AIHA University Live Online PDC: Understanding Exposure Variability and IH Statistics

Earn 7.5 Contact Hours

Member $460 | Nonmember $600 | Student $460

Accurate exposure assessment is critical in protecting worker health and ensuring a safe workplace. Understanding whether a group is compliant with the Occupational Exposure Limit (OEL), identifying individuals at higher risk, and evaluating the impact of interventions on exposure levels are essential questions for industrial hygiene practitioners.

Are the groups compliant with the OEL? Are individuals within these groups likely to experience higher risks than the group average? What effect does an intervention have on the underlying exposure distribution? What do the measurements collected tell us about all other days when monitoring exposure levels was not possible?

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 reliable answers. Despite well-described theoretical approaches, such as the AIHA monograph "A Strategy for Assessing and Managing Occupational Exposures," current European guidelines, and the upcoming new NIOSH recommendations, there is a lack of practical tools to support day-to-day decision-making when analyzing exposure measurement data. Even fewer tools address frequent methodological issues, such as the presence of non-detects, or present results in an easily communicable format.

Since 2015, the Expostats platform, a freely available web application developed at the University of Montreal, Canada, has aimed to support IH practitioners in interpreting occupational exposure measurements through Bayesian statistics.

This PDC addresses 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, as well as the newly released IHSTAT_Bayes, a version of the well-known IHSTAT program infused with the Expostats calculation engine.

Learning Objectives

After this online PDC, participants 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 and their applications in industrial hygiene practice.
• Explain the basic principles underlying Bayesian statistics and how they can be leveraged in IH data analysis to improve accuracy.
• Apply recent sampling and data interpretation strategies guidelines proposed in the U.S. and in Europe to enhance compliance and effectiveness.
• Utilize the Expostats platform tools to:
  • Perform risk assessment for a Similar Exposure Group.
  • Quantify the association between exposure levels and a categorical variable such as evaluating the effect of an intervention

Schedule (Eastern Time)

• 8:00 AM – Course Starts
  
• 10:00 – 10:15 AM – 15-minute Break
• 12:00 – 1:00 PM – 1-hour Break
• 3:15 – 3:30 PM – 15-minute Break
• 5:00 PM – Course Concludes

*Break times are subject to change and will total 1.5 hours.

Presenter

Jérôme Lavoué, Ph.D., MS
Initially trained as an industrial chemist in France, Jérôme holds a master's degree in environmental and occupational health and a Ph.D in public health from University of Montreal. His research interests include exposure assessment sciences, exploitation of exposure databases, development of strategies for risk analysis in the workplace, and the creation of practical tools. Jerome led the creation of the of the Expostats exposure data analysis toolset and, more, recently, of the Webexpo open-source library of algorithms for the Bayesian analysis of exposure measurements, which led to the creation of the IHSTAT_Bayes practical data analysis tool.

**This live event will be administered in our LMS through zoom meeting. Please view our FAQ for additional information.**