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OAR Box 1112 

Prepped by RyanDugan 

Document Number: 

30) ll-C-1h 

Docket Number: 

A-83-22 

Printed 4/16/2008 9:12:07 AM Sheet 30 of 97 
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DESCRIPTION OF THE DOSE-RESPONSE AND RISK 

MODELING EFFORT 

Ronald G. Whitfield 

Argonne National Laboratory, Argonne 111 

August 1983 
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DESCRIPTION OF THE DOSE/RESPONSE 

AND RISK MODELING EFFORT 

1. Background 

Argonne National Laboratory (ANL) is providing EPA's Office of Air 

Quality, Planning and Standards, Strategies and Air Standards Division 

(OAQPS/SASD) with technical assistance in assessing the risks of alternative 

National Ambient Air Quality Standards (NAAQS) for lead. Because of the 

uncertain nature of how lead exposures cause adverse health effects, this will 

be a probabilistic risk assessment. 

ANL's efforts are part of a larger effort funded by EPA to produce 

probabilistic risk estimates. The three major components of this effort are 

an exposure model , a physiological response model , and a dose/response 

model. The integration of these three components, called the risk model', 

produces the desired risk estimates. ANL is specifically responsible for 

developing a dose/response model and integrating results to form a risk model 

which produces overall risk estimates. 

There are many activities needed to accomplish these things. An 

outline and details of ANL's tentatively planned efforts are described as 

follows. 

2. Outline of Planned Efforts 

The basis for this probabilistic risk assessment is the criteria 

document for lead. However, there are oftentimes gaps between the scientific 

knowledge in the criteria document and the knowledge needed to complete a risk 

assessment. ANL will elici t probability judgements from lead health experts 

to complete this risk assessment. EPA will provide a lis t of lead health 

experts to be consulted for these judgements. The further steps for which ANL 

is responsible include: 
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1. Develop a probability encoding methodology, 

2. Perform expert encoding sessions, 

3. Analyze results of the encoding sessions, 

4. Develop risk estimates, 

5. Perform sensitivity analyses, and 

6. Document methods, models, and results. 

As part of the lead risk assessment program, ANL staff is prepared to 

interact with other groups charged with primary responsibility in developing 

exposure models, physiological effects models, and health effects models. 

This is necessary in order to assure that the submodels fit together to form a 

consistent, overall model, that complete coverage is given in the assessmentof-expert-judgment task, that the risk measures are compatible with these 

models, and that ANL and its subcontractor(s) thoroughly understand the 

model. This last aspect is important if the probability encoding sessions are 

to be conducted in an efficient and knowledgeable fashion. 

Part of this task consists of coordinating with, for example, those 

people with primary responsibility for developing physiological models and 

indices. The goal is to develop mathematical and/or statistical relationships 

between air quality and measures of health effects. It is crucial that 

suitable indices of physiological response be chosen, that relationships 

between physiological response and health effects be developed, and that 

meaningful measures of the risk of adverse health effects be used. 

3. Detailed Description of Planned Efforts 

The exposure model links air quality levels and human activity patterns 

in time and space to produce estimates of lead exposure. The physiological 

model links exposure estimates to produce estimates of physiological 
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response. The physiological response is expressed in terms of physiological 

indices (e.g., blood lead, bone lead, dentine lead, soft tissue lead). 

The dose/response model links levels of physiological response to 

health effects (e.g., reduced heme synthesis, decreased central nervous system 

capability, cognitive/behavioral damage). As mentioned, there are gaps in the 

knowledge base which must be bridged in order to complete this risk 

assessment. The probability judgements of experts will be used to accomplish 

this goal. 

3.1 Develop a Probability Encoding Methodology 

There are a number of practical issues which affect the method to be 

used to quantify expert judgement. The ideal method would assure that bias 

was minimized and would promote the coherence and consistency of assessments 

developed with a particular expert. These goals must be balanced against the 

reality of limited time, money, and people to perform the encodings. 

ANL will be assisted by either SRI International or Woodward Clyde 

Consultants (WCC) in developing the probability encoding methodology for 

lead. Decision analysts from these two organizations have been assisting 

OAQPS in developing a risk assessment methodology for carbon monoxide. 

EPA's choice between these two groups will be influenced by ANL's 

evaluation of the two methodologies and feedback from the Clean Air Science 

Advisory Committee for lead. 

Preparatory material will be developed for the experts. This material 

will be distributed to the experts before the interview dates. Material will 

be prepared for each effect. The purpose is to inform each participant of: 

(1) the exact nature of the judgements which will be sought (specific doseresponse relationships, or other critical exogenous or endogenous variables in 

the risk model), and (2) the general approach which will be used in order to 
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assess this information. At times, the judgements needed from an expert will 

consist of a determination of the significance of the research of another 

person for making probability assignments. In such cases, the participant 

will be instructed to review the research before the interview date. 

This material provided to the experts will also indicate the kinds of 

relevant conditions (health, exposure history, exposure levels, definitions of 

health effects and sensitive groups, etc.) under which the dose-response 

relationships and other uncertain factors will be encoded. 

Worksheets will be prepared to structure the session. These worksheets 

are primarily intended for the use of the assessors. In order to minimize the 

chance of introducing bias during the interview process, the order in which 

questions are asked can be varied between experts and even within a session 

with a given expert. These details will be decided before the interviews take 

place. 

A medical doctor familiar with the health effects of lead will also be 

consulted during the development of the methodology. The role of the medical 

doctor will include assisting ANL in : (1) the design of preparatory and 

i nterview material s to assure that proper terminology is used, (2) setting the 

conditions for which dose/response relationships will be elicited , (3) 

defining health effects, and (4) the phrasing of encoding questions. The 

intent of this collaboration is to insure, to the extent possible, that the 

encoding methodology is medically correct and understandable, and that i t does 

not confound important effects or introduce bias. 

The sub-contractor chosen to continue on this lead risk assessment will be 

responsible for obtaining the services of the needed medical doctor. 

Since encoding of expert judgement is not a process that can be 

completely determined in advance, the assessors must be prepared to adapt the 
planned line of questioning as situations dictate. Conditions (e.g., health, 

exposure history, etc.) under which the assessments will be made must be 

considered and explicitly incorporated into these materials. 

All assessores will be briefed on the assessment methodology, 

assessment materials, and pertinent health issues. The briefing will take 

place at ANL and it will be scheduled in advance of the start of the 

interviews. These materials will be revised as needed during the course of 

the first round of interviews. Two rounds of interviews will be conducted. 

It is desirable that no major revisions be made to the interview methodology 

after the second round of interviews begins. 

There are a number of probability encoding methods that may be employed 

in the interviews. These include (for continuous quantities): 

o fixed value methods - the probability that the uncertain 

quantity lies in a specified range of values is elicited 

from an expert, 

o fixed probability methods - the values of an uncertain 

quantify which bound specified probability interval are 

elicited from an expert, 

o directly drawing points on the distribution curve for 

either the cumulative density function or the probability 

density function, and 

o estimating parameters for a family of distribution 

functions. 

Most popular are the fixed value and fixed probability methods which 

can be used together to perform consistency checks (i.e., do the values 

assessed by a number of methods agree?). Devices like probability wheels 

(modified "wheels of fortune") can be used as visual aids for the expert. 
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The objective in using a variety of assessment methods and consistency 

checks is to maximize the chances of eliciting the "best possible" judgements 

from the expert. 

3.2 Perform Expert Encoding Sessions 

It is anticipated that a total of five health effects will be 

considered in this risk assessment. The sensitive group is children from 

conception through age 6. Three experts will be consulted for each health 

effect, and each expert will be interviewed twice. This is a total of 30 

interviews for the risk assessment. The health experts will be paid a small 

honorarium for each interview session. 

In these interviews, judgements will be elicited on issues from the 

following lists: 

Relationships 

o Bone lead to physiological response 

o Soft-tissue lead to physiological response 

o Blood lead to physiological response 

o Physiological response to health effects 

Health Effect Categories 

o Heme biosynthesis 

o Erythropoietic effects 

o Cognitive/behavioral effects 

o Electrophysiological effects 

(central nervous system) 

(peripheral nervous system) 

o Renal function 

o Cardiovascular 

o Immunological 
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o Carcinogenicity 

o Reproductive/developmental effects 

o Delivery complications 

(the mother) 

(the fetus) 

This information will be developed, as needed, through these planned 

interviews with recognized expert health scientists. The scientific basis for 

these assessments includes the lead criteria document. The goal is to 

quantify, to the extent practical, relevant uncertainties in the dose/response 

model , the physiological model , or the exposure model. 

Assessments will be conducted in 2 rounds. The first round has as one 

major goal that of instructing the expert in the process of eliciting 

probability judgements. It is anticipated that the second round of encoding 

will produce the judgements to be used in computing the final risk estimates. 

Because of the large number of interviews required, ANL will need the 

assistance of decision analysts from either SRI or WCC to complete this phase 

of the risk assessment. It is anticipated that at about three two-person 

teams will be formed from the available pool of assessors to conduct these 

interviews. We estimate that travel will be required to about 10 different 

cities in the midwest and eastern U.S. 

3.3 Analyze the Results of the Assessments 

Encoding results in the form of probabilities will be analyzed to check 

for bias, consistency, and coherence. The intent of this activity is to 

assure that the probability judgements elicited from the experts are the best 

possible. Any details overlooked during the interviews will be resolved with 

the expert (hopefully, over the telephone; in person if necessary). 
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Three experts will be interviewed for each health effect. Each set of 

judgements will be viewed as uniquely important in the risk assessment 

process, and this uniqueness will be maintained as risk estimates are 

developed. If diverse judgements are averaged in any way, this will be 

clearly pointed out. These differences in judgement are important sources of 

uncertainty. 

The anonymity of the health experts will be preserved in all public 

documents prepared through this risk assessment. It is not planned to make 

tape recordings of these sessions because of their limited value; it is time 

consuming to review these tapes after the interview session. Instead, 2 

assessors will conduct each probability encoding session and they will be very 

careful to obtain all needed results by the end of the interview. 

3.4 Develop Risk Estimates 

Risk estimates will be developed for each of 10 cities, for each of 

approximately 10 alternative NAAQS (5 levels, each at 2 averaging times) to be 

specified by the EPA. Risk output measures will be of three types, benchmark 

risk, head count risk, and expected head counts. The head count estimates 

will be performed for both incidences (counts multiple incidences for a single 

person in a prescribed time period) and persons. To obtain these estimates, 

it will be necessary to integrate the outputs of the exposure model , the 

physiological response model , and the dose/response model developed in this 

and other efforts in the EPA's lead risk program. 

Benchmark risk is a simple measure of risk to a sensitive population. 

It does not require that an account be made of the activities and movements 

of sensitive individuals. The focus is on the probability that peak 

concentrations occur at high enough levels to cause health effects. This 

measure is an estimate of the risk that pollutant concentrations will occur 
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that would cause a specified percentage, say 10%, of the persons in the most 

sensitive population to suffer adverse health effects, i f exposed. To 

calculate this measure, i t is necessary to: (1) define exactly what is meant 

by an adverse health effect, and (2) construct a probability distribution for 

each of two factors (nth highest concentration level over the subject time 

period, and the dose which would adversely affect a specified percent of the 

most sensitive individuals experiencing the adverse health effect). Given 

these distributions, benchmark risk is calculated via a convolution integral. 

Head count risks deal with the actual numbers of sensitive people who 

may experience adverse health effects. These estimates consider uncertainties 

in (1) dose-response relationships, (2) air pollutant concentration levels, 

amd (3) human activities and locations. Two measures of head count risk will 

be calculated: incidences and persons. The later measure counts an 

individual only once in the subject time period even though he may have 

experienced more than one occurrence of a health effect. The former counts 

all occurrences of a health effect, including multiple occurrences for an 

individual person. These risks will be in the form of probability 

distributions. 

Expected head count measures, both incidences and persons, are derived 

from head count risk distributions. 

3.5 Perform Sensitivity Analyses 

Sensitivity analyses will be performed to investigate the relative 

contributions of various factors to uncertainty in the risk outputs (i.e., 

estimates of benchmark risk, head count risk, and expected head count risk). 

3.6 Document Methods, Models, and Results 

ANL will prepare a draft and final draft report for this portion of the 

risk assessment program. As background material, it will summarize the other 
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lead risk program reports on exposure modeling and physiological modeling. 

The overall model which integrates these components will be presented. 

Results of the expert encoding sessions will be documented in detail, along 

with a thorough description of the encoding methodology. All results of the 

encoding sessions (dose-response relationships, exogenous and endogenous 

variables) will be clearly displayed and discussed. Discussion will cover 

such issues as bias, consistency, and coherence of encoded judgements. Risk 

output measures will be presented and thoroughly discussed. 

Any assumptions needed to complete the estimates will be documented and 

the scientific basis will be referenced. The sensitivity of results to these 

assumptions, the structure of models and submodels, and encoded information 

will be reported.