Dr. Aaron Scott - Advantages of Probability-Based Approaches to Animal Disease Surveillance

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Advantages of Probability-Based Approaches to Animal Disease Surveillance - Dr. Aaron Scott, Center Director, USDA/APHIS/VS/CEAH, from the 2012 Annual Conference of the National Institute for Animal Agriculture, March 26 - 29, Denver, CO, USA. More presentations at: http://www.trufflemedia.com/agmedia/conference/2012-decreasing-resources-increasing-regulation-advance-animal-agriculture

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NIAAMarch 27, 2012

Aaron Scott, DVM PhD DACVPM (epi) Center Director, NSU

Probability based approaches to animal health surveillance

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National Surveillance Unit“Building Partnerships and Leading Change”

Safeguarding Animal Health

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Using risk factors and probability to get the most

information at the lowest cost

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Why?

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Federal/State budgets

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What is surveillance?

Find disease

if its not there…

Prove it!!!

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Surveillance is evidence!

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Reverend Thomas Bayes

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Evidence may be combination of sample testing and

other knowledge about risk factors

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“Risk” = likelihood * consequence

= animals more likely to get disease? = animals more likely to have disease? = animals more likely to be detected?

= more dangerous to people????

Risk-based versus probability

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Inference …

…is drawing a conclusion about the population from one or

more pieces of evidence

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Sampling and inference

Convenience

Random

Representative

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Random Selection

•Inference is based on random sampling•Listing of all subjects (sample frame)•Each has equal chance of selection•Is always representative

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Random Sample size

“n” = 3X when 1:X

3,000,000 samples to detect 1 in 1,000,000

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Representative – non-biased

A representative sample could be just anybody!

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Geographic representation

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Representative

If not random, must be other supporting evidence for

representativeness…

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Targeted (“risk based”) sampling

Concept: Every sample gives information

Corollary: Some are worth more than others

Targeted = intentional bias!

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Must clearly define sub populationsMust have knowledge of risk factors

Must know magnitude of risk factorsTargeting represents sub-populationsMust know relationship

Targeting and inference

Population

Clear risk factor

Clear risk factor

3X

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What is “n”?

40 H-risk * value 3 = 12010 L-risk * value 0.5 = 5

50 tests = 125 “virtual” samples

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What are the risk factors?

Intentionally biased sample

+ other information

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Sows and boars (value = 2.5x to 5x ) Exposure to feral pigs (10x ? 100x ?) Non-confinement (??)

Some samples from all populationsMarket swine (< 1x)

PRV Targeting

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Slaughter sampling

From 3 herds: 5,000, 30, 10

Need “n” of 30/farm for inference30 + 30 + 10 =70 samples

Without additional info,n = 5,040!!!

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Collect all with traceable IDSend to lab and sortOnly knowledge is State of originDiscard all but 5% from each State

Current PRV

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PIN tag pilot

Collaboration:• NPB, AASV, industry reps• 6 State Veterinarians• Veterinary Services

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High value (feral swine exposure)Limit to number neededCollect “pink tag”, scan ID, combine

zip with feral risk, target # needed Other tagsSpend the money on other diseases

PIN Pilot

31Safeguarding Animal Health

national.surveillance.unit@aphis.usda.gov

http://www.aphis.usda.gov/vs/ceah/ncahs/nsu/

Thanks!!

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