CropLife America & RISE2014 Spring Conference

Arlington, VA

Finding Common Ground in thePesticide Risk Assessment Process

Bruce K. Hope, Ph.D.

2

Committee on Ecological Risk Assessment Under FIFRA and ESA– Report: April 2013

CropLife Science Forum– May 2013

Agency efforts– “Interim Approaches for

National-Level Endangered Species…Assessments”

National Research Council (NRC)

3

Risk

Uncertainty (as a probability) about an outcome (with specified consequences) being realized in the future due to a decision made today– This probability is the “risk estimate”

Uncertainty about the risk estimate itself– Sources

• Natural / stochastic variability• Incertitude (lack of knowledge, ignorance)• Measurement and model error

– Can be expressed qualitatively and/or qualitatively– Essentially our “confidence” in the risk estimate

4

Components of a Risk Assessment

Risk Characterization

Probability of a Specified Adverse

Effect

Exposure

Exposure-Response

Exposure Scenario

5

Risk Characterization

CONCENTRATION

PRO

BABI

LITY

EXPOSURE-RESPONSEEXPOSURE (EEC)

Risk EstimateProbability of eliciting a specified response

in an individual

6

Interim Memo: Exposure

Step 1– Modeled estimates

Step 2– Modeled estimates w/ refinements

Step 3– Not specified

Role for both prediction and measurements (empirical data) for model corroboration)

7

Interim Memo: Exposure-Response

Step 1 (No Effect / May Affect; Action Area)– Animals: EEC LD0.000001 (individual mortality)

• 5th percentile species from SSD or most sensitive species tested

– Plants: Lowest NOAEC or EC05

Step 2 (NLAA / LAA)– Animals: EEC EC10 (10% decrease in individuals)

• 5th percentile species from SSD or most sensitive species tested

– Plants: Lowest LOAEC or EC25

Step 3 (Jeopardy)– Population model(s) - Same SSD, D/R slopes as in Steps 1 & 2

8

Interim Memo: It’s a Start, but…

Point of departure for exposure is not defined– What will the EEC represent? Median, mean, 95%?

Point to point comparisons (EEC to LD0.000001, etc.) are not “risk” estimates– They are hazard or threshold assessments

Step 1 & 2 hazard assessments produce “risk quotients” that are not easily transferable to Step 3 stochastic population models– A common basis in probability (risk) is missing

9

Why Not Quotients?

A hazard (threshold) assessment gives decision makers no idea of the chance of an outcome

But being just over the threshold is often perceived of as a 100% certainty of a detrimental outcome

Benefits can be foregone to avert a “certainty” that is highly unlikely to ever happen

This may lead to decisions that limit pesticide use to a greater extent than is intended by policy

10

Informing Decisions with Risk

If I plan to make decision X (to register a pesticide)…

What is the probability (p(Y)) that detrimental outcome Y will occur in the future? [p(Y) is the risk estimate]

What is my confidence in that estimate of p(Y)?– Where confidence is affected by variability and incertitude

Acceptability of p(Y)’s value is strictly a policy choice– But knowledge of it’s size (large or very small) is an important

component of informed decision making

11

Tools for quantitative risk analysis

Monte Carlo– First-order (variability + incertitude)

• Widely used approach, particularly for data-rich situations

– Second-order (variability, incertitude)• Useful for value of information determinations

Probability Bounds Analysis

Bayesian Methods– Can work across a hierarchy of data levels– Dempster-Shafer Theory (multiple lines of evidence)

12

Risk as Common Ground

Probability of

Effect on Populatio

n

Exposure

Exposure-Response

Exposure Scenario

PopulationModel(s)

EPA: Steps 1 & 2

Services: Step 3

CONCENTRATION

PRO

BABI

LITY

EXPOSURE-RESPONSE(SSD)

EXPOSURE(EEC)

Riskestimate

(%)

Risk Characterization