This course was rated in the top 10 in 2022!

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? The answers to these questions are paramount to the practice of industrial hygiene. Unfortunately, the variability observed in occupational exposure levels represents a considerable challenge to obtaining them reliably. Despite available and well-described theoretical approaches to tackle these issues, including the AIHA monograph, "A Strategy for Assessing and Managing Occupational Exposures," or in the recent European guidelines, there is a lack of practical tools to support day-to-day decision-making when analyzing exposure measurement data. Even fewer tools tackle frequent methodological issues such as the presence of non-detects or present the results in a format easy to communicate.

First available in 2015, and updated in 2018, the Expostats platform (www.expostats.ca) is a freely available web application developed at the University of Montreal, Canada, aiming to support IH practitioners for the interpretation of occupational exposure measurements through Bayesian statistics. This PDC presents the challenge of exposure variability and the current theory underpinning the interpretation of workplace exposure levels. It also provides a primer in Bayesian statistics and demonstrates how decision-making can be conducted using the Expostats tools.

Value Added

Participants will leave with the ability to perform state-of-the-art data interpretation using the www.expostats.ca platform.

Outline

  • Exposure Variability - Modeled Using the Lognormal Distribution
  • Parameters Used for Risk Assessment
  • Dealing with uncertainty
  • Introduction to Bayesian Statistics
  • Recent Proposed Guidelines for Exposure Data Interpretation
  • The Expostats Platform – introduction and Hands-on Session with exercises in breakout rooms

Learning Outcomes

Upon completion, the participant will be able to:

  • Discuss the impact of workplace exposure variability on the uncertainty surrounding IH risk assessment.
  • Describe the most common metrics used to define overexposure.
  • Explain the basic principles underlying Bayesian statistics and how they can be leveraged in IH data analysis.
  • Use Expostats to perform a risk assessment for a Similar Exposure Group.
  • Implement recent sampling strategies guidelines proposed in the U.S. and in Europe.

Transfer of Knowledge

Instructor(s) will evaluate participants’ understanding of the materials presented based on:

  • Hands-on demonstrations and practicum
  • Interactive games
  • Practice exercises

Business Case/IH Value Statement

Traditional exposure statistics rely on confidence intervals and hypothesis tests to demonstrate overexposure, which is sometimes not easy to grasp by decision-makers. The methods described in the PDC will allow practitioners to express their results in a form that is better understood and easier to act upon for management.

Instructor:

Jerome Lavoue, University of Montreal, Montreal, QC, Canada

Originally trained as a chemist in France in 1996, Lavoue completed an MSc in Toxicology and a Ph.D. in exposure sciences at the University of Montreal in Canada. After postdoctoral studies in the field of industrial hygiene at the Institute for work and health in Lausanne, Switzerland, he was hired as a professor of industrial hygiene in 2008 at the Department of environmental and occupational health at the University of Montréal. His research focuses on occupational exposure assessment, with a special focus on retrospective assessment for epidemiological studies, development of statistical methods for industrial hygiene data analysis, and, more recently, the development of software to facilitate data analysis for industrial hygienists, including the www.expostats.ca website. Lavoue has been teaching industrial hygiene data interpretation at the university and for continuous education for 15 years, and is the lead author of the chapter about sampling and data interpretation strategies in a recent francophone industrial hygiene monograph edited by the Quebec association for occupational safety and health.

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This is a great course on IH Statistics and decision-making. I enjoyed the interactive quizzes and would recommend all IH's take this course!

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The instruction was amazing! Pace of the course was great, and I really enjoyed the course

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