Healthcare Accessibility Mapping with GIS and AI in Sub-Saharan Africa

// 1. Define Spatial Scope: Country boundary for Kenya in Sub-Saharan Africa
var countries = ee.FeatureCollection('FAO/GAUL/2015/level0');
var kenya = countries.filter(ee.Filter.eq('ADM0_NAME', 'Kenya'));
var roi = kenya.geometry();

// 2. Load WorldPop 2020 Population Count Data
var worldpop = ee.ImageCollection('WorldPop/GP/100m/pop')
  .filter(ee.Filter.eq('year', 2020))
  .select('population')
  .mosaic()
  .clip(roi);

// 3. Load Oxford MAP Travel Time to Cities (2015)
var travelTime = ee.Image('Oxford/MAP/accessibility_to_cities_2015_v1_0')
  .select('accessibility')
  .clip(roi);

// 4. Load SRTM Elevation for topographical context
var elevation = ee.Image('USGS/SRTMTM_003').select('elevation').clip(roi);
var slope = ee.Terrain.slope(elevation);

// 5. Center map display over Kenya
Map.centerObject(kenya, 6);
Map.setOptions('ROADMAP');

// 6. Define visualization parameters for population
var popVis = {
  min: 0.0,
  max: 50.0,
  palette: ['#f7fcf5', '#e0f3f8', '#9ecae1', '#4292c6', '#084594']
};

// 7. Define visualization parameters for travel accessibility (minutes)
var travelVis = {
  min: 0.0,
  max: 300.0,
  palette: ['#1a9850', '#91cf60', '#d9ef8b', '#fee08b', '#fc8d59', '#d73027']
};

// 8. Add layers to the Earth Engine map canvas
Map.addLayer(worldpop, popVis, 'WorldPop Population 2020 (per cell)');
Map.addLayer(travelTime, travelVis, 'Travel Time to Facility/City (Min)');
Map.addLayer(slope, {min: 0, max: 20, palette: ['white', 'black']}, 'Terrain Slope (Degrees)', false);

// 1. Define criteria for underserved health population
// High population density (> 5 people per 100m grid cell) AND long travel time (> 120 minutes)
var highPopMask = worldpop.gte(5);
var longTravelMask = travelTime.gte(120);

// 2. Combine conditions to extract priority underserved spatial zones
var underservedMask = highPopMask.and(longTravelMask);
var underservedPop = worldpop.updateMask(underservedMask);

// 3. Highlight priority underserved areas in bright red
var underservedVis = {
  palette: ['#ff0000']
};
Map.addLayer(underservedPop, {min: 5, max: 100, palette: ['#ff7800', '#e31a1c', '#800026']}, 'Underserved Population Grid');

// 4. Calculate total estimated population living > 2 hours away from facility nodes
var totalUnderserved = worldpop.updateMask(longTravelMask).reduceRegion({
  reducer: ee.Reducer.sum(),
  geometry: roi,
  scale: 100,
  maxPixels: 1e9
});

// 5. Calculate total national population for percentage baseline
var totalPopulation = worldpop.reduceRegion({
  reducer: ee.Reducer.sum(),
  geometry: roi,
  scale: 100,
  maxPixels: 1e9
});

// 6. Print summary quantitative results to console
print('Total National Estimated Population:', totalPopulation.get('population'));
print('Estimated Population > 2 Hours Travel Time:', totalUnderserved.get('population'));

// Export the underserved population raster to Google Drive for GIS reporting
Export.image.toDrive({
  image: underservedPop.unmask(0),
  description: 'Underserved_Healthcare_Population_Kenya',
  folder: 'GEE_PublicHealth_Exports',
  fileNamePrefix: 'Underserved_Pop_Kenya_2020',
  region: roi,
  scale: 250,
  maxPixels: 1e9
});