Monitoring & Segmentation of Tuberculosis Cases

Academic ProjectCompleted

An interactive data visualization project built with R, R Shiny, and ggplot2 for creating dynamic, explorable visualizations.

January 5, 2026 1 min read

RR ShinyData Visualizationggplot2

Interactive Shiny dashboard for WHO tuberculosis data analysis and clustering.

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

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)

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

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

Requirements

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

Installation

Clone this repository
Open R/RStudio in the project directory
Restore packages with renv::restore()
Run the application:
```
shiny::runApp("app.R")
```

Detailed Report