feat: Initial CBPOA commit — 武汉儿童呼吸疾病风险评估系统

Context: Build a spatial risk assessment system correlating air quality
data with children's respiratory disease incidence across Wuhan.

Approach: FastAPI backend serving PostGIS spatial queries, React
frontend with Deck.gl maps, and a PyTorch SpatialTemporalGCN pipeline
for multi-day (1d/3d/7d) risk prediction.

Changes:
- backend/ — FastAPI API with auth (JWT), alerts, risk analysis,
  geocoded case data, grid statistics, and report endpoints
- frontend/ — React dashboard with interactive risk maps, alert
  monitoring, district comparison charts, and timeline player
- models/ — SpatialTemporalGCN model with trained weights and ONNX
  export for inference
- scripts/ — ETL pipeline for weather + medical data, grid generation,
  feature engineering, training, and daily inference
- deploy/ — Docker Compose configs for backend, frontend, and MLflow
- docs/ — API docs, deployment guide, user guide, and code review

Impact: Enables spatial risk visualization, alert monitoring, and
ML-driven health risk forecasting for environmental health teams.

backend/utils/geo.py

@@ -0,0 +1,43 @@
+"""
+Geographic utilities: point-in-polygon testing via ray casting.
+"""
+
+
+def point_in_polygon(lat: float, lon: float, polygon_coords: list) -> bool:
+    """Check if a point is inside a polygon (supports Polygon and MultiPolygon)."""
+    if not polygon_coords:
+        return False
+
+    # MultiPolygon: check each polygon
+    if isinstance(polygon_coords[0], list) and isinstance(polygon_coords[0][0], list):
+        for polygon in polygon_coords:
+            if polygon and isinstance(polygon[0], list):
+                ring = polygon[0] if isinstance(polygon[0][0], list) else polygon
+                if point_in_ring(lat, lon, ring):
+                    return True
+        return False
+
+    # Single Polygon: use first ring (outer boundary)
+    ring = polygon_coords[0] if isinstance(polygon_coords[0], list) else polygon_coords
+    return point_in_ring(lat, lon, ring)
+
+
+def point_in_ring(lat: float, lon: float, ring: list) -> bool:
+    """Ray casting algorithm for point-in-ring test."""
+    n = len(ring)
+    inside = False
+
+    x, y = lon, lat
+    p1x, p1y = ring[0]
+
+    for i in range(1, n + 1):
+        p2x, p2y = ring[i % n]
+        if y > min(p1y, p2y):
+            if y <= max(p1y, p2y):
+                if x <= max(p1x, p2x):
+                    xinters = (y - p1y) * (p2x - p1x) / (p2y - p1y) if p1y != p2y else p1x
+                    if p1x == p2x or x <= xinters:
+                        inside = not inside
+        p1x, p1y = p2x, p2y
+
+    return inside