cord/DRG

Processing

Out Out Out

Out Out

Rendering and Feed Rendering and Feed ProductionProduction

Tissues to rendering

ProhibitedMBM production

Prohibitedfeed production

Feeding of cattle on farm

Non-prohibited MBM production

Non-Prohibited feed production

1

4

6

7

9

Blood

11

12

5 10

13

12

14

6

2

3

3

8

12

AnalysesAnalyses Base CaseBase Case

Assume BSE not currently present in U.S.Assume BSE not currently present in U.S. Introduce 10 BSE infected animals (also simulated importation Introduce 10 BSE infected animals (also simulated importation

of 1 to 500 BSE infected cows)of 1 to 500 BSE infected cows) Follow for 20 yearsFollow for 20 years

Example Risk management OptionsExample Risk management Options Ban on rendering cattle that die on farmBan on rendering cattle that die on farm UK-style “Specified Risk Material” banUK-style “Specified Risk Material” ban Test with introduction of 10 infected animals and follow for 20 Test with introduction of 10 infected animals and follow for 20

yearsyears OthersOthers

Potential for pre-1989 imports from England to introduce BSE to Potential for pre-1989 imports from England to introduce BSE to U.S.U.S.

SwitzerlandSwitzerland SpontaneousSpontaneous Scrapie as sourceScrapie as source

Model is ProbabilisticModel is Probabilistic

Initialize Model

Run Simulation

Record Results

Run 3

Run 2

Run 1

…

Run 1000

Number of Infected Cattle over 20 Years

Results: Base CaseResults: Base Case Few new cases of BSE Few new cases of BSE

mean = 3 and 95th percentile = 11mean = 3 and 95th percentile = 11 Primarily through feed ban leaksPrimarily through feed ban leaks 40% of animals predicted to die on farm introduce 40% of animals predicted to die on farm introduce

96% of infectivity to system96% of infectivity to system

BSE gone within 20 years of introductionBSE gone within 20 years of introduction

Base Case ResultsBase Case Results(continued)(continued)

Little infectivity for potential human exposure Little infectivity for potential human exposure (mean 35 cattle oral ID50s, 95th 170)(mean 35 cattle oral ID50s, 95th 170) BrainBrain 26%26% Beef on boneBeef on bone 11%11% AMR meatAMR meat 56%56% Spinal cordSpinal cord 5%5%

Conservative assumptions (e.g., no change if Conservative assumptions (e.g., no change if case detected)case detected)

Base Case – SummaryBase Case – Summary

Base Case - SummaryBase Case - Summary

Base Case - Summary Base Case - Summary Number of Cattle Infected:

Probability of Prevalence Value Exceeding Zero

1.0 1.0 1.0 1.0 .97

.66

.29

.12 .06 .05 .03 .02 .01 .01 .00 .00 .00 .00 0 0 0

Probability

0

.10

.20

.30

.40

.50

.60

.70

.80

.90

1.0

Year

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Base Case - SummaryBase Case - SummaryNumber of Cattle Infected: Range of Prevalence ValuesN

um

be

r o

f Ca

ttle

Infe

cte

d

1

10

100

Year

0 10 20

Base Case – SummaryBase Case – SummaryNumber of Cattle Clinical: Probability of Prevalence Exceeding Zero

0 0

.06

.46

.49

.25

.09

.05 .03 .03

.02 .01 .01 .00 0 .00 0 .00 0 0 0

Probability

0

.05

.10

.15

.20

.25

.30

.35

.40

.45

.50

Year

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Base Case – Changes Over Base Case – Changes Over TimeTime

Number of Cattle Clinical: Range of Prevalence Values

Nu

mb

er

of C

attl

e C

linic

al

0

1

2

3

4

5

6

Year

0 10 20

Model Predictions for More Model Predictions for More Substantial Imports of Infected Substantial Imports of Infected

CattleCattle

0

50

100

150

200

250

0 100 200 300 400 500 600

Number of BSE-Infected Cattle Imported

Additional Infected Cattle

Model Predictions for More Model Predictions for More Substantial Imports of Infected Substantial Imports of Infected

CattleCattle

0

500

1000

1500

2000

2500

0 100 200 300 400 500 600

Number of BSE-Infected Cattle Imported

Number of ID 50s Available for

Potential Human Consumption

Key Sources of Uncertainty Key Sources of Uncertainty Influencing the Predicted Number Influencing the Predicted Number

of Infected Cattleof Infected CattleT

ota

l In

fect

ed

w/o

Im

po

rts:

me

an

0

10

20

30

40

50

60

70

80

Parameter

1 Maternal Trans.

2a ID50s per Clin BSE Case

2b AM Inspector

2c Stunner

2d Splitter

3a Render Reduction Factor

3b MBM

Contam. Prob.

3c MBM

Contam. Fraction

3d MBM

Mislabel Prob.

3e Feed Contam. Prob.

3f Feed Contam. Fraction

3g Feed MisLabel Prob.

3h Misfeed Rate

4 Human Food Inspection

5 Die on Farm Render Rate

Key Sources of Uncertainty Influencing Key Sources of Uncertainty Influencing Predicted Human ExposurePredicted Human Exposure(ID(ID5050s Available for Human s Available for Human

Consumption)Consumption)

To

tal t

o H

um

an

s: m

ea

n

0

20

40

60

80

100

120

140

160

180

200

Parameter

1 Maternal Trans.

2a ID50s per Clin BSE Case

2b AM Inspector

2c Stunner

2d Splitter

3a Render Reduction Factor

3b MBM

Contam. Prob.

3c MBM

Contam. Fraction

3d MBM

Mislabel Prob.

3e Feed Contam. Prob.

3f Feed Contam. Fraction

3g Feed MisLabel Prob.

3h Misfeed Rate

4 Human Food Inspection

5 Die on Farm Render Rate

Key Management PointsKey Management Points

Spread in cattle herdSpread in cattle herd Mostly due to leaks in FDA feed ban and some maternal Mostly due to leaks in FDA feed ban and some maternal

transmissiontransmission Animals that die on farm with provide greatest infectivity Animals that die on farm with provide greatest infectivity

to animal feed systemto animal feed system

Potential human exposurePotential human exposure Handling of brain and spinal cord in processing very Handling of brain and spinal cord in processing very

importantimportant Primary routes of exposure are cattle brain, spinal cord, Primary routes of exposure are cattle brain, spinal cord,

beef on bone and AMR meatbeef on bone and AMR meat

Imports from EnglandImports from England Before 1989 Before 1989

Evaluated potential for 173 (of 334) English imports Evaluated potential for 173 (of 334) English imports not known to have been destroyed to introduce not known to have been destroyed to introduce infectivity to U.S. cattle and implicationsinfectivity to U.S. cattle and implications

Used information on birth year, export year, animal Used information on birth year, export year, animal type and sex, last sighting and more to estimate type and sex, last sighting and more to estimate likelihood and potential magnitude of introductions of likelihood and potential magnitude of introductions of BSE infectivity to U.S. cattle feedBSE infectivity to U.S. cattle feed

Used model to look at new BSE cases if introduction Used model to look at new BSE cases if introduction of different sizes did occurof different sizes did occur

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

During the 1980sDuring the 1980s

0

5

10

15

20

25

0 0.2 0.4 0.6 0.8 1

Cumulative Probability

ID5

0s

Cumulative Distribution for the Number Cumulative Distribution for the Number of BSE-Clinical Cattle in the Year 2000 of BSE-Clinical Cattle in the Year 2000

for Different Levels of Infectivity for Different Levels of Infectivity Introduced Introduced viavia Import of UK Cattle Import of UK Cattle

During the 1980sDuring the 1980s

0

200

400

600

800

1000

1200

1400

0 0.2 0.4 0.6 0.8 1

Cumulative Probability

Nu

mb

er

of

Clin

ica

l Ca

ttle

in 2

00

0

0.1 ID50s

1.0 ID50s

5.0 ID50s

10.0 ID50s

50.0 ID50s

Detectable

Strengths of Analytic Strengths of Analytic ApproachApproach

Identify key assumptions and dataIdentify key assumptions and data

Understand relative importance of Understand relative importance of different pathsdifferent paths

Compare relative effectiveness of Compare relative effectiveness of different risk management measuresdifferent risk management measures

Facilitates value of information (VOI) Facilitates value of information (VOI) analysis to identify critical research areasanalysis to identify critical research areas

Weaknesses of Analytic Weaknesses of Analytic ApproachApproach

Overconfidence in results?Overconfidence in results?

Dependent on underlying structure and Dependent on underlying structure and assumptions assumptions

Difficulty in calibration/validationDifficulty in calibration/validation

What is the alternative?What is the alternative?