theolumayowa10/west-africa-malaria-epidemiology

Analysis of 21 years of malaria data across West Africa using Python (data prep) and Power BI (dashboard visualization). # West Africa Malaria Epidemiology Dashboard (2000–2021) This project analyzes 21 years of malaria epidemiology data across West Africa using **Python** for data preparation and **Power BI** for interactive visualization. The goal is to uncover long-term trends, highlight high-burden countries, and support public health insights. --- ## Overview The analysis focuses on: - Malaria incidence trends (2000–2021) - 3-year rolling averages for smoothed patterns - Country-by-country malaria burden ranking - Geospatial distribution of malaria metrics - Interactive filtering by Year, Country, and Metric The final deliverable is a fully interactive **Power BI dashboard** that allows users to explore malaria patterns across West Africa. --- ## Tools & Technologies **Python** - Data cleaning and transformation (Pandas) - Rolling average calculation - Export of final dataset for dashboard use **Power BI** - Line charts, ranking charts, KPI cards - Map visualization - Pie chart for burden distribution - Custom theming and UI layout --- ## Dataset Sourced from the **WHO Global Health Observatory**, transformed using Python. Key fields include: - Country - Year - Malaria Metric - Value - 3-Year Rolling Average --- ## Workflow ### 1. Data Preparation (Python) - Cleaned and standardized raw dataset - Calculated percentage changes and rankings - Generated rolling averages - Exported final CSV for Power BI ### 2. Dashboard Development (Power BI) - Connected cleaned dataset - Built interactive slicers - Created trend and rolling-average line charts - Added KPI and burden-ranking visuals - Designed map and pie chart for distribution analysis ---