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Spatial Analysis for Public Health Researchers (Leeds)

This one-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 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.

2024/25 Course date TBC

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).

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.

Course Tutor

Michelle Morris is Associate Professor and 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. 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.

“The course exceeded my expectations. I have previously attended similar courses (Basic ArcGIS mapping; Small area estimation) and I did wonder whether this particular course might be surplus to my requirements having already attended two others. However, the R content alone was worth the trip from the south coast!

I will probably (when I have time) collaborate with colleagues on a paper using GIS maps. Also, this course will definitely help when I consult with researchers who are seeking my advice on data, statistical analysis and the presentation of results. Just to say well done to the tutors for an excellent course, very well delivered.”

“I liked the explanation of the data sources and geographies as this gave me more context to work from in the practical sessions”