The Quantitative Microbial Risk Assessment Interdisciplinary Instructional Institute (QMRAIII) – A Platform for Cross Disciplinary Training of Engineers with Social and Biological Scientists to Address Public Health Issues

Jade Mitchell; Mark H. Weir; Julie Libarkin; Joan B. Rose

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Conference: 2017 ASEE Annual Conference & Exposition
Location: Columbus, Ohio
Publication Date: June 24, 2017
Start Date: June 24, 2017
End Date: June 28, 2017
Conference Session: Multidisciplinary Course Efforts
Tagged Division: Multidisciplinary Engineering
Page Count: 11
DOI: 10.18260/1-2--28995
Permanent URL: https://peer.asee.org/28995
Download Count: 673

Paper Authors

biography

Jade Mitchell Michigan Sate University, Dept. of Biosystems and Agricultural Engineering

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Dr. Jade Mitchell is an Assistant Professor in the Department of Biosystems and Agricultural Engineering at Michigan State University. She received her B.S. from the University of Pittsburgh in Civil and Environmental Engineering, M.S. in Civil Engineering and Ph.D. in Environmental Engineering from Drexel University. Dr. Mitchell is keenly interested in supporting environmental and human health decision making through the use of integrated risk and decision frameworks. Her work includes development of new frameworks, models and data sets toward this end. Dr. Mitchell has specific experience in quantitative microbial risk assessment (QMRA) and she conducted her graduate research under the multi-University, multi-disciplinary, Center for Advancing Microbial Risk Assessment (CAMRA), a jointly funded US EPA and DHS Center of Excellence. After joining MSU, she became affiliated with CAMRA as a principal investigator. Her lab conducts both computational risk modeling research and fundamental research. Her current work and future interests lie at the intersection of chemical and microbial stressors where understanding trade-offs, benefits and risks deviate from existing risk paradigms and require new data, tools and frameworks. Her future research goals include applications of risk-based decision making to water infrastructure management, and emerging hazards such as antibiotic resistance. She is managing editor and a developer of the QMRAwiki, an interactive, online tool for the QMRA community. Dr. Mitchell has also been involved in developing and teaching training workshops in QMRA for several years. She was recently awarded a nearly $1M grant from the National Institutes of Health to develop a new course, models and tools to support interdisciplinary engagement in QMRA.

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Mark H. Weir The Ohio State Universiry

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Mark H. Weir earned his BS in Environmental Engineering from Wilkes University and Ph.D. in Environmental Engineering from Drexel University. He worked as the Associate Director of the Center for Advancing Microbial Risk Assessment. He worked in risk research and engineering with the US EPA until leaving for a faculty position at Temple University. While at Temple he served as the Acting Division Director of the Environmental Health Division in the College of Public Health. Dr. Weir is now at The Ohio State University working with both the College of Public Health and College of Engineering. He specializes in predictive water quality and risk models constructed to be easy to use for operations workers and managers.

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Julie Libarkin

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Dr. Libarkin is a Professor of Geoscience Education at Michigan State University in the Department of Earth and Environment Sciences and CREATE for STEM Institute for Research on Science and Mathematics Education. Currently, her research focuses on cognition, assessment of student learning, validity and reliability in research, curriculum and visual design, and discipline-based education research.

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Joan B. Rose

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Abstract

The recent and tragic water crisis in Flint, MI highlights the need for better linkages between engineers, public health agencies and public policy officials. Quantitative microbial risk assessment (QMRA) is an interdisciplinary field and research domain that addresses exposures to microbial pathogens through the environment. It is a widely accepted framework for the study of water quality and food safety. QMRA is most often performed by engineers because it is computationally intensive to mathematically model dynamic physical, chemical and biological processes from source to adverse health outcomes in a receptor. However, it relies heavily on multidisciplinary contributions for effective implementation. Risk management includes the design of engineering controls but also risk communication and risk perception - social science topics that are integral components of risk analyses. Furthermore, exposure to microbial agents is associated with substantial variability and uncertainty in behavior across the population. Despite the utility of the QMRA approach, few biological or social scientists are trained in this process or have sufficient statistical and quantitative skills to undertake such analyses. Similarly, few engineers possess the necessary skills in the social sciences to adequately address issues of human behavior that affect risks associated with exposure to pathogenic agents or responses to health risks. Therefore, we developed an intensive short course to enhance multidisciplinary cross training and graduate research through a combination of lectures and experiential learning opportunities – hands-on exercises and a group project. Through a comprehensive evaluation plan of the courses conducted in 2015 and 2016, we assessed the expanded ability of the course to improve outcomes for engineers in areas of the risk paradigm not traditionally emphasized in their graduate programs. Likewise, we tested the ability of the course to improve the quantitative and modeling skills in participants with backgrounds in social and behavioral sciences. The survey instruments were developed to evaluate both real and perceived knowledge of the participants. This talk focuses on our assessment of the extent to which perception was changed by learning. Participants completed identical pre- and post-workshop surveys containing five Perceptions scales (Perceptions of: QMRA-Related Ability, QMRA-Specific Ability, Knowledge – Hazard Identification, Knowledge – Dose Response and Exposure Assessment, Knowledge - Risk Management). This paper describes the structure of the course, content, pedagogy, and the lessons learned through the participant evaluation and perception of learning. Modifications to the course in response to participant comments were made between the 2015 and 2016 course and will be presented as well. Finally, this paper will serve as a model going forward for our subsequent short courses and may also be used as a model for cross disciplinary training of engineers within other domains that require social science integration.

Citation
Format

Mitchell, J., & Weir, M. H., & Libarkin, J., & Rose, J. B. (2017, June), The Quantitative Microbial Risk Assessment Interdisciplinary Instructional Institute (QMRAIII) – A Platform for Cross Disciplinary Training of Engineers with Social and Biological Scientists to Address Public Health Issues Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28995

TY - CPAPER
AB - The recent and tragic water crisis in Flint, MI highlights the need for better linkages between engineers, public health agencies and public policy officials. Quantitative microbial risk assessment (QMRA) is an interdisciplinary field and research domain that addresses exposures to microbial pathogens through the environment. It is a widely accepted framework for the study of water quality and food safety. QMRA is most often performed by engineers because it is computationally intensive to mathematically model dynamic physical, chemical and biological processes from source to adverse health outcomes in a receptor. However, it relies heavily on multidisciplinary contributions for effective implementation. Risk management includes the design of engineering controls but also risk communication and risk perception - social science topics that are integral components of risk analyses. Furthermore, exposure to microbial agents is associated with substantial variability and uncertainty in behavior across the population. Despite the utility of the QMRA approach, few biological or social scientists are trained in this process or have sufficient statistical and quantitative skills to undertake such analyses. Similarly, few engineers possess the necessary skills in the social sciences to adequately address issues of human behavior that affect risks associated with exposure to pathogenic agents or responses to health risks. Therefore, we developed an intensive short course to enhance multidisciplinary cross training and graduate research through a combination of lectures and experiential learning opportunities – hands-on exercises and a group project. Through a comprehensive evaluation plan of the courses conducted in 2015 and 2016, we assessed the expanded ability of the course to improve outcomes for engineers in areas of the risk paradigm not traditionally emphasized in their graduate programs. Likewise, we tested the ability of the course to improve the quantitative and modeling skills in participants with backgrounds in social and behavioral sciences. The survey instruments were developed to evaluate both real and perceived knowledge of the participants. This talk focuses on our assessment of the extent to which perception was changed by learning. Participants completed identical pre- and post-workshop surveys containing five Perceptions scales (Perceptions of: QMRA-Related Ability, QMRA-Specific Ability, Knowledge – Hazard Identification, Knowledge – Dose Response and Exposure Assessment, Knowledge - Risk Management). This paper describes the structure of the course, content, pedagogy, and the lessons learned through the participant evaluation and perception of learning. Modifications to the course in response to participant comments were made between the 2015 and 2016 course and will be presented as well. Finally, this paper will serve as a model going forward for our subsequent short courses and may also be used as a model for cross disciplinary training of engineers within other domains that require social science integration.
AU - Jade Mitchell
AU - Mark H. Weir
AU - Julie Libarkin
AU - Joan B. Rose
CY - Columbus, Ohio
DA - 2017/06/24
PB - ASEE Conferences
TI - The Quantitative Microbial Risk Assessment Interdisciplinary Instructional Institute (QMRAIII) – A Platform for Cross Disciplinary Training of Engineers with Social and Biological Scientists to Address Public Health Issues
UR - https://peer.asee.org/28995
DO - 10.18260/1-2--28995
ER -