With roots in system dynamics and group model building, Community-Based System Dynamics (CBSD) is a participatory method for engaging and working with communities and organizations to address complex issues across a variety of contexts and cultures. CBSD is employed in research and practice settings globally to tackle “messy problems” by engaging community members. Over a 5-day period, this course introduces participants to CBSD, with emphasis on applications of CBSD to promote equity. The course provides participants with facilitation techniques for managing and engaging stakeholders; designing and structuring workshops; and opportunities to gain feedback on applying CBSD to a problem of interest or ongoing work. This course also develops skill sets for tools central to the use of system dynamics, such as qualitative causal mapping and creating a dynamic hypothesis.

This course is targeted towards researchers or practitioners in public health or related disciplines that address complex problems. A health disparities focus will also be present across examples in the course, so individuals interested in using these tools for disparities and equity issues are also encouraged. No previous experience or exposure to system dynamics is necessary for this course.

After completing this course, participants will be able to:

• Understand CBSD and its relationship to other methods of systems science, systems thinking, and system dynamics in particular.
• Identify and define problems most appropriate for CBSD.
• Utilize best practices to design a community-based participatory workshop.
• Identify facilitation strategies and scripts to enhance group-based participatory experiences.
• Understand how to use resources, such as Scriptapedia, in workshop design.
• Utilize qualitative causal loop diagrams as a tool to discuss and illustrate system behavior.

Prerequisite knowledge: No prerequisite knowledge or skills are required for this course.

Technical requirements: The free simulation software program Vensim may be used in this course.

Continuing Education Credits*: 1.5 CEU or 15 CPH

Community-based participatory research (CBPR) is an orientation to research that begins with community informational and 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. This course will review the history and principles of CBPR and introduce participants to practical approaches and tools for equitable and authentic community-researcher engagement in all phases of research: from the creation of research questions, to study design, data collection, data analysis, and dissemination. Participants will also learn strategies for participatory grant-writing, budgeting, and opportunities for workforce development and capacity building for community residents and leaders in research. This course is open to researchers and community-based organizations.

After completing this course, participants will be able to:

• Learn about the history and principles of CBPR, and what distinguishes it from community-placed research.
• Understand the importance of and practical approaches for community-researcher engagement in all phases of a research process.
• Apply CBPR principles to research partnership development and grant-seeking processes.

Prerequisite knowledge: No prerequisite knowledge or skills are required for this course.

Technical requirements: There is no required software for this course.

Continuing Education Credits*: 1.5 CEU or 15 CPH

Bayesian methods combine information from various sources and are increasingly used in biomedical and public health settings to accommodate complex data and produce readily interpretable output. This course will introduce students to Bayesian methods, emphasizing the basic methodological framework, real-world applications, and practical computing. Special consideration will be given to methods for spatial data analysis.

After completing this course, participants will be able to:

• Understand the fundamentals of Bayesian inference and the differences between Bayesian and frequentist (classical) methods.
• Formulate research questions and develop Bayesian approaches to address these questions.
• Become familiar with the available software for implementing Bayesian methods.
• Understand advanced Bayesian methods used in the scientific literature.

Prerequisite knowledge: Basic understanding of linear models (e.g., regression) and “generalized linear models” (e.g., logistic regression) is required. Basic familiarity with R programming language is recommended for this course.

Technical requirements: R and WinBUGS are required for the course. The free software is available for participants to install on their computers. A Windows computer is preferred for use of this software.

Continuing Education Credits*: 1.5 CEU or 15 CPH

The goal of this intermediate 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 using GIS. Through hands-on exercises based on local case studies, students will gain practice in assessing the relationship between aspects of our environments (e.g., housing, trees and parks, food/nutrition) and health in Philadelphia. Class sessions will consist of briefs lectures and extensive hands-on computer lab exercises that students can tailor based on geographic location or health outcome interests.

After completing this course, participants will be able to:

• Use GIS tools such as spatial overlays, interpolation and zonal statistics with both vector and raster data.
• Utilize GIS tools in combination with basic statistics and graphing to answer urban health research questions.

Prerequisite knowledge: Knowledge of basic concepts and techniques of GIS and some basic knowledge of ESRI's ArcGIS Pro software is required for this course.

Technical requirements: A temporary license for Esri's ArcGIS Pro will be provided for participants to install on their computers.

Continuing Education Credits*: 1.5 CEU or 15 CPH

The course is an introduction to the basic concepts and techniques of Geographic Information Systems (GIS). This course contains lectures and exercises in ArcGIS. The lectures introduce the basic concepts of GIS, data models, coordinate system and map projections, data management and processing, spatial analysis, spatial estimation, and GIS data visualization. Students will also learn how to use the fundamental knowledge and techniques of GIS to solve real-world problems. Through the exercises, students will get familiar with the interfaces and analysis tools in the Esri software package ArcGIS. Students will also practice applying GIS as a tool and a methodological approach to spatially analyze environment and public health data. This course is targeted towards anyone interested in gaining working knowledge of ArcGIS and GIS.

After completing this course, participants will be able to:

• Understand basic concepts and terms of GIS and know how to spatially analyze data using ArcGIS.
• Acquire spatial data that is relevant to urban health, e.g., census data, land use data, greenspace, road networks, satellite images, etc.
• Build knowledge of data structure, data management, and coordination and projection systems.
• Practice featuring symbols and making elegant maps in ArcGIS.
• Apply the knowledge of GIS to solve research questions in urban health research.

Prerequisite knowledge: No prerequisite knowledge or skills are required for this course.

Technical requirements: A temporary license for Esri's ArcGIS Pro will be provided for participants to install on their computers. Students planning on using a Mac computer with Intel processors will need Boot Camp with Microsoft Windows installed in the partition or a virtual environment (e.g., VMWare or Parallels 15 or greater). Students with a MacBook with the new Apple Silicon (i.e., M1 processors), can complete the course assignments with an alternative software to ArcGIS, such as QGIS.

Continuing Education Credits*: 1.5 CEU or 15 CPH

Multilevel studies and multilevel analysis have been increasingly used in the public health field. This course will discuss the rationale for multilevel studies and multilevel analysis in public health as well as differences with other study designs and other analytical approaches. Although the course will not be heavily mathematical, the basics of fitting multilevel models for different types of outcomes as well as the interpretation of estimates obtained from multilevel models will be reviewed and practiced. Emphasis will be on conceptual understanding, application, and interpretation of multilevel analysis in the context of urban health research. The course will also review and critique empirical applications in urban health research and discuss conceptual and methodological challenges in using multilevel analysis.

After completing this course, participants will be able to:

• Understand the fundamentals of multilevel studies and multilevel analysis and their differences with other study designs and analytical approaches.
• Fit multilevel models and interpret estimates derived from them.
• Be familiar with applications of multilevel analysis in urban health research.
• Understand the strengths and limitations of multilevel analysis for urban health research.

Prerequisite knowledge: Knowledge of regression analysis (linear, logistic, Poisson) is required. Familiarity conducting regression analysis in SAS, Stata, or R software is recommended for this course.

Technical requirements: Participants will need access to SAS, Stata, or R software for the course. R free software is available for participants to install on their computers.

Continuing Education Credits*: 1.5 CEU or 15 CPH