GIS: Visualizing and Analyzing Health Data
Explore fundamental concepts and hands-on techniques for health data visualization and analysis using open-source GIS programs in this two-day intensive workshop designed for beginners.
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Course Description
Gain practical skills in geospatial data visualization and spatial analysis using open-source tools through this intensive two-day workshop, featuring expert-led lectures and hands-on applications.
- Apply geospatial data visualization and spatial analysis techniques using open-source software, including QGIS or R/RStudio, tailored to your preferred learning track.
- Utilize environmental and demographic data to perform geo-processing, cluster analysis, and identify spatial relationships through hands-on exercises and real-world datasets.
- Master data acquisition, management, and mapping methods using tools like GeoDa, GWR4, ggplot2, and sf for creating advanced spatial visualizations and conducting in-depth analyses.
- Identify statistical hotspots and integrate spatial data into traditional regression models, enhancing your ability to explore patterns and associations in public health research.
To contact support for this course, please email [email protected].
Course Prerequisites
This workshop welcomes investigators at all career stages, with a focus on trainees, students, and early-stage researchers. Participants should have an introductory background in statistics, basic knowledge of R, and a laptop with QGIS, saTScan, GeoDa, R, and RStudio installed prior to the workshop. All software is free and compatible with Mac, PC, and Linux, and personal laptops will be used during multiple sessions.
What You Will Learn
By the end of this workshop, participants will be familiar with:
- Principles of data visualization and analysis
- Sources and techniques for the acquiring and managing spatial data
- Methods for geospatial visualization and analysis
- Techniques for the identifying statistical hotspots and clusters
- Incorporating spatial data into traditional regression methods of association studies
Instructors
Jeremy Porter, PhD, Mailman School of Public Health, Columbia University. Dr. Porter is a Lecturer in the Environmental Health Sciences Department with his primary duties being associated with teaching and advising in the area of Public Health GIS and Spatial Statistics. Additionally, he is a Professor at the City University of New York and holds appointments in multiple departments and institutes throughout the university, where he is currently the Chair and Director of the Quantitative Methods in the Social Sciences Department at the CUNY-Graduate Center. He regularly serves in consulting capacities with a number of government, non-profit, and for-profit entities on research exclusively focused on the development and implementation of spatial methods.
Joel Capellan, PhD, Mailman School of Public Health, Columbia University, serves as an Adjunct Professor in the Environmental Health Sciences Department and as an Associate Professor of Criminal Justice at John Jay College. He specializes in gun violence, spatial analysis, and policy evaluation. He has published extensively and trained public safety professionals in Central America on USAID-funded projects. Currently, he serves as the Director of the Center for Enhancing the Research Capacity of Minority Serving Institutions at John Jay College. His work has been featured in The Guardian, NPR, and ABC News.