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Exposure modeling in occupational hygiene decision making.
Vadali-M; Ramachandran-G; Mulhausen-J
J Occup Environ Hyg 2009 Jun; 6(6):353-362
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.
Exposure-assessment; Mathematical-models; Occupational-exposure; Occupational-hazards; Occupational-health; Risk-analysis; Statistical-analysis; Work-analysis; Work-environment; Workplace-studies; Author Keywords: Bayesian decision making; exposure models; two-dimensional Monte Carlo
Gurumurthy Ramachandran, University of Minnesota, Division of Environmental Health Sciences, School of Public Health, MMC 807, 420 Delaware St. SE, Minneapolis, MN 55455
Issue of Publication
Journal of Occupational and Environmental Hygiene
University of Minnesota, Twin Cities
Page last reviewed: March 11, 2019
Content source: National Institute for Occupational Safety and Health Education and Information Division