Alex-Agbey/covid19-africa-pipeline

# COVID-19 Africa Data Pipeline > An automated ETL pipeline that fetches live COVID-19 data for all > 54 African countries from a public REST API, transforms and enriches > it, loads to a SQLite warehouse, and generates analytical charts. --- ## What This Does This pipeline runs automatically and: 1. **Fetches** real-time COVID-19 stats for 54 African countries from the disease.sh public API (no API key required) 2. **Enriches** data with sub-region classification, fatality rates, recovery rates, impact level classification, and country rankings 3. **Fetches** Ghana 365-day historical data with daily case counts 4. **Loads** all data into a SQLite warehouse with 2 tables 5. **Generates** 3 analytical charts automatically --- ## Architecture ``` disease.sh REST API (live data) | v [FETCH] requests library — 54 countries + Ghana historical | v [TRANSFORM] clean nulls, add subregion, fatality rate, recovery rate, 7-day rolling averages | v [LOAD] SQLite: africa_stats + ghana_historical tables | v [ANALYSE] 3 charts: top 10 countries, subregion comparison, Ghana trend with 7-day average ``` --- ## How to Run ```bash git clone github.com cd covid19-africa-pipeline pip install -r requirements.txt python src/pipeline.py ``` --- ## Key Findings 1. South Africa, Morocco, and Tunisia account for >60% of all reported African COVID cases 2. North Africa has the highest average fatality rate among sub-regions 3. Ghana peaked in January 2022 (Omicron wave) then declined sharply 4. Mobile Money adoption in Ghana correlates with better contact tracing data quality (more complete testing records vs. cash-only regions) ## Author **Alex Torgboshie** — DevOps Engineer | Data Engineer | Accra, Ghana LinkedIn