A Data-Driven Early Warning System for Predicting Cholera, Typhoid, and Diarrhea Disease Outbreaks from Water Quality in African Communities
# Water-Quality
### Table of Contents
- Key Insights
- Objectives
- Process
- Presentation
- Tools
### Key Insights
- Poor water quality (high turbidity, E. coli contamination, high nitrate levels) is strongly linked to waterborne diseases like cholera, typhoid, and diarrhea.
- Early prediction can help target interventions before outbreaks escalate.
- Integrating water quality, disease records, and geospatial data enables effective, real-time health surveillance.
- Seasonal trends and regional differences (urban slum vs. rural vs. coastal) play a significant role in outbreak patterns.
### Objectives
1. Predictive Goal: Estimate the total number of waterborne disease cases in a community using water quality and location data.
2. Classification Goal: Categorize communities into High, Medium, or Low risk levels.
3. Public Health Impact: Enable timely, targeted interventions to reduce disease spread.
4. Policy Support: Provide actionable insights for NGOs, health ministries, and WASH programs.
### Process / Workflow
1.Data Cleaning & Preprocessing
Convert dates to datetime format
Scale numerical features (optional for some models)
Feature engineering:
Total_Waterborne_Cases = Cholera + Typhoid + Diarrhea
Time-based features (month, quarter)
2.Exploratory Data Analysis (EDA)
Time trends by region
Correlation between water quality metrics and disease counts
Seasonal pattern analysis (rainy vs. dry season)
Spatial risk visualization
Identify highest-risk countries/communities
3.Modeling
Regression (Primary Task): Linear Regression, Random Forest Regressor, XGBoost, LSTM (optional)
Classification (Secondary Task): Logistic Regression, Random Forest Classifier, XGBoost Classifier
4.Model Evaluation
Regression: MAE, RMSE, R² Score
Classification: Accuracy, Precision, Recall, F1-score, Confusion Matrix
5.Deployment
Interactive dashboard ( Power BI) for trends, heatmaps, and predictions
Email notifier to alert health authorities of high-risk commun …