Exposure modeling in occupational hygiene decision making

Monika Vadali, Gurumurthy Ramachandran, John Mulhausen

Research output: Contribution to journalReview articlepeer-review

22 Scopus citations

Abstract

The primary objective was to develop a framework for using exposure models in conjunction with two-dimensional Monte Carlo methods for making exposure judgments in the context of Bayesian decision analysis. The AIHA exposure assessment strategy will be used for illustrative purposes, but the method has broader applications beyond these specific exposure assessment strategies. A two-dimensional Monte Carlo scheme by which the exposure model output can be represented in the form of a decision chart is presented. The chart shows the probabilities of the 95th percentile of the exposure distribution lying in one of the four exposure categories relative to the occupational exposure limit (OEL): (1) highly controlled (<10% of OEL), (2) well controlled (10-50% of OEL), (3) controlled (50-100% of OEL), and (4) poorly controlled (>100% of OEL). Such a decision chart can be used as a prior in the Bayesian statistical framework, which can be updated using monitoring data to arrive at a final decision chart. Hypothetical examples using commonly used exposure models are presented, along with a discussion of how this framework can be used given a hierarchy of exposure models.

Original languageEnglish (US)
Pages (from-to)353-362
Number of pages10
JournalJournal of occupational and environmental hygiene
Volume6
Issue number6
DOIs
StatePublished - Jun 1 2009

Keywords

  • Bayesian decision making
  • Exposure models
  • Two-dimensional Monte Carlo

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