GIS for Epidemiology

Background

Epidemiological data are inherently spatial, yet spatial analysis remains underused in routine practice and training. This workshop equips epidemiologists and public-health researchers with practical spatial methods to map, explore, and analyse disease data, building on classic examples such as the John Snow cholera investigation and modern outbreak datasets.

Approach

The course is delivered as a Quarto website with structured sessions in R. It covers foundational concepts of spatial data science, spatial data handling with sf, visualisation of disease data, and exploratory spatial analysis. Applied sessions introduce spatial autocorrelation and cluster detection, supported by case studies, hands-on exercises, and prerequisite installation guides.

What we found

Participant learning outcomes include the ability to:

• Handle and transform epidemiological spatial data in R.
• Map disease distributions and rates effectively.
• Test for spatial autocorrelation and interpret the results.
• Detect disease clusters and high-risk areas.
• Apply spatial reasoning to outbreak investigation.

Outputs & impact

The series produced a complete Quarto course website, session notebooks, case studies, exercises, and a managed renv environment for reproducibility. It was delivered as Day 2 of the “Geospatial Technology for Public Health Policy” workshop (GISE Hub, IIT Bombay), hosted at the Central University of Gujarat (CUG), Gandhinagar, on 27–29 May 2024, with Arun’s session on 28 May 2024. Facilitators were Dr. Biju Soman (SCTIMST) and Dr. Arun Mitra (AIIMS Bibinagar). Materials are reusable across future epidemiology training events.