An end-to-end machine learning and Streamlit application for predicting malaria, cholera, and typhoid outbreaks in Nigeria using environmental and public health data.
# 🇳🇬 Nigeria Public Health AI Surveillance System
> An end-to-end Machine Learning and Data Analytics platform for predicting **Malaria**, **Cholera**, and **Typhoid** outbreaks across Nigeria using environmental and public health indicators.
🌐 **Live Demo:**
nigeria-public-health-ai-su…
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## 📖 Project Overview
The **Nigeria Public Health AI Surveillance System** is an interactive Machine Learning application designed to support public health decision-making by predicting disease outbreaks using environmental and demographic data.
The application analyses historical public health information alongside environmental conditions such as rainfall, temperature, humidity, season, settlement type, water source, sanitation level, and population density to estimate the likelihood of disease outbreaks.
The system predicts:
- 🦟 Malaria
- 💧 Cholera
- 🤒 Typhoid
using trained Machine Learning models and presents the results through an interactive dashboard with automated reporting.
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## 🎯 Project Objectives
- Predict disease outbreaks using Machine Learning.
- Support early public health intervention.
- Visualize outbreak risk across Nigeria.
- Provide AI-assisted decision support.
- Generate downloadable professional reports.
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## ✨ Key Features
- ✅ Interactive Streamlit dashboard
- ✅ Machine Learning prediction models
- ✅ Automatic best-model selection
- ✅ Disease comparison charts
- ✅ Nigeria outbreak map
- ✅ Risk assessment dashboard
- ✅ AI Decision Support Summary
- ✅ Automated PDF report generation
- ✅ Downloadable prediction reports
- ✅ Professional multi-page reporting
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## 🧠 Machine Learning Workflow
```text
Historical Public Health Data
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Data Cleaning
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Feature Engineering
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Model Training
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Model Evaluation
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Best Model Selection
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Streamlit Dashboard
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AI Decision Support
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Professional PDF Report
```
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## 🏗️ Technologies Used
### Programming
- Python
### Machine …