PARV4 Prevalence treemap

Dr. Johannnes Abeler and his colleagues sought to perform a meta-analysis of a preference for truth telling experiment designed by Fischbacher and Föllmi-Heusi in 2013. Their analysis combined data from over 420 experiments across 40 different countries and they sought to make this data as easy to digest as possible through interactive visualisation in the website.

This characterisation of PARV4 infection provides enhanced insights into the epidemiology of infection and co-infection in African cohorts, and provides the foundations for planning further focused studies to elucidate transmission pathways, immune responses, and the clinical significance of this organism

These visualisations were built using R and Shiny, here's a basic overview of what Shiny is.

This project was started when Dr. Philippa Matthews approached University of Oxford's IT Research Support Team and requested support in creating an interactive visualisation to accompany a specific publication on blood-born virus coinfection data. A combination of R, htmlwidgets and Shiny was recommended to provide the requested interactivity.

The visualisation makes use of the following charts:

  • Treemaps - useful for comparing hierarchical group sizes

To replicate this interactive visualisation for yourself, refer to the IDN Shiny app template or else fork the actual code for the shiny app here. You an also contact the IDN on

Case Study Details

Academic Dr. Philippa Matthews (

Nuffield Department of Medicine

Divison Medical Sciences
Where is visualisation used?
Data Source
Link(s) to code
Developer Martin Hadley (