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Spatial Analytics for Public Health Researchers

Date(s) - 21/10/2019
9:30 am - 4:30 pm

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This course is now fully booked. Please contact Kylie Norman if you would like to be added to the mailing list for the next course.

This 1 day course offers an introduction to spatial analytics in a public health context. As spatial data sets get larger, more sophisticated software needs to be harnessed for their analysis. R is now a widely used open source software platform for statistical analysis and is increasingly popular for those working with spatial data thanks to its powerful analysis and visualisation packages. This course introduces the basics of how R can be used for spatial data. The course will begin with an overview of different spatial units and how they fit together. Public health examples will be used to illustrate the relevance of using each of these units. You will work through examples of how spatial units can be added into existing data sets. In the afternoon you will generate your first map using public health data.

Programme Objectives

  • To understand common spatial units in the UK
  • To use open resources to match data at different spatial scales
  • To generate a map of public health data (in a licenced and open source software).

Course Tutor

Michelle Morris is an Academic Fellow of the University of Leeds and Wellcome Trust ISSF Fellow, based in the Leeds Institute for Data Analytics. Her primary research interests are spatial and social variations in diet, lifestyle and health and how new and emerging data sources in these areas can best be utilised to benefit patient health outcomes. Last year she presented at the LIDA seminar, Big Data in Public Health – future horizons, applications and ethical issues, on the case for using Big Data to fill in the gaps in the narrative for public health research. Her unique career history (a degree in Neuroscience, working in industry in Health Informatics, and then gaining an MSc and then her PhD investigating, “Spatial analysis of dietary cost patterns and implications for health”) has perfectly fitted Michelle to embark on her University Academic Fellow vision of crossing discipline boundaries, bringing together people, data and methods to improve health through informatics – specifically combining consumer analytics with health informatics and using ‘big data’ to benefit patient outcomes.


Is this course for me?

This course is for researchers who want to start looking at spatial or social variations in their data and generating maps to present results. The course will assume that your knowledge of spatial scales and generation of maps is zero. Examples will all be from a public health context.



£70 – Students
£120 – Academic, public and charitable sector
£300 – Other


Further Information 

Lunch and refreshments will be provided. For further information about this course please contact Kylie Norman.