GIS & Spatial Data Science for Public Health

Background

Public-health practitioners increasingly need to work with geographic data, yet most have limited exposure to spatial methods. This flagship recurring workshop series introduces GIS and spatial data science to public-health professionals, researchers, and students, using open-source tools and reproducible workflows. No prior GIS experience is assumed.

Approach

Delivered as a hands-on Quarto-based course built entirely in R, the curriculum moves from foundational concepts of spatial data science to applied analysis. Core tools taught include sf and terra for spatial data handling, tmap and leaflet for static and interactive mapping, and spdep for spatial statistics. Sessions cover spatial joins, choropleth mapping, and hotspot/cluster analysis, interleaved with guided exercises and worked public-health datasets.

What we found

Participant learning outcomes include the ability to:

• Read, manage, and transform vector and raster spatial data in R.
• Produce publication-quality static and interactive maps (choropleths, point maps).
• Perform spatial joins and integrate attribute data with geographies.
• Run hotspot and cluster analyses to detect spatial patterns in health data.
• Build reproducible, Quarto-based spatial analysis workflows.

Outputs & impact

The series has produced a full Quarto course website, slide decks, session notebooks, prerequisite guides, and reusable exercise datasets. It has been delivered at: (a) Summer School 2024 — “Open Stack: Geospatial Models for Public Health”, GISE Hub, IIT Bombay, 25–31 July 2024 (Arun’s sessions on Days 3–4, 27–28 July 2024); and (b) SANGAM 03 — GISE Hub, IIT-Bombay & MUHS, Nashik, 22 August 2025. Materials are maintained as a reusable, openly shareable curriculum.