artsite/content/projects/dataviz-tuberculose.md

slug, title, type, description, shortDescription, publishedAt, readingTime, status, tags, icon

slug	title	type	description	shortDescription	publishedAt	readingTime	status	tags	icon
dataviz-tuberculose	Monitoring & Segmentation of Tuberculosis Cases	Academic Project	An interactive data visualization project built with R, R Shiny, and ggplot2 for creating dynamic, explorable visualizations.	An interactive data visualization project using R and R Shiny.	2026-01-05	1	Completed	R R Shiny Data Visualization ggplot2	i-ph-chart-bar-duotone

Interactive Shiny dashboard for WHO tuberculosis data analysis and clustering.

• GitHub Repository: Tuberculose-Visualisation
• Live Application: Tuberculose Data Visualization

::BackgroundTitle{title="Overview"} ::

This project provides an interactive visualization tool for monitoring and segmenting global tuberculosis data from the World Health Organization (WHO). It applies multivariate analysis to reveal operational typologies of global health risks.

Author: Arthur Danjou
Program: M2 ISF - Dauphine PSL
Course: Data Visualisation (2025-2026)

::BackgroundTitle{title="Features"} ::

• Interactive world map with cluster visualization
• K-means clustering for country segmentation (Low/Moderate/Critical Impact)
• Time series analysis with year selector (animated)
• Region filtering by WHO regions
• Key Performance Indicators (KPIs) dashboard
• Raw data exploration with data tables

::BackgroundTitle{title="Project Structure"} ::

├── app.R                    # Shiny application
├── NoticeTechnique.Rmd      # Technical report (R Markdown)
├── NoticeTechnique.pdf      # Compiled technical report
├── data/
│   ├── TB_analysis_ready.RData          # Processed data with clusters
│   └── TB_burden_countries_2025-12-09.csv # Raw WHO data
└── renv/                    # R package management

::BackgroundTitle{title="Requirements"} ::

• R (>= 4.0.0)
• R packages (see renv.lock):
  • shiny
  • shinydashboard
  • leaflet
  • plotly
  • dplyr
  • sf
  • RColorBrewer
  • DT
  • rnaturalearth

::BackgroundTitle{title="Installation"} ::

1. Clone this repository
2. Open R/RStudio in the project directory
3. Restore packages with renv::restore()
4. Run the application:

   shiny::runApp("app.R")
   

::BackgroundTitle{title="Detailed Report"} ::

::BackgroundTitle{title="License"} ::

© 2026 Arthur Danjou. All rights reserved.

::BackgroundTitle{title="Resources"} ::

You can find the code here: Data Visualisation Code

And the online application here: Data Visualisation App