# Malaria Data Dashboard for Niger
## Overview
This repository contains a **Shiny application** built in R to analyze and visualize malaria data in Niger from 2019 to 2024. The application provides interactive dashboards, maps, forecasting, anomaly detection, and AI-powered recommendations to support public health decision-making. It leverages data from the Niger Ministry of Health's MDO reports and integrates geographic data for regional visualizations.
Key features include:
- **Interactive Visualizations**: Time-series plots, static and interactive maps, and bar charts to explore malaria metrics (e.g., Confirmed Cases, Attack Rate, Fatality Rate).
- **Data Explorer**: An interactive table for detailed data exploration with filtering and sorting capabilities.
- **Forecasting**: Predicts malaria trends up to 12 weeks using the Prophet library.
- **Outbreak Alerts**: Detects anomalies in malaria metrics using the anomalize package.
- **AI-Powered Recommendations**: Identifies high-risk regions based on Attack Rate, Positive Rate, Fatality Rate, and recent case trends, with actionable intervention suggestions.
- **Natural Language Queries**: Allows users to ask questions about the data via an xAI API (requires an API key).
- **Data Export**: Download filtered data in CSV or Excel formats.
## 📸 Dashboard Preview
*Note: This is a placeholder image. To include your own screenshot, follow the instructions below:*
- **Take a Screenshot**: Run the app (`app.R`), navigate to the desired tab (e.g., Overview or District Details), and capture a screenshot.
- **Upload the Image**: Save the screenshot (e.g., as `screenshots/dashboard.png`) and upload it to a `screenshots` folder in your repository:
```bash
mkdir screenshots
git add screenshots/dashboard.png
git commit -m "Add dashboard screenshot"
git push origin main
```
- **Update the Link**: Replace the placeholder URL above with:
```markdown
```
This will display your custom image, showcasing the dashboard’s interfac …