feat: add reports center, admin drill-down, disease filter + bug fixes + perf optimization

Frontend features:
- 报表中心 (ReportsCenter): list/detail views, diagnosis breakdown chart, CSV export
- 多级行政下钻 (AdminBreadcrumb): 湖北省→武汉市→区→街道 hierarchical drill-down
- 按病种筛选 (DiseaseFilter): multi-select diagnosis filter on monitoring + reports pages

Backend:
- Add /forecast/{days} endpoint, diagnosis filter params on cases endpoints
- Add /streets aggregation endpoint, enrich reports with real case data
- Extract shared case_loader module

Bug fixes (14):
- Fix missing /risk/forecast route (404), historyApi pointing to non-existent router
- Fix min_risk filter silently ignored in insights/hotspots
- Fix type mismatches: CaseTrendResponse, CaseStatsResponse shapes
- Fix silent .catch(() => {}) swallowing errors, fetchAlerts not clearing stale state
- Fix lru_cache caching exceptions, generateReport used cachedGet for write op
- Fix missing useEffect deps in Insights, DistrictComparison, ReportsCenter

Performance (9):
- Zustand selectors across 9 components (eliminate re-render cascades)
- Fix districtCases.sort() mutating store state, inline IIFE → memo'd component
- CaseLocationMap: React.memo, race protection, correct deps
- AlertCard: stable callbacks, TimelinePlayer: useMemo, TopNav: clock isolation
- SideNav: modules array to module scope, DiseaseFilter: memoized filter

backend/routers/geocoded.py

@@ -1,7 +1,7 @@
 """
 Router for geocoded case data and grid aggregated data
 """
-from fastapi import APIRouter, HTTPException
+from fastapi import APIRouter, HTTPException, Query
 from pydantic import BaseModel
 from typing import List, Optional
 import logging
@@ -53,6 +53,18 @@ class GeocodedResponse(BaseModel):
     cases: List[GeocodedCaseData]
     total_count: int
 
+
+class StreetData(BaseModel):
+    """Street-level aggregated case data"""
+    name: str
+    total_cases: int
+    outpatient: int
+    inpatient: int
+
+
+class StreetsResponse(BaseModel):
+    streets: List[StreetData]
+
 @router.get("/grid", response_model=GridCaseResponse, summary="Get aggregated grid case data")
 async def get_grid_cases():
     """
@@ -176,3 +188,38 @@ async def get_geocoded_count():
     except Exception as e:
         logger.exception("Error counting geocoded cases")
         raise HTTPException(status_code=500, detail="Internal server error")
+
+
+@router.get("/streets", response_model=StreetsResponse, summary="Get street-level aggregation")
+async def get_streets(district: str = Query(..., description="District name")):
+    """Get street-level aggregated case data for a district."""
+    cases_file = DATA_DIR / "geocoded_all_cases.csv"
+    if not cases_file.exists():
+        raise HTTPException(status_code=404, detail="Geocoded data not found")
+
+    try:
+        df = _load_csv(cases_file)
+        df = df.dropna(subset=['latitude', 'longitude'])
+        df = df[df['district'] == district]
+
+        # Group by street
+        streets = []
+        if 'street' in df.columns:
+            street_groups = df.groupby('street')
+            for street, group in street_groups:
+                if pd.isna(street) or str(street).strip() == '':
+                    continue
+                out_count = len(group[group['case_type'] == 'outpatient'])
+                in_count = len(group[group['case_type'] == 'inpatient'])
+                streets.append(StreetData(
+                    name=str(street),
+                    total_cases=len(group),
+                    outpatient=out_count,
+                    inpatient=in_count
+                ))
+            streets.sort(key=lambda s: s.total_cases, reverse=True)
+
+        return StreetsResponse(streets=streets)
+    except Exception as e:
+        logger.exception("Error loading street data")
+        raise HTTPException(status_code=500, detail="Internal server error")