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Using the Bayesian Calculation Platform to Interpret Industrial Hygiene Exposure Levels (AIHce EXP 2019 OnDemand)

Course Description:
Recorded at AIHce EXP 2019

Is a group compliant with the OEL? Are individuals within this group likely to experience higher risk than the group average? What effect does an intervention have on the underlying exposure distribution? Despite available and well described theoretical approaches to answer these questions, there is a lack of practical applications to support day-to-day decision making when analyzing exposure measurement data. Even fewer applications tackle frequent methodological issues such as the presence of nondetects or present the results in a format easy to communicate. The Expostats platform ( is a freely available web application developed at University of Montreal, Canada, to support IH practitioners in the interpretation of occupational exposure measurements. The Expostats tools use Bayesian statistics to analyze data from a similar exposure group, evaluate within and between worker variability, and estimate the association of a categorical variable (e.g. before/after, or morning/day/night shift) with exposure levels. The aim of this education session is to present the current theory underpinning the interpretation of workplace exposure levels and to demonstrate how decision making can be conducted using the Expostats tools.

Contact Hours:

Presentation Date:

Jérôme Lavoué, University of Montreal, Canada.