Momahmoses/healthcare-access-gap-analysis

GIS travel-time healthcare access gap analysis for Nigeria that identifies underserved communities. # Healthcare Facility Access Gap Analysis Geospatial tool mapping healthcare accessibility across Nigerian states using road-network travel-time analysis, population density, and facility location data, identifying underserved communities and recommending optimal sites for new clinics. --- ## Problem Statement Over 70 million Nigerians lack access to a functional health facility within reasonable travel time. State health ministries need spatial evidence to prioritise facility construction and mobile health unit deployment. --- ## Features | Feature | Description | |---------|-------------| | Travel-Time Modelling | Network-based travel time per population cluster | | Access Classification | Excellent / Good / Acceptable / Poor / Critical Gap | | Population Quantification | People without adequate access per state | | Optimal Site Recommendations | Top 10 priority locations for new facilities | | Interactive Maps | Folium maps with access levels, facility markers, and recommended sites | --- ## Tech Stack | Layer | Technology | |-------|-----------| | Geospatial | GeoPandas, Folium, Shapely | | Analysis | pandas, NumPy, scikit-learn | | Visualisation | Matplotlib, Seaborn, Plotly | --- ## Project Structure ``` healthcare-access-gap-analysis/ ├── src/ │ ├── data_loader.py # Population cluster and facility data ingestion │ ├── analysis.py # Travel-time modelling, gap scoring, recommendations │ └── visualize.py # Access maps, coverage charts ├── data/raw/ # Population rasters, facility locations, road network ├── outputs/ # Maps and recommendation reports ├── config.py # Speed profiles, access thresholds ├── main.py # Pipeline entry point └── requirements.txt ``` --- ## Quick Start ```bash git clone github.com cd healthcare-access-gap-analysis pip install -r requirements.txt python main.py ``` --- ## Data Sources - GR …