Introduction to Spatial Analysis in R

Overview - spatial analysis in R short course

Spatial analysis is becoming an increasingly useful tool throughout public health research with increasing amounts of spatial health data generated each year. Whether you’re a humanitarian aid worker looking to add map making to your growing rapid analysis skillset or an early stage PhD student who wants to learn the fundamentals before progressing to geostatistics, this short course will be well suited to your needs.

Our hands on, practical approach to teaching, with real-life examples, means you can progress from no previous experience with R to applying R to your own work with confidence. We also place a strong emphasis on enabling students to continue their learning independently allowing your skillset to continue growing beyond the end of the course.

Day 1:

  • Introduction to the R computer programme, vocabulary and format of different datatypes
  • Using the “dplyr” and “ggplot2” packages to create numerical and visual summaries of structured data sets

Day 2:

  • Introduction to reading and visualising spatial data including interactive maps using “mapview”, “tmap”, and “sf” packages.
  • Demonstration of basic and some advanced spatial manipulations such as buffering, spatial joins, and distance calculations and interactive visualisation of spatial data

Day 3:

  • Revision of Generalised Linear Models and their extension as Generalised Linear Mixed Models and Generalised Additive Models
  • Discrete space spatial models with Markov random field smoothers

Day 4:

  • Continuous space spatial models with Gaussian process based smoothers
  • Reproducible reporting with R Markdown

Who is this course for?

Practicing public health professionals and health researchers interested in adding expertise in spatial data analysis to their existing skillsets. Operational researchers and in particular those working in humanitarian crises / emergency deployments are particularly encouraged.

Teaching methods

The course is taught as a series of hands-on computer practicals using public health relevant examples from humanitarian crises. Background theory is presented by a lead tutor then students work independently or in small teams to solve a series of exercises with help available from in classroom teaching assistants. No prior experience with R is necessary for the course, but some basic knowledge and interest in epidemiological data analysis is highly desirable.

How to apply
How to apply - spatial analysis short course

Applying for this course


Please also read LSHTM's Admissions policies prior to submitting your application.


The student is responsible for obtaining any visa or other permissions to attend the course, and is encouraged to start the application process as early as possible as obtaining a visa for the UK can sometimes take a long time. The Short Courses team, in the Registry, can provide supporting documentation if requested.

Accommodation and meals

A list of hotels and other accommodation located in the vicinity of the School can be supplied on request to the Registry. Lunch can be purchased from the School's Refectory in the Keppel Street building or the cafe on the Tavistock Place building. Evening meals are not catered for at the School, but there is a large choice of restaurants, cafes and shops nearby.

The London School of Hygiene & Tropical Medicine is committed to improving global health through its programme of short and full-time postgraduate study.

Please note:

  • If you have been offered a place on the course you will not be able to register without bringing formal ID (Passport / UK photo driving license) and without having obtained the correct visa.
  • It is essential that you read the current visa requirements for short course students.
  • Although this short course has run successfully in all the four years it has been offered, the School may cancel courses two weeks before the first day of the course if numbers prove insufficient.  In those circumstances, course fees will be refunded.
  • The School cannot accept responsibility for accommodation, travel and other losses incurred as a result of the course being cancelled.