School of Scientific Computing & Informatics · Geoinformatics
Spatial Epidemiology & Health GIS
Where people live shapes their health. This course teaches the spatial methods used in public health to map disease, find clusters, measure access to care and relate health to the environment.
Course overview
Spatial Epidemiology & Health GIS starts with disease mapping done properly: rates, standardisation and smoothing for small areas, and the visual choices that can mislead.
You then detect clusters, model spatial relationships between health outcomes and risk factors, measure travel-time access to health facilities and link outcomes to environmental exposures from satellite data, with attention to privacy when mapping personal health data.
Learning outcomes
By the end of the course you will be able to:
- Compute and map standardised rates for small areas
- Smooth unstable rates with empirical Bayes and Bayesian models
- Detect spatial clusters and test their significance
- Fit spatial regression models and interpret them
- Measure access to health services and protect privacy in health maps
Skills you will practise
Eligibility and prerequisites
Who can apply
- Students and graduates in any science, engineering, pharmacy, medicine, agriculture, geography or computing programme (B.Sc., B.Tech., B.E., BCA, M.Sc., M.Tech., MCA, PhD)
- Researchers, faculty and working professionals in research, healthcare, biotech, pharma or IT who want to apply computing to science
- Final-year students may apply before their results are declared
Prerequisites
- Geoinformatics: GIS & Remote Sensing or equivalent
- Basic statistics
Best suited to
- Public-health and epidemiology students
- Health researchers and programme managers
- GIS professionals moving into health
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Counts, rates and standardisation
- Small-area problems
- Map design for health data
Topics
- Empirical Bayes
- BYM models
- Uncertainty maps
Topics
- Moran’s I and LISA
- Scan statistics
- Multiple testing
Topics
- Spatial lag and error models
- Geographically weighted regression
- Confounding
Topics
- Travel time to facilities
- Satellite-derived exposures
- Privacy and geomasking
Topics
- Question
- Analysis
- Report
Practical sessions and projects
Capstone project
A spatial health report
Map and model an open health dataset and present clear, privacy-respecting findings with their uncertainty.
Assessed on the correctness of the analysis, the quality of the code and the reasoning in the write-up. A pass is required for the certificate.
- Mapping health
Map district-level rates and see how standardisation changes the picture.
- Smoothing and Bayesian maps
Smooth unstable small-area rates and map their uncertainty.
- Clusters and autocorrelation
Detect clusters of a simulated disease and test whether they are real.
- Spatial regression
Model a health outcome against socioeconomic and environmental covariates.
- Access and exposure
Map travel time to the nearest facility and identify underserved areas.
- Project: a public-health spatial report
Analyse open health data spatially and present findings and limitations for decision-makers.
Software, tools and datasets
Software and tools
All software is free and open source or free for academic use. Recommended computer: 8 GB RAM, 30 GB free disk, Linux, macOS or Windows with WSL2.
Datasets
- Open health and census data: Rates and mapping.Public data portals
- OpenStreetMap facilities and roads: Accessibility analysis.OpenStreetMap (ODbL)
Core reading
- Waller LA, Gotway CA. Applied Spatial Statistics for Public Health Data. Wiley, 2004.
- Moraga P. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny. CRC Press, 2019.
Duration, format and fees
- Next cohort
- Dates are sent with your admission offer
- Timetable
- Three evening or weekend sessions a week (IST), plus a lab clinic; intensive and weekend-only schedules on request
- Payment
- Secure online payment link with your admission offer (UPI, cards, net banking). Instalments on request for fees above ₹15,000.
- Refunds
- See the refund and cancellation policy.
Instructor
The instructor for each cohort is named in your admission offer and on this page when the cohort is announced. Vedicgen instructors are selected for hands-on research or industry experience in the subject they teach, and every course is reviewed by a second subject expert.
Questions about who teaches a cohort? [email protected]
Certificate
Learners who complete the course and pass its capstone receive a Vedicgen certificate of completion for Spatial Epidemiology & Health GIS, issued by Vivofold, stating the guided hours and skills assessed. Each certificate has a unique ID and QR code that anyone can check.
Apply for Spatial Epidemiology & Health GIS
Apply
Send the form below. It takes about five minutes.
Review
An adviser confirms your fit and format within two working days.
Offer
You receive dates, timetable and a secure payment link.
Onboard
Set-up guide, pre-reading and joining links.
Frequently asked questions
In the live cohort, modules are taught in instructor-led sessions with a weekly lab clinic where you work on real public data with help at hand; every session is recorded. The self-paced format uses the same lessons, labs and datasets with mentor review of your capstone. Both formats end with an assessed project reviewed for the code and the science.
A laptop with at least 8 GB of RAM and about 30 GB of free disk space, running Linux, macOS, or Windows with WSL2. Installation instructions are sent before the first session, and lab clinics help with any set-up problems.
Yes. Learners who complete the course and pass its assessment receive a Vedicgen certificate of completion, issued by Vivofold. Every certificate carries a unique ID and a QR code that anyone, including an employer or admissions office, can check on the certificate verification page.
Apply with the form on this page. Live and in-person cohorts run through the year; the dates, timetable and joining details of the next cohort are sent with your admission offer and listed on this page once announced. Self-paced enrolment opens as soon as your application is accepted.
Yes. No course runs longer than four weeks, and the length is customisable: choose the standard schedule, an intensive one- to two-week schedule, weekends only, or a custom timetable. Pick your preference on the application form; colleges and teams can book their own dates.
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