Gitauking/disease-surveillance-kenya

A containerized data pipeline for disease surveillance in Kenya (2007–2022). Uses Docker, Postgres, and Python to ingest and model outbreak data, with Grafana dashboards for cases, deaths, mortality rates, and forecasts (2023–2025). Demonstrates ETL, time-series forecasting, and health analytics. # Disease Surveillance & Prediction Pipeline (Kenya 2007–2022) ## 🚀 Overview This project ingests disease surveillance data (2007–2022, Kenya) into a Postgres database, then visualizes insights and forecasts using Grafana. ## ⚡ Tech Stack - Docker + Docker Compose - PostgreSQL (data store) - Adminer (database admin UI) - Grafana (dashboards) - Python Ingestor (CSV → Postgres) - Python Modeler (synthetic yearly series + Holt-Winters forecasting) ## 📂 Project Structure disease_surv_project/ ├── data/ # CSV data │ └── kenya_outbreaks_2007_2022.csv ├── ingestor/ # Data ingestion service │ ├── Dockerfile │ └── ingestion.py ├── modeler/ # Forecasting service │ ├── Dockerfile │ └── model_train.py ├── docker-compose.yml ├── .env.example └── README.md# disease-surveillance-kenya