Testing for Influenza A

Testing for Mpox

Testing for Norovirus

Testing for Rotavirus

Testing for RSV

Testing for SARS-CoV-2

Catchment Area Maps

Ann Arbor WWTP

Flint WWTP

Jackson WWTP

Tecumseh WWTP

Ypsilanti WWTP

Wastewater Metrics

We present SARS-CoV2 and other viral pathogens as wastewater concentrations that have been normalized to account for the amount of human material that is in the sample. We normalize using the concentration of Pepper mild mottle virus (PMMoV) measured in the same sample. This virus is harmless to humans and is shed in stool.

Landing Page Grid

Quartile Level Selection

Quartile boundaries were calculated using PMMoV-normalized values.

Organism 0 25 50 75 100 ST.DEV
SARS-CoV-2 N1 Influent 0 0.0002622222 0.0005347985 0.0008883249 0.0085462555 0.0007447375
RSV Solid 0 0 0.000008476658 0.000038853564 0.005191065889 0.0002305836
Norovirus Influent 0.00004340733 0.00400923339 0.01274044482 0.02994468328 0.59340659341 0.04502491
Rotavirus Influent 0 0.0002336559 0.0013078136 0.0056843507 0.1681057704 0.01022976

Quartile levels set as:

  • 1 = Low = Seven-sample rolling average < 25th quartile
  • 2 = Medium = Seven-sample rolling average < 50th quartile
  • 3 = High = Seven-sample rolling average < 75th quartile
  • 4 = Highest = Seven-sample rolling average >= 75th quartile
Organism Date Range AA FL JS TM YC
SARS-CoV-2 N1 Influent 2021-07-08 to 2023-06-22 627 593 548 491 622
RSV Solid 2022-11-01 to 2023-06-20 115 108 109 108 107
Norovirus Influent 2021-09-07 to 2023-06-20 262 231 248 292 280
Rotavirus Influent 2022-01-10 to 2023-06-20 119 106 121 122 124

Influenza A Quartile Levels: Quartiles were re-calculated, using only values that were above the level of detection from the time period of 2022-09-02 to 2023-07-11. Those new quartile cut-off values are 0.00002835035, 0.00005060750, and 0.00011351033. For the quartile level system on the landing page, the level is calculated off of the single day value, not the seven-sample rolling average. If the sample is below the level of detection, no level number is assigned.

Clinical Correlation Selection


Level thresholds for SARS-CoV-2 were calculated based on correlating case rates and normalized wastewater concentration levels in Ann Arbor over the 2021-2022 year. The wastewater concentration levels correspond approximately to case rates as follows:

  • 1 = 50 or less weekly cases/100K
  • 2 = 51 to 200 weekly cases/100K
  • 3 = 201 to 400 weekly cases/100K
  • 4 = 401 weekly cases/100K or more

Influenza A:

Level thresholds for Influenza A were calculated based on correlating hospitalization rates and normalized wastewater concentration levels over the 2022-2023 Flu Season. The wastewater concentration levels correspond approximately to hospitalization levels as follows:

  • 1 = 0-0.25% of inpatient beds filled with Influenza A patients (county hospitals)
  • 2 = 0.25%-1% of inpatient beds filled with Influenza A patients (county hospitals)
  • 3 = 1-4% of inpatient beds filled with Influenza A patients (county hospitals)
  • 4 = 4-6% of inpatient beds filled with Influenza A patients (county hospitals)
  • 5 = 6%+ of inpatient beds filled with Influenza A patients (county hospitals)

The seven-sample average is colored according to the relative “level” of the organism detected.

“Trend” is a modification of the CDC’s Incidence Trend calculation, which was presented by Matt Lozier (document originally here - retrieved via the Wayback Machine from a web scrape done on 19 November 2022 available here).

If the “Trend” metric falls into “decline”, then a counter begins to count the number of days the metric is in decline. This “Days in Decline” metric uses the derivative of a spline fit to the three sample average of the PMMoV-normalized wastewater data in combination with the Trend category determination in order to decide whether the system is still “in decline”.

This decision to exit a decline is conservative, in order to account for “wobble” (natural variation) within the system and along the decline. It is slow to turn off (it needs 5 sample days of an overall increase, “elevated plateau”, or “elevated growth” in a row to turn off the downward counter) and it doesn’t let the decline stop if the system is still in “low plateau” or the category can’t be determined due to low sampling over the previous 2 weeks. This allows the scenario of a decrease, plateau, and continuation of decrease, which is a scenario which would want to be counted as one long decline.

The trend variable calculation that is presented on the Trends & Comparison page is calculated following the methodology presented by the Sentinel Wastewater Epidemiology Evaluation Project run by the Michigan Department of Health and Human Services.

7-Sample Trend = First, the seven sample rolling average for the given gene is calculated. Then the seven sample average value from 7 samples ago is subtracted from the current seven sample average. This value is divided by the seven sample average from 7 samples ago and multiplied by 100.

14-Sample Trend = First, the fourteen sample rolling average for the given gene is calculated. Then the fourteen sample average value from 14 samples ago is subtracted from the current fourteen sample average. This value is divided by the fourteen sample average from 14 samples ago and multiplied by 100.

Both trend values are categorized as:

COVID-19 Case Data

  • Case data are from the Michigan Disease Surveillance System (MDSS), the Michigan Department of Health and Human Services’ web based communicable disease reporting system. Cases are attributed to date of illness onset. If illness onset date is unavailable, date of testing is used. If date of testing is unavailable, date of referral to MDSS is used. Date attributions are subject to change over time as better data become available. Both probable and confirmed status cases are available for display. Confirmed cases only include individuals with a positive diagnostic laboratory test for COVID-19. Probable cases include individuals with COVID-19 symptoms and an epidemiological link to a confirmed case or a positive serology test, but do not have a positive diagnostic laboratory test.

  • Cases were assigned to a given wastewater catchment area only if they had associated location data included in their case report. This information for cases is associated with the individual’s residential address, so this does not account for any travel into or out of the catchment area.

  • COVID-19 case data is presented as a 7-Day Average Number of Cases per Day, per 100,000 Population. If this value for a day is < 10, then the value is not displayed (censored).

Estimated Populations of Wastewater Catchment Areas

Wastewater Catchment Area Estimated Population Source
Ann Arbor 121093 ACS 5Y Estimate 2020 - City
Flint 95999 ACS 5Y Estimate 2020 - City
Jackson 90000 State of Michigan SWEEP
Tecumseh 8680 State of Michigan SWEEP
Ypsilanti 330000 State of Michigan SWEEP

Rotavirus Test Positivity Data

Source: https://www.cdc.gov/surveillance/nrevss/rsv/hhsregion.html

RSV Hospitalization Data

Source: https://data.cdc.gov/Case-Surveillance/Weekly-Rates-of-Laboratory-Confirmed-RSV-Hospitali/29hc-w46k

Google Trend Analytics

Google Trend information is pulled periodically as a potential correlate of disease occurrence.

This information is presented at a weekly, state-wide level only. The organism specific search terms used are:

Influenza A “flu symptoms”, “influenza”, “flu”, “influenza symptoms”

Mpox “mpox symptoms”, “mpox”, “monkeypox symptoms”, “monkeypox”

Norovirus “norovirus symptoms”, “norovirus”, “stomach flu”, “stomach flu symptoms”

RSV “rsv symptoms”, “rsv”

SARS-CoV-2 “covid”, “covid symptoms”


Influent Methods


We use the following methods to extract, concentrate, and quantify SARS-CoV-2 in wastewater.

  • Extraction and Concentration

  • Quantification

  • Influent Methodology from Flood, M. T., D’Souza, N., Rose, J. B., & Aw, T. G. (2021). Methods evaluation for rapid concentration and quantification of SARS-CoV-2 in raw wastewater using droplet digital and quantitative RT-PCR. Food and environmental virology, 13(3), 303-315. (with modifications)

Norovirus and Rotavirus

Norovirus GII and Rotavirus species A are detected using influent samples prepared using the method described above, but with the primers from the following papers.

  • For Norovirus GII: Kageyama, Tsutomu, et al. “Broadly reactive and highly sensitive assay for Norwalk-like viruses based on real-time quantitative reverse transcription-PCR.” Journal of Clinical Microbiology 41.4 (2003): 1548-1557.
  • For Rotavirus: Zeng, S-Q., et al. “One-step quantitative RT-PCR for the detection of rotavirus in acute gastroenteritis.” Journal of Virological Methods 153.2 (2008): 238-240.

Further information regarding norovirus GII monitoring is available online: https://doi.org/10.1101/2023.04.10.23288357

Solids Methods

Extraction from settled solids is used to detect RSV, IFA, and Mpox. The method for sample processing is described in the paper below. Kim, Sooyeol, et al. “SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works.” Environmental science: water research & technology 8.4 (2022): 757-770.

The primers used for IFA, RSV, and Mpox are from the following papers.

  • Wolfe, Marlene K., et al. “Wastewater-based detection of two influenza outbreaks.” Environmental Science & Technology Letters 9.8 (2022): 687-692.

  • Hughes, Bridgette, et al. “Respiratory syncytial virus (RSV) RNA in wastewater settled solids reflects RSV clinical positivity rates.” Environmental Science & Technology Letters 9.2 (2022): 173-178.

  • Wolfe, Marlene K., et al. “Use of Wastewater for Mpox Outbreak Surveillance in California.” New England Journal of Medicine (2023).

History of Application Changes

Record of the changes made to this dashboard (history starting March 2023).

17 March 2023

  • In reference to wastewater sample measurements, instances of “Seven/Fourteen Day” corrected to “Seven/Fourteen Sample” to better reflect the reality of sampling and calculation.
  • Updated About Page formatting to include multiple tabs for improved organization of information.

21 March 2023

  • Influenza A, RSV, and Mpox solid sample PMMoV-normalized data views added to the “Pathogens” tab
  • Google Trend search views for RSV, Influenza A, Norovirus, Mpox, and SARS-CoV-2 search terms were added to the “Pathogens” tab
  • Influenza A, RSV, and Mpox options added to landing page Trend tables

27 March 2023

  • Website title header changed from “Wastewater Sampling by the Wigginton-Eisenberg Research Group at the University of Michigan” to “Community Level Wastewater Monitoring by UM”

28 March 2023

  • Additional team member lab and research group websites added to the Dashboard About Page sidebar.

31 May 2023

  • Original landing page was moved to “Additional Views” > “Trends & Comparison” and replaced with a heat map grid view of all organisms and testing locations as a “Home” page.

19 June 2023

  • Buttons added to the bottom of the heat map grid view on the “Home” page. These buttons allow for quick navigation to the stated organism’s full “Pathogen” page.

27 June 2023

  • Rotavirus influent sample PMMoV-normalized data view added to the “Pathogens” tab
  • Norovirus & Rotavirus laboratory technique section of About Page updated

17 July 2023

  • “Days in Decline” definition and description expanded in About Page

9 August 2023

  • Aesthetic design and color changes made to entire site

11 August 2023

  • Landing page grid had rotavirus added, and new capability to switch between levels determined by quantile or clinical correlations.
  • Landing page panel with level information moved to About page.

15 August 2023

  • Feedback request banner added to landing page.

16 August 2023

  • Option to switch between viewing the 3-sample average line and the 7-sample average line on Influenza A, Norovirus, RSV, and SARS-CoV-2 added to each organism’s scatterplot page.
  • Level view lines (Quartile and/or Clinical Correlation) on Influenza A, Norovirus, Rotavirus, RSV, and SARS-CoV-2 added to each organism’s scatterplot page.
  • Downloadable SARS-CoV-2 Risk Cards made available on landing page.

5 September 2023

  • Header case/hospitalization labels added to Landing Page grid blocks.
  • Pathogen > Influenza A tab: Clinical Correlation and Quartile Level Legends were added to the sidebar, the default landing view of the chart displays the Clinical Correlation levels, and there is now the ability to control the y-axis maximum of the chart.
  • Pathogen > SARS-CoV-2 tab: Clinical Correlation and Quartile Level Legends were added to the sidebar and the default landing view of the chart displays the Clinical Correlation levels.
  • Pathogen > RSV tab: Midwest Region RSV hospitalization data from the CDC was added to the case comparison chart.
  • Pathogen > Rotavirus tab: Midwest Region Rotavirus test positivity data from the CDC was added to the case comparison chart.

5 September 2023

  • X-Axis date labels edited to the same format (ex. Apr ’23) across all charts under the Pathogen table.

About Testing Wastewater for Viruses & Bacteria

Pathogenic microorganisms that infect humans are commonly shed in feces, urine, saliva, and skin. The shed organisms can eventually end up in municipal wastewater, where they can be detected and quantified. Such measurements can provide helpful information for public health officials regarding community health.

History and Methods

In the 1960s, epidemiologists began using wastewater to track and contain polio outbreaks. These early efforts relied on culture-based methods to detect polioviruses in the wastewater. In the 1980s, Hepatitis A was monitored in wastewater using hybridization techniques with radioactive cDNA probes. Broader wastewater pathogen detection techniques began in the 1990s with the advent of polymerase chain reaction (PCR) technology. PCR-based methods have been widely used for SARS-CoV-2 surveillance.


  • Normalizing the sample - Human inputs within a single community’s wastewater can be diluted during stormwater events or other changes in wastewater inputs. Likewise, comparing pathogen concentrations in the wastewaters between different community sewersheds can be complicated by different wasteawter compositions, such as the amount and types of industries in the sewershed. Normalizing ultimately helps account for the number of individuals that contribute to the wastewater sample and thus facilitates comparing organism concentrations measured over time in the same sewershed and between sewersheds. Potential normalization factors include concentrations of of Pepper Mild Mottle virus, crAssphage, Bacteroides HF183, or Lachnospiraceae Lachno3 in the wasteawter. Normalizing by wastewater flow rate and sewershed population, as well as chemical concentrations, have also been proposed.

  • Sample collection method and frequency - Wastewater collected as a grab sample represents a single point in time, whereas composite samples represent wastewater levels over a specified period of time (often 24 hours). Sample collection frequency can affect the ability to observe trends in wastewater–samples collected and analyzed at a higher frequency (e.g., daily samples) provide more information on disease dynamics in a community than samples collected and analyzed at a lower frequency collection (e.g, weekly samples).

  • The laboratory detection method used - Methods used to quantify organisms in wastewater can be culture-based or molecular-based. Culture-based methods require a live, or infectious organism to be detected and quantified. PCR-based methods require the targeted regions of the genome to be intact so that they can be detected and quantified. PCR methods do not relay information about the infectiou state of the organism, but they are relatively quick and specific. With PCR-based methods, pathogen wastewater concentrations can be measured and reported within 1-2 days of when the organisms were shed. Different methods have different limits of detection.

  • The persistence of the organism in the environment - The temperature of the environment, along with the presence of other chemicals and organisms in the environment, may impact the amount of the infectious/live organism or its genome that can be detected.

  • Wastewater-based epidemiology methods have detection limits that depend on the amount of organisms people shed during an infection and the methods used to recover and detect the organism.

SARS-CoV-2 in Wastewater

SARS-CoV-2, or the virus that causes COVID-19, is shed in stool during infections. We can therefore quantify SARS-CoV-2 RNA in wastewater to get a sense of a community’s COVID-19 burden. Most efforts to quantify SARS-CoV-2 concentrations in wastewater focus on the liquid fraction of wastewater. Methods have also been developed to measure SARS-CoV-2 RNA in the solid fractions of wastewater and there is evidence that solids fractions contain higher concentrations of SARS-CoV-2 than the liquid fraction (see links below). Focusing on solids can therefore improve detection limits. Although our team currently measures SARS-CoV-2 in liquid influent samples, we plan to incorporate solids measurements in the future.


Additional Wastewater Dashboards