Community-Based System Dynamics (CBSD) is a participatory method for engaging and working with communities and organizations to address complex issues. Developed from group model building and system dynamics, CBSD is now being used around the world, both in research and practice, to engage diverse communities and organizations. This 5-day course provides an introduction to CBSD, with opportunities for participants to receive feedback on preliminary designs for their own CBSD work. Participants will build capabilities relevant to CBSD, including qualitative causal mapping skills, exposure to system dynamics simulation models, skills on identifying issues appropriate for CBSD, assessing community readiness, convening a core modeling team, workshop design and facilitation.

Community-based participatory research (CBPR) is an orientation to research that begins with community research interests and seeks to use the knowledge gained to inform action for community health improvements and social change. Although this approach to research is widely adopted in urban health and generally familiar to both community-based organizations and researchers, many still struggle with the lack of knowledge or experience with applying practical CBPR approaches to a pressing community health issue or potential research partnership.

Improving the quality of data visualizations can help in communicating results more clearly and transparently to other scientists, stakeholders and the general public. This course will use a workshop format to help students build their own data visualization projects using R, with Urban Health examples. The five sessions will include:

Please note this course takes place over three days (Friday 1:30-5:00pm, Saturday and Sunday 9:00am-4:30pm). The goal of this course is to familiarize students with the applications of Geographic Information Systems (GIS) to assess or evaluate urban health challenges, and potential solutions, with a focus on the Philadelphia context. Students are expected to have some prior experience with GIS and be familiar with acquiring spatial data, data management, symbolizing features and making maps, and data coordinate and projection systems.