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This working document prepared by NIOSH’s Division of Compensation Analysis and Support (DCAS) or its contractor for use in d iscussions with the 

ABRWH or its Working Groups or Subcommittees. Draft, preliminary, interim, and White Paper documents are not final NIOSH or ABRWH (or their 

technical support and review contractors) positions unless specifically marked as such. This document represents preliminary positions taken on technical 

issues prepared by NIOSH or its contractor. NOTICE: This report has been reviewed to identify and redact any information that is protected by the Privacy 

Act 5 USC §552a and has been cleared for distribution.

Draft Criteria for the Evaluation and Use of Internal Exposure Coworker Datasets

J.W. Neton, Ph.D., CHP

June 17, 2014

1.0 INRODUCTION

Under the Energy Employees Occupational Illness Compensation Program Act (EEOICPA), NIOSH 

completes dose reconstructions for employees with cancer who are covered under the provisions of the 

Act. The methods used to complete these dose reconstructions are prescribed in 42 C.F.R. Part 82 

(USHHS 2002). While the use of individual personnel monitoring is preferred in the completion of dose 

reconstructions, these data are oftentimes not available because either the worker was monitored and the 

data have been lost or the worker was potentially exposed and not monitored. In the latter case, NIOSH 

has observed that, in accordance with the practices in effect at the time, only workers with the highest 

exposure potential were monitored or, in some cases, monitoring was conducted on representative 

members of the exposed population. In the absence of individual monitoring data, 42 C.F.R. Part 82 

allows for the use other worker’s data to complete dose reconstructions. Section 82.2 (b) states:

If individual monitoring data are not available or adequate, dose reconstructions may use 

monitoring results for groups of workers with comparable activities and relationships to the 

radiation environment.

The groups of workers specified in §82.2(b) are generically known as coworkers. Coworkers are 

considered to be workers at the same site whose radiation monitoring measurements are considered to be

representative or plausibly bounding of those received by one or more workers with no individual 

monitoring data. Depending on the amount and specificity of the available worker and workplace data, 

the level of detail included in coworker models can vary greatly. For dose reconstructions under 

EEOICPA, it is often difficult to locate a worker in a specific job at a specific location. Because of this, 

NIOSH has chosen to develop coworker models that cover a wide range of workers for a specific 

radionuclide at a specific time. 

2.0 CRITERIA FOR THE EVALUATION OF THE ADEQUACY OF COWORKER DATASETS

As indicated above, coworker datasets should be established from monitored workers with comparable 

activities and relationships to the radiation environment. To accomplish this, one must carefully evaluate 

each coworker dataset to ensure that it is either representative of the distribution of exposures for the
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This working document prepared by NIOSH’s Division of Compensation Analysis and Support (DCAS) or its contractor for use in d iscussions with the 

ABRWH or its Working Groups or Subcommittees. Draft, preliminary, interim, and White Paper documents are not final NIOSH or ABRWH (or their 

technical support and review contractors) positions unless specifically marked as such. This document represents preliminary positions taken on technical 

issues prepared by NIOSH or its contractor. NOTICE: This report has been reviewed to identify and redact any information that is protected by the Privacy 

Act 5 USC §552a and has been cleared for distribution.

intended population or that it provides a plausible upper bound for those workers1. Criteria to consider 

when determining the adequacy of a dataset are provided below.

2.1 Data Adequacy

The measurement technique used to monitor the worker should be evaluated to ensure that the technique 

can quantitatively measure the exposure of interest. For internal exposure monitoring, this evaluation 

should include a review of the sample collection methods, any chemical processes employed, and the 

radiation counting equipment used. Among the items to be considered are: 1) representativeness of the 

bioassay sample collection method; 2) radiochemical recovery if chemical extraction techniques are 

used; 3) reduction in counting efficiency for alpha emitters due to self –absorption; and 4) reliability of 

the radiation counting equipment. For external exposure monitoring, it is important to consider the 

ability of the monitoring devices to detect the energies and types (beta, gamma, or neutron) of radiation 

that were present in the workplace. In addition, a review of the adequacy of the calibration methods 

employed and the extent that fading is a factor should be addressed.

The amount of the available monitoring data should also be evaluated to determine if there are sufficient 

measurements to ensure that the data are either bounding or representative of the exposure potential at 

the facility. Facilities with the potential for internal and/or external exposure to a large percentage of the 

workforce would require many more samples than one in which the potential for exposure was limited to 

just a few workers. In addition, the variability of the exposure potential should be considered. It has 

been observed, for example, that some National Laboratories conducted work under many different 

experimental configurations, resulting in a wide variety of exposure potentials. In this case, it might not 

be possible to generate a single coworker model that adequately captures all categories of unmonitored 

worker doses. 

Although there is no hard and fast rule for the minimum number of data points required to represent a 

given time interval, approximately fifteen values has been cited as a reasonable number for performing 

statistical tests on censored datasets (Singh et al. 2010). Because our program estimates parameters from 

the data, a default minimum of 30 values is recommended per modeled interval. The minimum number 

of samples should, of course, be considered in light of the number of worker’s potentially expose to the 

airborne source-term. For example, the number of samples necessary to be representative of the 

exposures at a uranium foundry, where airborne activity is generally widespread, will be greater that the 

number required of a small glove box operation involved in the manipulation of plutonium parts. 

 1 Under 42 CFR 83.13(c)(1), radiation doses are considered to be estimated with sufficient accuracy if NIOSH has 

established that it has access to sufficient information to estimate the maximum radiation dose, for every type of 

cancer for which radiation doses are reconstructed, that could have been incurred in plausible circumstances.
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This working document prepared by NIOSH’s Division of Compensation Analysis and Support (DCAS) or its contractor for use in d iscussions with the 

ABRWH or its Working Groups or Subcommittees. Draft, preliminary, interim, and White Paper documents are not final NIOSH or ABRWH (or their 

technical support and review contractors) positions unless specifically marked as such. This document represents preliminary positions taken on technical 

issues prepared by NIOSH or its contractor. NOTICE: This report has been reviewed to identify and redact any information that is protected by the Privacy 

Act 5 USC §552a and has been cleared for distribution.

Finally, if electronic records or summary databases are used to develop the coworker model, these 

should be reviewed against a representative sampling of original data where possible to ensure that they 

contain a complete and unbiased listing of all the data collected by the site. 

2.2 Application of Monitoring Data to Unmonitored Workers

Prior to applying a site’s worker monitoring data to estimate the exposures of unmonitored workers, the 

type of personnel monitoring program employed at the covered facility must be established. In general, 

three types of monitoring programs have been employed at sites covered under EEOICPA. These 

programs, listed in hierarchical order of preference for use in coworker modeling are: 1) routine, 

representative sampling of the workers; 2) routine measurement of workers with the highest exposure 

potential; and 3) the collection of samples after the identification of an incident. Because they are not 

representative of the overall distribution of exposures, programs that rely on measurement of the highest 

exposed workers or are incident based require more careful consideration.

For routine monitoring programs, a review of the program should be conducted to determine the basis 

for the selection of program participants. It must be established who was monitored and why they were 

monitored. In this evaluation there must be some demonstration that the monitored population consisted 

of: 1) a representative sample of the exposed population or 2) the workers with the highest exposure 

potentia1. In these cases, the assignment of a coworker dose from the distribution of measured values 

would either be claimant favorable in the first case or representative of the worker’s exposure in the 

second case.

In some situations, sites have relied on incident-based sampling to monitor worker’s exposure. Because 

there are temporal gaps in the monitoring data, it is more difficult to demonstrate that this type of 

sampling can be used to develop representative or plausibly bounding coworker models. Prior to the use 

of incident-based sampling in a coworker model, the effectiveness of workplace controls, must be 

demonstrated through the review of routine air monitoring samples and/or periodic contamination 

surveys. If one can demonstrate that the effectiveness of workplace administrative and/or engineering 

controls was adequate to prevent exposures, except during upset conditions, it may be possible to use 

incident-based sampling in a coworker model

2.3 Appropriateness of the Modeled Data for the Unmonitored Population

The appropriateness of the application of the monitored population’s data to those workers who were 

unmonitored should be evaluated. It is important to establish the exposure types and work activities of 

the unmonitored workers. A review of the job types and categories of the unmonitored workers should 

be conducted to determine if there are special exposure categories that might not be covered by the 

monitored population. 
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This working document prepared by NIOSH’s Division of Compensation Analysis and Support (DCAS) or its contractor for use in d iscussions with the 

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technical support and review contractors) positions unless specifically marked as such. This document represents preliminary positions taken on technical 

issues prepared by NIOSH or its contractor. NOTICE: This report has been reviewed to identify and redact any information that is protected by the Privacy 

Act 5 USC §552a and has been cleared for distribution.

If the unmonitored population can be determined through a source term evaluation to have no potential 

for exposure, then it is not necessary to establish a coworker model. In this case, it might be sufficient 

to include ambient environmental dose in the dose reconstructions. 

3.0 ANALYSIS OF MONITORING DATA

If after review of the monitoring program data, it is established that: 1) there is sufficient data to 

construct a general coworker model; and 2) the data can reasonably be represented by a log-normal 

distribution: the geometric mean and geometric standard deviation can be used to represent the 

distribution of exposures observed in the overall monitored population. For workers that are considered 

to have worked in environments with a potential for elevated exposure, the 95th percentile of the 

distribution should be used as an upper bound of their exposure during the modeled time period. (Note: 

Although it could be argued that the job categories that fall under this criterion should be listed, any 

attempt to do so might be artificially restrictive. Based on past practice, NIOSH believes that this 

decision is most accurately made using the information available in the site profiles, the claimant 

interview and other documents that might be in the worker’s records. This also applies to the following 

category of intermittently exposed workers.) For workers who were less likely to be highly and/or were 

intermittently exposed in the workplace, the full distribution (i.e., the geometric mean and its associated 

standard distribution) should be used as representative of their potential for exposure during the modeled 

period. 

Note: NIOSH is considering a modification of the OPOS approach to include a time-weighted average 

analysis. We have conducted an analysis of the SRS americium coworker model using a time-weighted 

averaging technique and have determined that this method more appropriately accounts for the 

variability in excretion patterns, including this issue associated with carry-over from positive bioassay 

results in previous years. NIOSH is interested in further discussions on this.

3.1 Time Interval of the Modeled Data

The amount of data that are available will directly influence the time intervals used in the coworker 

model. As stated in section 2.2, a minimum number of 30 samples per monitored interval is

recommended. Based on a review of the currently available datasets, a modeled interval of one year 

strikes a good compromise between the availability of data and the need to ensure that the samples are 

contemporaneous with ongoing operations. In certain situations, there are sufficient data to develop 

quarterly models, but this is the exception rather than the norm. If, because of data limitations, it is 

necessary to consider time intervals beyond on year in the coworker model, any changes in site practices 

or operations should be evaluated to ensure that the data can be validly combined. 
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This working document prepared by NIOSH’s Division of Compensation Analysis and Support (DCAS) or its contractor for use in d iscussions with the 

ABRWH or its Working Groups or Subcommittees. Draft, preliminary, interim, and White Paper documents are not final NIOSH or ABRWH (or their 

technical support and review contractors) positions unless specifically marked as such. This document represents preliminary positions taken on technical 

issues prepared by NIOSH or its contractor. NOTICE: This report has been reviewed to identify and redact any information that is protected by the Privacy 

Act 5 USC §552a and has been cleared for distribution.

4.0 EVALUATION OF STRATIFICATION

The general coworker model described above could contain a combination of several different 

distributions. As such, the basic criteria discussed above might not sufficiently cover the range of 

exposures encountered by certain sub-populations of workers. There may be an underlying job category 

that is from a more highly exposed stratum of workers that would not be adequately bounded. Although 

this could occur with any job category/classification, it has often times been a concern when building 

trades workers are included in the general distribution with all monitored workers. If accurate job 

categories and/or descriptions can be obtained for the worker’s making up the general dataset, and there 

is reason to believe that one of the categories is more highly exposed, the distribution of the potentially 

more highly exposed population should be evaluated as a separate standalone distribution.

As described above, workers with a higher potential for exposure would be considered to have been 

exposed at the 95th percentile of the general worker distribution. Thus, the geometric mean and standard 

deviation of the stratified subset should be compared to the 95th percentile of the general distribution. If 

it can be shown that the use of the full distribution in the stratified subset is more favorable than using 

the 95th percentile of the general distribution, the full distribution of the stratified subset should be used 

for those workers that fall into this category. 

Note: NIOSH is working on the feasibility of such an evaluation and hopes to provide input on how this 

might be accomplished in the near future. Reliance on the probability of causation (PC) to make such a 

determination, although somewhat complicated, seems doable. If a predictable relationship between the 

PC generated for the full distribution and the use of the 95th percentile as a constant for the general 

distribution can be established, one might be able to establish a truly practically significant difference. 

Preliminary results seem to indicate that PC outcome associated with the full distribution can be 

generated by using a constant value that is around the 84th percentile. If this were true, then it would 

make sense to stratify distributions only if the ~84th percentile of the full distribution of the stratified 

dataset is larger than the 95th percentile of the general distribution of all monitored workers. 

5.0 REFERENCES

Singh, A., N. Armbya, and A. K. Singh, 2010, ProUCL Version 4.1.00 Technical Guide (Draft), 

EPA/600/R-07/041, U.S. Environmental Protection Agency, Office of Research and Development, 

Washington, D.C., May. [SRDB Ref ID: 113464]

U.S. Department of Health and Human Services. Methods for radiation dose reconstruction under the

Energy Employees Occupational Illness Compensation Program Act of 2000, final rule. Washington, 

DC: U.S. Government Printing Office; 42 CFR Part 82; 2002.
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This working document prepared by NIOSH’s Division of Compensation Analysis and Support (DCAS) or its contractor for use in d iscussions with the 

ABRWH or its Working Groups or Subcommittees. Draft, preliminary, interim, and White Paper documents are not final NIOSH or ABRWH (or their 

technical support and review contractors) positions unless specifically marked as such. This document represents preliminary positions taken on technical 

issues prepared by NIOSH or its contractor. NOTICE: This report has been reviewed to identify and redact any information that is protected by the Privacy 

Act 5 USC §552a and has been cleared for distribution.

U.S. Department of Health and Human Services. Methods for radiation dose reconstruction under the

Energy Employees Occupational Illness Compensation Program Act of 2000, final rule. Washington, 

DC: U.S. Government Printing Office; 42 CFR Part 83; 2002.