17d9ca0e37
RKI AMELAG wastewater surveillance data with CSV exports and bun fetch script. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
4.2 KiB
DE Wastewater Surveillance (AMELAG)
🎯 BEST ESTIMATE
| Metric | Value | Confidence | Last Updated |
|---|---|---|---|
| SARS-CoV-2 viral load (national) | ~1,554 gc/L | 90% | 2026-04-15 |
| SARS-CoV-2 4-week trend | -52.8% (↓↓) | 85% | 2026-04-15 |
| SARS-CoV-2 % of all-time peak | 0.3% | 90% | 2026-04-15 |
| Influenza A 4-week trend | -39.3% (↓↓) | 85% | 2026-04-15 |
| RSV B 4-week trend | -27.0% (↓↓) | 85% | 2026-04-15 |
One-liner: All five tracked respiratory pathogens declining in German wastewater, SARS-CoV-2 at 0.3% of peak.
Caveat: Wastewater surveillance detects population-level viral shedding, not clinical severity; seasonal declines are expected in spring.
Quick Context
Germany's AMELAG network (Abwassersurveillance für die epidemiologische Lagebewertung) monitors respiratory viruses in wastewater from ~67–75 treatment plants covering ~25% of the population. Wastewater data provides an unbiased signal of community infection levels because it captures all shedding individuals regardless of testing behavior. The system tracks SARS-CoV-2, Influenza A/B, and RSV A/B with weekly population-weighted national aggregates.
Datasets
wastewater-latest.csv
Full time series for all pathogen types (SARS-CoV-2, Influenza A/B, RSV A/B, and combined variants).
- datum: Week date (Wednesday of reporting week)
- typ: Pathogen type
- n_sites: Number of reporting wastewater treatment plants
- pop_coverage_pct: Population coverage percentage
- viruslast_gc_per_l: Viral load in gene copies per liter
- viruslast_normalisiert: Flow-normalized viral load
- vorhersage_gam: GAM-smoothed prediction value
- obere_schranke / untere_schranke: 95% confidence intervals
wastewater-summary.csv
Current status summary per primary pathogen with trend analysis.
Methodology Summary
Approach: Population-weighted aggregation of wastewater treatment plant viral load measurements, smoothed with Generalized Additive Models (GAM).
Sources:
Definition Used: Gene copies per liter (gc/L) of treated wastewater influent, population-weighted national aggregate across reporting sites.
Source Analysis
Why These Sources?
| Source | Strengths | Weaknesses | Weight Given |
|---|---|---|---|
| AMELAG GitHub (RKI/UBA) | Official open data, CC-BY 4.0, machine-readable TSV, weekly updates | ~25% population coverage, 1-2 week lag | High |
| Infektionsradar Dashboard | Visual context, additional metrics | No public API, frontend-only | Reference |
Key Limitations
- Population coverage is ~25% — not all German cities/regions are equally represented.
- Lab changes at individual sites can cause discontinuities (flagged in individual site data).
- Wastewater measures viral shedding, not infections or severity — the relationship between gc/L and clinical burden is non-linear.
Substrate Connection
- Problems: PR-00003 (Performance Society Exhaustion — pandemic impact on work/health)
- Related Datasets: Bay-Area-COVID-Wastewater (US equivalent)
- Cross-reference: DE-Mental-Health (pandemic impact on mental health indicators)
Research Metadata
| Attribute | Value |
|---|---|
| Research Date | 2026-04-22 |
| Researcher | Sven / PAI |
| Method | Automated fetch from AMELAG GitHub TSV |
| Confidence Level | 90% |
| Known Gaps | Individual site data not included in summary; variant-level data not available in wastewater |
Changelog
| Date | Change | Reason |
|---|---|---|
| 2026-04-22 | Initial dataset creation | Implement DE wastewater surveillance from AMELAG |
Full Data
See wastewater-latest.csv for the complete time series (905 data points across all pathogen types).
Fetch script: bun get-de-wastewater from Substrate root.