3 Commits

Author SHA1 Message Date
e95e2f1338 feat: add analysis pages and raster risk map
Ship a new app version with broader analytics, restructured
dashboards, and a server-rendered risk map.

Frontend:
- Add Overview, Demographic, Disease, and Environmental Health
  analysis pages
- Add AnomalyMarkers, CalendarHeatmap, and MetricHeatmapTable
  components
- Rebuild Alerts map onto server-rendered raster risk tiles;
  expand Monitoring, Trend, and District Comparison views
- Extend API client, stores, and TypeScript types

Backend:
- Add environment router (pollutants, lag correlations)
- Add risk_raster util serving XYZ 100m risk tiles
- Expand cases endpoints (demographics, seasonality, diagnoses)
  and insights; harden auth and file-based loaders

Data & tooling:
- Add processed outpatient/inpatient/combined case parquet (LFS)
- Add nested CLAUDE.md guides, pyrightconfig, and test updates
2026-06-21 17:35:03 +08:00
e64ca3b4f5 fix: analysis 500s, caching, alert page perf
P0: Fix KeyError in 3 analysis endpoints. geojson.py stores 1d risk
as "risk_value" but analysis.py accessed "risk_1d" — always crashed.

Backend: Add lru_cache to GeoJSON/CSV/Parquet loaders, date helpers,
and district loader. Add try/except and FileNotFoundError guards.

Frontend: Debounce riskRange, merge counts into useMemo, stabilize
handleGridClick with ref, memoize nearest-grid scan, wrap AlertMap
in React.memo, switch useLodGrid from fetch to cachedGet.
2026-06-05 02:27:10 +08:00
fc468464b2 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.
2026-06-05 02:13:49 +08:00