The factors responsive to the urgent need to build dynamic models informed by diverse viewpoints and which help reduce health inequities, this module characterises the art and science of dynamic modelling in health that draws on participatory processes, including projects conducted within and in partnership with organisations and health systems, and/or with communities and people with lived experience (PWLE). This module is available to all, but particularly aims to serve those involved in dynamic modelling projects regardless of career stage or whether they are part of the core technical modelling team, or serve in a supportive capacity. The materials seek to help assist module participants in getting started in, avoid pitfalls regarding, and maximize effectiveness of modelling that engages with, taps insights from, and secures buy-in or a sense of ownership from system stakeholders and/or PWLE. To do so, it draws on progress across three decades of literature on and practical experience regarding group model building, participatory engagement and community-based modelling, as well as supporting social science.

Learning Objectives

This module will provide the ability to:

• Recognise at least 5 benefits of participatory engagement with communities and organisations
• Identify at least 3 of 5 levels ways in which participatory engagement can inform modelling research, and at least 2 levels of engagement for each
• Identify at least 4 points in the evolution of a quantitative modelling project at which participatory engagement sessions can be deployed, and activities associated with the engagement sessions for each
• To identify 6 common barriers to participatory engagement
• List 5 strategies for reducing such barriers in participatory modelling
• To identify 5 common barriers to participatory engagement
• Distinguish participatory system mapping from participatory modelling
• Characterise the meaning of a boundary object, and describe how a diagram can function as one
• Describe in detail at least one widespread technique for system mapping
• Describe 5 different roles taken on by core modelling team members within a model mapping session

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Bio: Dr. Nathaniel Osgood is a Professor in the Department of Computer Science, Director of the Computational Epidemiology and Public Health Informatics Laboratory, and Associate Faculty in the Department of Community Health & Epidemiology at the University of Saskatchewan. His research is focused on providing cross-linked simulation, data science, categorical computing, topology data analysis, and machine learning tools to inform understanding of population health trends and health policy trade-offs. Dr. Osgood served for 8 years as Chief Research Advisor and Lead Methodologist for the Saskatchewan Centre for Patient-Oriented Research and has contributed to over a dozen initiatives involving people with lived experience and the health system with dynamic modeling, machine learning and big data collection efforts, and contributes category-theory based innovation to support such efforts. Among his many data science contributions, Dr. Osgood is the co-creator of two novel mobile sensor-based epidemiological monitoring systems, most recently the Google Android- and iPhone-based Ethica Health (now Avicenna) platform applied in hundreds of health studies around the world, and has overseen extensive analysis work in studies conducted with these platforms using broad combinations of statistical, machine learning, topological data analysis and visualization methods. Prior to joining the University of Saskatchewan, 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 and industry positions.