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Course Description

This special topics course explores selected themes, topics, and/or applied practices that are not covered by existing courses and do not have a natural disciplinary home. Any unit may request an offering through the Office of Graduate and Postdoctoral Studies.

This course exposes students to novel research from various fields —from computer science to health and nutrition, sociology, marketing, and ecology— to explore complex challenges that urban environments face with regards to food access, mobility, and overall population health. Drawing from Canadian (including First Nations) and global contexts, students will engage in implementation science; this is, they will learn how to move knowledge into action from early stages of conception to execution, testing, scale up, and evaluation. Students will dive into state-of-the-art implementation science methods that range from effective community engagement to computational science. Overall, the course will encourage students to think critically and integrate knowledge and practice to solve complex societal problems and find ways to make cities healthier, more livable, and more resilient.

Learning Outcomes

By the end of the course, the learner should be able to:

  • Describe and integrate concepts and perspectives from diverse disciplines that are key to the study of healthy cities and implementation science.
  • Discuss and reflect on the applicability of various implementation science methods to solving challenges in urban environments.
  • Propose solutions to a specific healthy cities problem of their choice, justifying the selection of methods and predicting potential outcomes.
  • Showcase leadership and networking skills with peers and instructors.
  • Demonstrate aptitude for interdisciplinary collaboration and co-learning.


Course Topics

  • What is ‘Implementation Science’?
  • Systems Thinking
  • Cities and Smart Cities
  • Convergence by Design
  • Sex and Gender Based Analysis (SGBA+)
  • Digital Health and Patient Centred Outcomes
  • Socio-Spatial Epidemiology
  • Introduction to Modelling
  • Community-Based Participatory Research Healthy
  • Introduction to Data Science, AI, Natural Language Processing, Text Processing and Data Availability
  • Introduction to Health Economics
  • Design Methods


Assessment Item Weight Learning Outcomes
Weekly Reflections (9) 45% (5% each) 1, 2 and 4
Group Facilitation 15% 1, 2, 4 and 5
Final Methods Paper - Outline 15% 1, 2 and 3
Final Methods Paper - Final Draft 25% 1, 2, 3 and 5
Total 100%  


Technical Requirements

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*Course details are subject to change.


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