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Bayesian Analysis of Plutonium Bioassay Data at Los Alamos National Laboratory

Poudel, Deepesh1; Miller, Guthrie2; Klumpp, John A.1; Bertelli, Luiz1; Waters, Tom L.1

Erratum

There is an error in the paper titled “Bayesian analysis of plutonium bioassay data at Los Alamos National Laboratory” ( Poudel et al. 2018 ), which appeared in the December 2018 issue. The second to last paragraph of the Discussion section should read:

“The ID code uses the systemic model published in ICRP Publication 67 ( ICRP 1993 ) to describe the biokinetics of plutonium once the material is introduced into the blood. It is important to note that the systemic model published in Leggett et al. (2005) represents an updated version of the ICRP 67 systemic model. The model was developed to reflect the discrepancies observed between the ICRP 67 model predictions and the more recent data, particularly bone and liver deposition fractions. The upcoming ICRP publication on occupational intakes of radionuclides also recommends the systemic model published in Leggett et al. (2005) . A future version of the code can include this revised version of the systemic model.”

In addition, in the model description for the IEE model (in Table 3), the parameter st should be 4 × 10 −3 d −1 . Finally, the notation “e(50),” when followed by units Sv or rem, should be replaced by “E(50),” as the former is generally used to denote the committed effective dose coefficients (in Sv Bq −1 ).

Health Physics. 116(5):722, May 2019.

doi: 10.1097/HP.0000000000000933
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Erratum

The main concern of operational internal dosimetry is to detect intakes and estimate doses to the worker from a series of bioassay measurements. Although several methods are available, the inverse problem of internal dosimetry—i.e., determination of time, amount, and types of intake given a set of bioassay data—is well suited to a Bayesian approach. This paper summarizes the Bayesian methodology used at Los Alamos National Laboratory to detect intakes and estimate doses from plutonium bioassay measurements. Some advantages and disadvantages of the method are also discussed. The successful application of Bayesian methods for several years at Los Alamos National Laboratory, which monitors thousands of workers annually for plutonium, indicates that the methods can be extended to other facilities.

1Radiation Protection Division, Los Alamos National Laboratory, P.O. Box 1663, MS G761, Los Alamos, NM 87545;

2Los Alamos National Laboratory (retired), Santa Fe, NM.

The authors declare no conflicts of interest.

For correspondence contact: Deepesh Poudel, P.O. Box 1663, MS G761, Los Alamos, NM 87545, or email at dpoudel@lanl.gov.

(Manuscript accepted 6 June 2018)

© 2018 by the Health Physics Society