This second EDI session will build on the first, delivered by Dr. Sharmistha Mishra. Dr. Mishra’s address demonstrated the risks accompanying dynamic modelling without applying an equity lens, including the risk of a widening of health disparities. This talk will employ brief vignettes from community- and patient-engaged projects undertaken by the speaker in both academic and in the health system to highlight some of the textured equity issues that arise in the context of modelling with vulnerable populations. Building on discussion following Dr. Mishra’s presentation, the talk will continue on to discuss ways in which model architecture & design impact the capacity to effectively apply an equity lens, including benefits and risks that can come with model representation of particular dimensions of heterogeneity. In reflection of the fact that both equity-conscious modelling projects themselves and the societal gains they confer benefit by involving affected populations, the talk will proceed on to discuss participatory modelling traditions and supportive processes from community-based participatory research and patient-oriented research. While such processes involve commitments of time and to relationship-building, the talk notes that such commitments are rewarded by enhanced pathways to modelling project and societal impact. Participatory modelling projects differ in the degree, type, and timing of public involvement and can confer benefits to dynamic modelling projects conducted both in academia and in the health system. We further discuss some of the methodological priorities and model desiderata that emerge when employing participatory processes. As time allows, the talk will note some principles and suggestions for undertaking dynamic modelling work drawing on participatory processes and guidance from those with lived experience. The presentation concludes with a summary of and a set of resources involving work with communities and those with lived experience.

Nathaniel Osgood serves as Professor in the Department of Computer Science at the University of Saskatchewan, and Director of the Computational Epidemiology and Public Health Informatics Laboratory. His research focuses on combining tools from Systems Science, Data Science, Computational Science, and Mathematics to inform decision-making in health & health care. Dr. Osgood serves as Chief Research Advisor for the Saskatchewan Centre for Patient Oriented Research and has contributed to or co-led over a dozen initiatives involving people with lived experience with dynamic modelling, machine learning and/or big data collection efforts. Dr. Osgood served as the technical director of COVID-19 modelling for the Province of Saskatchewan from March 2020-April 2021. Through cross-leveraging combinations of dynamic modelling, Artificial Intelligence/Machine Learning, and diverse data sources, CEPHIL delivers COVID-19 situational analyses and short-term forecasts daily for Saskatchewan, multiple times a week for all provinces across Canada for PHAC and once a week to First Nations Reserves across Canada via FNIHB. In addition to dozens of published applications of agent-based, compartmental modelling and in diverse health & health care areas and guiding analytics that have shaped important policy and investment decisions at the Saskatchewan at the Ministry of Health, Dr. Osgood has contributed techniques hybridizing multiple simulation approaches with machine learning tools and which leverage such hybrid models with data from multiple high-velocity data sources, innovations to improve dynamic modelling quality and efficiency, introduced novel modelling languages, and worked enhance dynamic modelling formulation using approaches from category theory. Among his many data science contributions, Dr. Osgood is the co-creator of diverse epidemiological surveillance and data collection systems, most prominently the Google Android-, iPhone- and web-based Ethica Data platform applied in hundreds of health studies around the world, including for multiple COVID-19 related studies. Prior to joining the U of S faculty, he graduated from MIT with a PhD in Computer Science, served as a Senior Lecturer and Research Associate at MIT and served in a variety of academic, consulting & industry positions.