analysis to inform decisions: evaluating bse
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Analysis to Inform Decisions: Evaluating BSE. Joshua Cohen and George Gray Harvard Center for Risk Analysis Harvard School of Public Health. Contributors. Harvard Center for Risk Analysis Joshua T. Cohen Keith Duggar George M. Gray Silvia Kreindel - PowerPoint PPT PresentationTRANSCRIPT
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?