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

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 course conducted in 2015, 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 paper focuses on our assessment of the extent to which perception was changed by learning. Participants completed identical preand postworkshop 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. Introduction and Background Quantitative microbial risk assessment (QMRA) is globally accepted for addressing probabilities of disease using mathematical approaches and integrated data sets for human health threats associated with exposure to etiological agents in a diverse set of indoor and outdoor environments. QMRA is inherently interdisciplinary and requires some understanding of biological processes and methodology that focuses on dynamic and complex systems. Because few specialists in QMRA exist, risk assessments are generally conducted by scientists from multiple research disciplines as new needs arise. Most often QMRA is 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. Risk assessment provides a science based interface to policy and requires that the science is adequately communicated to diverse stakeholders. 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. Quantitative information is particularly challenging to communicate, but can greatly improve decision and policy making. QMRA methods have particular importance for mitigating risks from emerging or reemerging pathogens. It appears that emerging pathogen events are increasing, and that this trend cannot be fully explained by increases in surveillance or research (Jones et al., 2008). Additionally, climate change, land use change, and transportation networks have altered or expanded the ranges of many important arthropod vectors, along with their associated pathogens (e.g., dengue virus, West Nile virus, Trypanosoma cruzi [Chagas disease], Plasmodium sp.[malaria], etc.) (Kilpatrick & Randolph, 2012). Many bacterial diseases that have been well-controlled in developing countries by antimicrobial drugs are reemerging as resistance evolves simultaneously with more people using antimicrobials (Jones et al., 2008), such as drug-resistant staphylococcal or tuberculosis infections. Because of these pressing issues, it is keenly important for engineers and biological scientists to understand risk sciences to improve the design and selection of engineering controls and other mitigation strategies. A ten-day long, yearly short course was developed to train engineers, biological and social scientists in QMRA approaches the Quantitative Microbial Risk Assessment Interdisciplinary Instructional Institute (QMRAIII). Participants of QMRA III (1) attend lectures from the top scientists in the QMRA field; (2) engage in specific hands-on exercises; (3) under the mentorship of a program faculty member and teaching assistant, conduct a QMRA as a research case study within a multidisciplinary team; and (4) use and contribute to the QMRAwiki – an interactive,