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.

deploy/frontend/.dockerignore

@@ -0,0 +1,6 @@
+node_modules
+.git
+*.md
+tests
+.env*
+dist