The chapter hosts an annual workshop and quarterly tutorials where LMIC students and members of partnership organisations are encouraged to present and learn a wide range of R related public health analyses.
Introduction to R-HTA Modelling - 25 September 2023
This half-day interactive tutorial was held on Monday, 25 September 2023. Health analysts from low/middle income countries were trained on how to use R language when building HTA models. No prior experience using R programming was required for this tutorial as participants were taught the basics, but undertanding of health econmic concepts was an essential prerequisite.
Advanced R-HTA Modelling Tutorial - 20 January 2023
This half-day interactive tutorial was held on Tuesday, 20 January 2023 and participants gained practical skills on how to convert a model built in Excel to R. The tutorial also showed participants how to build an interactive model using Shiny.
Intermediary R-HTA Modelling Tutorial - 20 September 2022
This half-day interactive tutorial was held on Tuesday, 20 September 2022 and participants gained practical skills in R for HTA modelling. The tutorial, built on the skills taught in the introductory Q2 Tutorial and gave hands-on experience in building a basic sick-sicker decision analytical model for Health Technology Assessment.
Introductory R-HTA Modelling Tutorial - 21 June 2022
The half-day interactive tutorial was held on Tuesday, 21 June 2022 where particapnts gained practical skills in R for HTA modelling.The tutorial equipped partcipants with hands-on experience in building a simple sick-sicker decision analytical model for Health Technology Assessment, using the DARTH package.
Inaugural presentation-based workshop - 23 February 2022
If you missed our inaugural workshop, view the presentations by clicking below!
R in LMICs: what's the potential?
Our panel discussion on the 23rd February 2022 provided participants with valuable insights from our HTA experts, Prof Gianluca Baio, Dr Howard Thom, Dr Fernando Escudero, and Dr Lucy Cunamma, who debated on the potential advantages and pitfalls of R within the LMIC contexts.