SARS-CoV-2 wastewater surveillance data

We made a major change to our SARS-CoV-2 assay in November 2024 which affects all data. Visit the 'Info and methods' tab at the left for details.

Visit the 'Info and methods' tab on the left to see more detailed information on how our samples are collected, analyzed, and interpreted.

Select a sampling site from the map to populate the graphs.

Click on the + at the right to expand the summary table.

General information, data analysis, and interpretation

Important notes:

• New: On 2024-11-14, we moved our SARS-CoV-2 assay to a new, single gene target. Before that date, all SARS-CoV-2 data were based on the combined results from 2 different gene targets. Parallel testing of both methods showed that concentrations based on the previous 2 combined gene targets was almost exactly 1/2 the value of concentrations based on the new, single gene target. To aid data comparability across lab methods, all historical data has been divided in half. Data trends, patterns, and interpretations remain unchanged.

• On 2024-2-28, we moved all quantification of wastewater surveillance samples from a qPCR process to a ddPCR (droplet digital PCR) process. While parallel testing of both methods indicated that the results are often very similar, we recommend using caution when interpreting or combining data from before and after that date.

• On 2021-08-01, all laboratory analyses moved to the Utah Public Health Laboratory from academic partner labs. While data for many sites remained quite similar, some sites did display a noticeable shift. We recommend using caution when you interpret or combine data from before and after that date.

Dashboard updates

The data displayed in this dashboard updates daily overnight. Note that new wastewater data will usually be added twice per week, typically on Tuesdays (for samples collected the previous Thursday) and Fridays (for samples collected the previous Tuesday). Sampling may be cancelled for state and federal holidays due to a lack of available staff at our partner utilities.

Sampling

Current sites: 35 sites are sampled on Tuesdays and Thursdays. The majority of our partner utilities collect either flow- or time-weighted composite samples of roughly 24 hours duration (meaning sampling begins on Mondays or Wednesdays and ends on Tuesdays or Thursdays). Two sites (Snyderville Basin East Canyon and Snyderville Basin Silver Creek) collect 6-hour manual composite samples, and Roosevelt collects grab samples.

New sites: When we begin sampling at a new site, it takes some time before we can be confident when when we categorize concentrations due to the method's reliance on site-specific historical data.

We currently have no new sites.

Legacy sites: There are currently 12 wastewater facilities where samples are no longer being collected: Blanding City WWD, Daggett County WRF, Dutch John WRF, Fillmore City SD, Gunnison City SD, Magna WWTP, Mona SD, Moroni WWTP, Monticello WWTP, Oakley WWTP, Richfield City SD, and Springdale SD. To see old data from these sites, click on the 'Show legacy sites' button on the map. Note the x-axis dates for these old data!

Wastewater data analysis and interpretation

We recommend you use trends and categorized concentrations (as described below) to compare data between sites. Given the large number of differences between sites in infrastructure, climate, population characteristics, etc., we discourage direct comparisons or averaging of raw data between sites.

Dates: Our analyses use the date sampling ended in our analyses. Thus, a sample whose collection began 10/02/23 and ended 10/03/23 would use a date of 10/03/23. Note that the CDC uses the date sampling began, so that same sample would use a date of 10/02/23 in their analyses.

Reporting limits: The smallest concentration that can be reported by the laboratory is called the reporting limit. It is a function of the sensitivity of the lab instrument, aspects of the specific methods being used, and other factors. In essence, we are confident in the accuracy of values above the reporting limit, even though we don't know the true concentration for values below the reporting limit.

Our most common reporting limit for SARS-CoV-2 is 12 copies/milliliter of wastewater, although this has varied somewhat with minor shifts in our methods. For analytical and display purposes, concentrations below the reporting limit are set to 1/2 of the reporting limit. Note that values below the reporting limit do not necessarily indicate a complete lack of cases in that sewershed.

Normalization and units: Quantitative PCR results are normalized by the wastewater flow during the sampling period and the estimated sewershed population. The resulting units are millions of gene copies per person per day, or MGC/person/day.

Concentration: Concentrations are categorized into a three-tier system: Low, Watch, and Elevated. These categorizations are site-specific and a relative measure of concentration, meaning that it is valid to compare categories between sites (unlike comparing the underlying data itself). To determine the categorizations, quantile thresholds (20%, 40%, 60%, 80%, and 95%) are calculated using historical data from each site. Each data point is compared against these site-specific thresholds and placed into the appropriate 'bin' (0-20%, 60-80%, etc.). The data is then further categorized into a three-tier system as follows:

• Low: 0-20% and 20-40%. Data in this category is relatively low compared to historical data from the site.
• Watch: 40-60%. This is a middle category for data that while not necessarily considered high, also can't be considered low.
• Elevated: 60-80%, 80-95%, 95+%. Data in this category is considered high compared to historical data from the site.

Trend: Trend identification is based on a linear regression of the log transformed results normalized for flow and population (i.e., our normal results transformed onto a log scale). Regressions are calculated over a 13-day period from the most recent sample, which normally includes 4 samples. The chosen significance level is 0.30; sites with regression p-values above 0.30 are categorized with a trend of Plateau/Indeterminate. Note that at least 3 samples in this 13-day period are required to derive a p-value. Sites with fewer than 3 samples in that 13-day period are flagged 'Insufficient recent data'.

The 13-day percent change is based on the slopes from these regressions. Percent change is not calculated when the slope is 'Plateau/Indeterminate' (i.e., when the slope is not significant).

Plateau/indeterminate means that viral RNA was detected, but there was not a significant recent trend based on the above criteria. This does not indicate the magnitude of viral RNA in the sewer system. The level of viral RNA in wastewater may be high, low, or in between relative to previous samples from that site.

Case data

Geocoding: All COVID-19 cases in our database are assigned to a sewershed based on residential address at diagnosis. If a case cannot be geocoded due to missing or bad address information but has at least a ZIP code, it is randomly allocated to an appropriate sewershed with a probability based on the distribution of residential ZIP code addresses within various sewersheds.

For example, take hypothetical ZIP code X that is partially covered by sewersheds A and B. If 31% of the residential ZIP code addresses are within sewershed A and 23% are within sewershed B, then such a case would be randomly allocated to sewershed A 31% of the time and to sewershed B 23% of the time.

Data suppression: Following department protocol on data privacy and security, daily case counts between 1 and 4 (and metrics based on such counts, like case rates) are suppressed. This means that we do not display the actual count or rate. Instead, we replace the actual case count with a value of 2, which is the nearest whole number to the mean and median of all suppressed counts. Note that case data suppression tends to occur more frequently in sewersheds with smaller populations, as they typically have fewer cases on a given day.

National Wastewater Surveillance System (NWSS)

In response to the COVID-19 pandemic, CDC launched the National Wastewater Surveillance System (NWSS) in September 2020. CDC developed NWSS to coordinate and build the nation’s capacity to track the presence of SARS-CoV-2, the virus that causes COVID-19, in wastewater samples collected across the country. Utah was one of the initial eight states to join this effort. Now, only a few short years later, nearly all states and several cities participate.

Visit the NWSS website: www.cdc.gov/nwss

View national wastewater surveillance data: https://covid.cdc.gov/covid-data-tracker/#wastewater-surveillance

Frequently asked questions

What is wastewater surveillance?

People who are infected with SARS-CoV-2 (and potentially other pathogens) shed viral RNA (genetic material from the virus) in their feces. This RNA can be detected and measured in samples of community wastewater. Wastewater, also called sewage, can come from both residential use (e.g., toilets, showers, and sinks) as well as non-household sources like industrial use and rain. The process can be summarized as follows:

• Wastewater from a sewershed (the community area served by a wastewater treatment utility) is collected as it flows into a treatment plant before treatment occurs (i.e., an influent sample).
• The sample is transported to the Utah Public Health Laboratory (UPHL) for sample processing and testing.
• UPHL transmits the raw laboratory data to the UWSS epidemiology team, who clean and analyze it.
• The data is made available to federal, state, and local public health partners via internal mechanisms, and the public via this dashboard.

What are some advantages of wastewater surveillance?

• Wastewater surveillance can capture the presence of SARS-CoV-2 shed by people who have COVID-19, even if they don't have symptoms.
• Wastewater surveillance data is often an early indicator that the number of people who have COVID-19 in a community is increasing or decreasing.
• Unlike most other types of public health surveillance, wastewater monitoring does not depend on the availability of individual testing, people having access to healthcare, or people seeking healthcare when sick (i.e., healthcare-seeking behavior).
• Wastewater surveillance is a very efficient and cost-effective way to gather valuable public health data about communities.

What are some disadvantages of wastewater surveillance?

• Wastewater surveillance will not capture data from homes that use a septic system or from facilities served by decentralized treatment systems, like some prisons, universities, or hospitals, that treat their own wastewater.
• Very low levels of infection in communities may not be captured by wastewater surveillance. The lower limits of detection (i.e., the smallest number of people shedding the virus that can still be detected by current methods) for wastewater surveillance are not yet known.
• At this time, it is not possible to accurately and reliably predict the number of infected individuals in a community based solely on wastewater surveillance data.
• We don't yet know enough about the many differences between sewersheds in infrastructure, population characteristics, industrial input, etc. to successfully account for them, meaning that direct comparison of data between sites is generally discouraged.

What is UWSS monitoring in wastewater?

Currently, UWSS is testing for SARS-CoV-2, the virus that causes COVID-19. In the future, we plan to expand testing to additional pathogens.

Can SARS-CoV-2 variants of concern be detected in wastewater?

Yes, with the appropriate additional testing. UWSS has been performing whole genome sequencing of wastewater samples since October 2021. We plan to add those data to this dashboard in the near future.

I have a question that isn't answered here.

If your question is related to sampling or data analysis, it may be answered in the 'Info and methods' tab. If not, don't hesitate to contact us at uwss@utah.gov!

Contact us

For questions, comments, and concerns, email us at:

uwss@utah.gov

We'd love to hear from you!