What is this? Public health researchers measure SARS-CoV-2 (the COVID-19 virus) in wastewater as an early warning system. Because infected people shed the virus in their feces, the concentration in sewage reflects how many people in a community are currently infected — even those who never get tested.
This tool converts those wastewater readings into an estimated number of people currently infectious. The underlying model was fitted to 11 paired data points spanning two years of wastewater signal levels and independent expert prevalence estimates, and explains 95% of the variance in that dataset.
Where to find your local wastewater reading: Visit WastewaterSCAN and find your nearest monitoring site. Look for the "N Gene:PMMoV" value — that's the number to enter below. You can use the slider or type directly into the number field.
Data sources & credits
Wastewater data: WastewaterSCAN (Stanford & Emory), a national wastewater surveillance program monitoring SARS-CoV-2 and other pathogens across 140+ US sites.
Prevalence estimates: @JPWeiland on X, who publishes independent estimates of COVID infectious prevalence derived from wastewater and other surveillance data. All 11 calibration data points used to fit this model are drawn from his published estimates (2023–2026).
Tool methodology: Developed with assistance from Claude (Anthropic). The model uses a power law fit (log-log regression) across 11 paired signal/prevalence observations, achieving R²=0.953.
Disclaimer: This is an independent estimation tool, not an official public health product. Estimates carry significant uncertainty and should be interpreted as order-of-magnitude guidance, not precise counts.
Calibration data points & methodology
| Date | Signal | Trend | JPWeiland estimate | Model prediction |
|---|---|---|---|---|
| Jun 22, 2026 | 17.33 | Stable | <40,000 new/day (~1 in 1,196) | 1 in 1,093 |
| Apr 10, 2026 | 37.09 | Declining | 1 in 550 infectious | 1 in 535 |
| Mar 29, 2026 | 51.39 | Declining | 135,000 new/day; ~1 in 500 | 1 in 394 |
| Mar 10, 2026 | 73.90 | Declining | 325,000 new/day; ~1 in 200 | 1 in 280 |
| Nov 15, 2024 | 97.41 | Declining | 185,000 new/day; 1 in 180 | 1 in 216 |
| Apr 19, 2024 | 109.80 | Declining | 200,000 new/day; 1 in 164 | 1 in 193 |
| Jul 18, 2025 | 162.70 | Rising | 209,000 new/day; ~1 in 160 | 1 in 133 |
| Sep 5, 2025 | 323.20 | Declining | 480,000 new/day; 1 in 70 | 1 in 70 |
| Nov 27, 2023 | 398.50 | Rising | 620,000 new/day (~1 in 90) | 1 in 58 |
| Sep 6, 2024 | 444.80 | Declining | 870,000 new/day; 1 in 38 | 1 in 52 |
| Aug 2, 2024 | 642.00 | Stable | 900,000 new/day; 1 in 37 | 1 in 37 |
How the model works: The N Gene:PMMoV ratio normalizes SARS-CoV-2 genetic material in wastewater against Pepper Mild Mottle Virus (PMMoV), a stable human fecal indicator virus. This normalization corrects for dilution effects and population size differences between monitoring sites.
Model fitting: A power law relationship (log-log regression) was fitted across 11 paired observations of wastewater signal and prevalence estimates published by @JPWeiland between 2023 and 2026. The resulting equation is: 1-in-N = 15,914 × Signal^(−0.939), with R²=0.953. The near-linear exponent of −0.939 means that halving the signal roughly doubles the estimated 1-in-N, with a slight flattening at very low signal levels. On the log-log chart, this appears as a straight line — which is why the log scale makes the fit so much easier to read.
Phase detection: When today's signal differs from the signal 10 days ago by more than 10%, the tool detects a trend automatically. During a decline, people infected when the signal was higher are still contagious today — so the effective signal used in the model is a weighted average of today's reading and the reading from 10 days ago (40%/60% weighting). During a rise, the weighting reverses (60%/40%). During stable periods, today's signal is used directly.
Uncertainty: The ±25% uncertainty band reflects typical residual error in the model — most predictions fall within this range of Weiland's actual estimates. Estimates should be treated as order-of-magnitude guidance. "Infectious" per Weiland's framing means currently capable of transmitting; total infected (including those recovering) would be somewhat higher.