Application of Markov chain Monte Carlo analysis to biomathematical modeling of respirable dust in US and UK coal miners

Details

• Alternative Title:
  Regul Toxicol Pharmacol
• Personal Author:
  Sweeney, Lisa M. ; Parker, Ann ; Haber, Lynne T. ; Tran, C. Lang ; Kuempel, Eileen D.
• Description:
  A biomathematical model was previously developed to describe the long-term clearance and retention of particles in the lungs of coal miners. The model structure was evaluated and parameters were estimated in two data sets, one from the United States and one from the United Kingdom. The three-compartment model structure consists of deposition of inhaled particles in the alveolar region, competing processes of either clearance from the alveolar region or translocation to the lung interstitial region, and very slow, irreversible sequestration of interstitialized material in the lung-associated lymph nodes. Point estimates of model parameter values were estimated separately for the two data sets. In the current effort, Bayesian population analysis using Markov chain Monte Carlo simulation was used to recalibrate the model while improving assessments of parameter variability and uncertainty. When model parameters were calibrated simultaneously to the two data sets, agreement between the derived parameters for the two groups was very good, and the central tendency values were similar to those derived from the deterministic approach. These findings are relevant to the proposed update of the ICRP human respiratory tract model with revisions to the alveolar-interstitial region based on this long-term particle clearance and retention model.
• Subjects:
  Bayesian Analysis Bayes Theorem Calibration Coal Mining Dust Great Britain Humans Inhalation Exposure Lung Markov Chains Models, Theoretical Monte Carlo Method Occupational Exposure

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• Source:
  Regul Toxicol Pharmacol. 66(1):47-58.
• Pubmed ID:
  23454101
• Pubmed Central ID:
  PMC4676727
• Document Type:
  Journal Article
• Funding:
  CC999999/Intramural CDC HHS/United States
• Place as Subject:
  United States
• Volume:
  66
• Issue:
  1
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:a6a8874c9b49397ca8d54546f0c87d190daad9082e6dcc72c929ee474675be1e
• Download URL:
  https://stacks.cdc.gov/view/cdc/36810/cdc_36810_DS1.pdf
• File Type:
  [PDF - 843.36 KB ]