COVID-19: Wisconsin Coronavirus Wastewater Monitoring Network

This interactive dashboard includes:

• A waffle chart showing the number of sewersheds within each concentration category (outlined below)
• A graph comparing average SARS-CoV-2 levels at all sewersheds with average COVID-19 case rates for all participating sewersheds.
• Concentrations of SARS-CoV-2 virus gene copies in the wastewater, normalized by sewage flow and sewershed population.
• Daily new COVID-19 case rates within the chosen sewershed.
• Wisconsin sewershed locations and boundaries that are included in the monitoring network.

A sewershed is an area of land where raw sewage from homes and businesses flows through a series of sewer pipes into a single downstream point, where it enters a wastewater treatment facility.

The list on the left shows how the three most recent samples at a given facility compare to all of the samples from the past six months. To compare, we look at all measurements from the past six months, and separate the data into quintile-based concentration categories.

• Highest 20% (very high)
• 60th - 80th percentile (high)
• 40th - 60th percentile (moderate)
• 20th - 40th percentile (low)
• Lowest 20% (very low)

This process lets us determine cutoffs between those categories. We compare the average of the three most recent samples to those cutoffs, and are able to determine whether recent values are higher, about the same, or lower than the past six months of data, which is displayed as the category on the dashboard.

Significant increases in SARS-CoV-2 levels in wastewater are defined when recent measurements show an increasing trend and new values are higher than recent measurements. Increasing trends are determined from a linear regression over the past five measurements using a relaxed significance test (p < 0.3). A high measurement is defined if the average of the three most recent data points is above the 80th percentile of all data from the past 30 days (as opposed to six months as above).

An increase in virus gene copies over time shows that cases may be increasing in the community. Because each community is different, you should not compare viral gene copy numbers between communities. Looking at trends over time in a specific community can be used to help understand whether cases or hospitalizations are likely to increase in the future.

The wastewater concentration of SARS-CoV-2 figure can now be viewed with a linear or a logarithmic (log) scale. These two options are displaying the same values, but with different scales on the y-axis of the figure.

• A linear scale can be most helpful when data points are in a narrow range and there isn't much variability between them.
• A log scale can be most helpful when there is a large range of values in the data. Because there is a large range of values in the wastewater data, a log scale may be more helpful to see trends over time in certain sewersheds.

Benefits of monitoring for SARS-CoV-2 in wastewater

Early Detection

• People with COVID-19 begin to have the virus in their feces shortly after they catch the virus, sometimes days before they would begin to show symptoms or get tested.
• Increases of viral gene copies in wastewater have been seen up to a week before corresponding increases in diagnosed cases seen through testing.
• By seeing a rise in cases earlier, local public health interventions can be implemented sooner. This can then help limit COVID-19 spread in a community.

"Pooled" Sampling

• Rather than test every single person individually, this approach allows monitoring of entire communities at the same time.
• It captures those without symptoms and people that may not go in for testing. This provides a more complete picture of COVID-19 activity in a community.

Limitations of monitoring for SARS-CoV-2 in wastewater

There are several limitations to wastewater surveillance, which is why we recommend following trends over time:

• Population migration. The people that contribute to a sewershed may vary from day-to-day, as they travel in or out of a sewershed for work or tourism.
• Uncertainties in shedding of the virus. The amount and how long people shed the virus is still unclear. Since it is still unclear how much virus people shed, we cannot use wastewater results to estimate the number of people with COVID-19.
• Variability of samples and analysis. The laboratories analyzing results from the sampled sites work closely with the CDC to ensure best methods are used. However, because these methods are new, they will likely change and improve over time.

We are still learning about when and how much virus is in the feces of people with COVID-19. Therefore,you should only look at the trends of viral gene copies over time. The data in the dashboard shows the total number of viral gene copies detected in the area from which the wastewater was collected.

Because people can have the virus in their feces for 20 to 30 days after they are no longer contagious, decreases in the number of viral gene copies in wastewater might lag behind decreases in cases in a community. You should take the number of viral gene copies in wastewater into account along with community case numbers and other COVID-19-related data to inform decisions about taking actions to help limit COVID-19 spread.

Can I compare results from one community with another?

We do not recommend comparing the number of gene copies found between communities. The flow of wastewater is not all the same, and sources of wastewater flow are different in each community (for example: industrial discharges or rainwater). It is better to use data from a single location to see trends over time. However, you may compare trends between different locations.

The data in this dashboard will be updated at least twice per week.

Data sources:

• SARS-CoV-2 concentration data are from the Wisconsin COVID-19 Wastewater Surveillance System.
• Case data are from the Wisconsin Electronic Disease Surveillance System (WEDSS).

Additional resources

CDC National Wastewater Surveillance System

Wisconsin State Lab of Hygiene COVID-19 Wastewater Surveillance System