MACEPA Data Fellowship Retreat 2025
All data, figures, and analyses are intended for educational purposes only and should not be used for decision-making, and have been adjusted or simulated to protect sensitive information. Do not use outputs from this project outside of the educational context!
The 2025 MACEPA Data Fellowship was an in-person workshop series conducted for the first two cohorts of MACEPA Data Fellows (2024 and 2025 classes) held in Abuja, Nigeria from November 3rd to 7th, 2025. Over an immersive five days, fellows and their mentors engaged in intensive training, hackathon sessions, and personalized mentorship meetings. The workshop strengthened the fellows’ technical expertise and reinforced their role to support their countries’ National Malaria Programs in driving data-informed decision-making for the control and elimination of malaria. Fellows from the Central African Republic, the Democratic Republic of Congo, the Gambia, Ethiopia, Nigeria, and Zambia attended the retreat.
This site gathers all retreat materials in one place: technical training guides (GitHub/R/Quarto, data cleaning, visualization, Shiny), downloadable code and examples, and links to the presentation slide decks. The purpose of sharing these materials publicly is to extend the reach of the training beyond the in-person event and provide a resource for other malaria data analysts looking to build their skills. Additional resources can be found on the MACEPA Technical Training Materials site.
| Page | Contents |
|---|---|
| GitHub, R, and Quarto | Slides and walkthrough for version control basics and publishing with Quarto. |
| Data Cleaning in R | Step-by-step guidance and examples for cleaning DHIS2 data. |
| Data Visualization | Techniques and code for charting and presenting DHIS2 outputs. |
| Shiny Apps | Intro to building and sharing interactive Shiny content. |
| Presentation Slide Decks | Embedded PowerPoint decks for all training sessions. |
Presentation slide decks:
- Preparing DHIS2 data for analysis by Hannah Slater & Amir Siraj
- Pulling Data from DHIS2 Using the API in R by Sarja Jarjusey
- Systematic Cleaning of DHIS2 Malaria Data in R by Enku Demssie
- Preparing Intervention and Accessory Data by Hayley Thompson & Justin Millar
- Visualizing Data from DHIS2 by Serge Zola
- Analyses to Support NMP Decision-Making by Amir Siraj & William Sheehan
- Application of MagicGlasses2.0 to complement data triangulation in The Gambia by Sarja Jarjusey
