Update: April 2024
We are no longer reporting COVID-19 case data on this dashboard. Case data for COVID-19 are still being reported by New York State Department of health at New York's COVID tracker website. We are now reporting in-patient COVID-19 hospitalizations instead. Hospitalizations have been shown to correlate well with wastewater levels of SARS-CoV-2 and are a better indicator of the overall burden of disease COVID-19 presents for a community.
Welcome to the dashboard for the NYS Wastewater Surveillance Network
The NYS Wastewater Surveillance Network is a collaboration between Syracuse University, SUNY-ESF, University at Buffalo - SUNY, Stony Brook University, Upstate Medical University, NYS Department of Health, and NYS Department of Environmental Conservation. This website is where all the wastewater surveillance data collected by participating counties is reported. You can view data in the interactive map and graphs below for all current and past participants. Additional information is available in the information tab on the left sidebar.
Updates to data
Erie county historical data (2020 and 2021) are available on the Erie County Dashboard. The New York State Network is in the process of adding data from all participating counties in both the state program and the CDC national program to this dashboard. Data are added as they are received. CDC data undergoes different data processing and trends displayed on the national dashboard might differ from trends displayed here.
Note: Trends for New York City and the counties Genesee, Orleans, and Suffolk are based on the natural log of raw gene copies.
First time visiting the dashboard? A dashboard tutorial is now available online. Please follow this link to watch a demonstration and learn more about how to use the interactive figures. Also, we have a document that explains the steps of how to use the features on this page and navigate the dashboard interactive content. Dashboard Tutorial . (A PDF will open for you to view).
Statewide summary
62
Participating counties
173
WWTPs with recent data 1
15,374,303
Population covered
438
Samples collected last 15 days 2
203
Number of WWTPs enrolled
395
Samples sequenced last 40 days 3
1 Plants actively reported at least one sample between Mar 15, 2024 and Apr 15, 2024
2 Samples collected between Mar 31, 2024 and Apr 15, 2024
3 Sequenced samples were collected between the weeks beginning Feb 20, 2024 and Mar 31, 2024
Last Updated: Apr 18, 2024
Most recent sample: Apr 15, 2024
Map of participating treatment plants and counties
SARS-CoV-2 detection level
SARS-CoV-2 detection level is displayed in three categories: Low, Moderate, and Substantial to High. Current estimated levels are based on the highest detection reported from the most recent three samples. These detection levels have been shown to correlate with estimated community transmission levels. Category change in the last 15 days is calculated by subtracting the current number of sites in each current level category from the number of sites in the same category 15 days earlier and dividing by the number of sites in the same category 15 days earlier. See the Map description for more detailed information.
Two-week trend
To identify how wastewater results are changing over time, trend analysis is conducted on the most recent data. A two-week trend is calculated for each location using all data points within the fifteen previous days of the most recent sample for that location. The trend analysis calculates the average change in the SARS-CoV-2 Intensity over the fifteen-day period using a linear regression. Sites with fewer than two samples within the fifteen-day window appear as NA values. Category change in the last 15 days is calculated by subtracting the current number of sites in each current level category from the number of sites in the same category 15 days earlier and dividing by the number of sites in the same category 15 days earlier. See the Map description for more detailed information.
Genetic sequencing lineage data
Samples with positive SARS-CoV-2 results are genetically sequenced to identify the multiple variants or lineages of SARS-CoV-2 and to estimate the relative proportions of these lineages. Unlike patient samples, wastewater samples contain multiple lineages of SARS-CoV-2. Samples are only sequenced if SARS-CoV-2 is detected and therefore sample results that are Not detected will show up as No SARS-CoV-2 detected on the lineage map. Some samples fail sequencing and these are represented by No sequencing data available. The date range for sequencing data is different than for quantification data because sequencing of viral genomes from wastewater happens at separate laboratories. The most recent data for sequencing are shown for each site.
Map description
Map
NOTE: Results presented here are based on the current state of the science. Understanding regarding the data and science around what different detection values mean is evolving and the correlations may change in the future leading to changes in how wastewater results are categorized.
This dashboard provides trend analysis of the wastewater surveillance being conducted in participating counties in New York State. The detection level of SARS-CoV-2 indicates how much viral RNA was detected in the sample and these detection levels correlate highly with the probability of community transmission based on current understanding of the science. These correlations are based on statistical analysis of wastewater intensity and active case data. The two-week trend indicates the average increase or decrease in the SARS-CoV-2 intensity (the population normalized ratio) detected in wastewater. The statewide map displays the current participating counties as well as those that have participated in the past. To learn more information about SARS CoV-2 detection and trends within a county, select a county in the dropdown menu on the right or zoom in or click on a county on the map.
Zoom in or click to see more detail
Zoom in on the map to see more information or click on a county of interest and the map will zoom into that county's sample sites. You can see what wastewater treatment plants are participating, where they are located, and view trends for each. Zooming in will also display the sewershed boundaries corresponding to the treatment plants. Counties that participated in the past but are not currently reporting surveillance have older data available for review. Zoom in on those counties to see their sample sites and view historical data
SARS-CoV-2 detection level
Detection levels were determined based on statistical correlation between active case thresholds and wastewater detection. Detailed methods and documentation are available here.
Detection levels of SARS-CoV-2 are categorized into groups to reflect community level transmission: high (>50 cases/100,000), moderate (10-50 cases/100,000), and low (<10 cases/ 100,000). Low and moderate transmission categories correspond approximately to laboratory results of non-detections (wastewater intensity = 0) and detections below the limit of quantification (wastewater intensity< .2), respectively. High transmission corresponds to quantifiable detections. As this is an expansive categorical result, we further break the high transmission category into quantiles. The quantiles use all historical data, by method, as we have multiple laboratories analyzing wastewater samples. The historical data computes the quantiles that recent data (again by method) is compared to. This returns a numerical percentile of exactly where the recent data point falls along the historical data set.
Two-week Trend Calculation
To identify how wastewater results are changing over time, trend analysis is conducted on the most recent data. A two-week trend is calculated for each location using all data points within the fifteen previous days of the most recent sample for that location. The trend anlysis calculates the average change in the SARS-CoV-2 Intensity (log of the viral gene copies divided by the log of the fecal indicator) over the fifteen day period using a linear regression. Fifteen days was selected because it contains the most information about recent viral transmission within the community and provides the most up-to-date context for what direction transmission might be going. CDC trend analysis also uses the fifteen day period to calculate trends. If a sample site has fewer than two samples within the fifteen day window, then their trend results will show up as a grey color on the map.
Sequencing Data
Samples with positive SARS-CoV-2 results are genetically sequenced to identify the multiple variants or lineages of SARS-CoV-2 and to estimate the relative proportions of these lineages. Unlike patient samples, wastewater samples contain multiple lineages of SARS-CoV-2. Samples are only sequenced if SARS-CoV-2 is detected and therefore sample results that are Not detected will show up as No SARS-CoV-2 detected on the lineage map. Some samples fail sequencing and these are represented by No sequencing data available.
Wastewater data
Wastewater trend description
Detection trend graph
The first graph displays the change in wastewater detection of SARS-CoV-2 RNA over time. This graph displays the log-transformed ratio of SARS-CoV-2 to human fecal indicator detected. This ratio adjusts the detected values based on population so that lower levels of detection indicate fewer shedding events. As detection levels rise, the trend line will also rise indicating increases in detection.
Intensity ratio of SARS-CoV-2 detected
Recovery of viral fragments of SARS-CoV-2 RNA from wastewater is influenced by many factors that impact the final value measured in the lab including that RNA fragments decay over time in waste. Most samples are turned around in 24 hours limiting these effects, however, to better understand the amount of SARS-CoV-2 detected in wastewater, a ratio is used. This ratio is the natural log of total gene copies of SARS-CoV-2 RNA detected divided by the natural log of total copies of human fecal indicator detected in the sample. The human fecal indicator is constantly shed by humans and works as a measure for the total amount of waste coming into the sewer system. This value is generally stable meaning that it helps compare one SARS-CoV-2 RNA sample to another. Thus, the ratio is a good indicator for how much SARS-CoV-2 virus might be transmitting in the observed community. This ratio is called the Intensity of SARS-CoV-2 detected in wastewater. Current methods being used in New York use two different human fecal indicators. The first is crAssphage DNA, which is a ubiquitous bacteriophage found in most humans. The second is pepper mild mottle virus or PMMoV, which is a common virus found in peppers and excreted in humans.
Gene copies
This plot shows the average number of gene copies (units are copies per milliliter) detected in each sample of wastewater. These values are not normalized by population but do show general trend information. For some counties and jurisdictions, the natural log of gene copies is used to determine the two-week trend instead of intensity. The natural log of gene copies was found to correlate best with case data and new COVID-19 hospitalizations, and is suitable for sampling sites that do not collect fecal indicator data. One benefit of reporting gene copies is that detection levels can be grouped based on three categories. When no gene copies are detected, this is known as a non-detect so it is classified as Not detected.
Sometimes, labs detect SARS CoV-2 viral fragments, but levels are too low to quantify how much is in the wastewater. These readings indicate that there is SARS-CoV-2 RNA in the wastewater, but it is at a lower level indicating fewer infections in the community that is connected to the sewer system. This is known as a detection below the limit of quantification or detected, <LOQ.
When labs detect SARS-CoV-2 RNA fragments and can quantify the values, this is known as a quantifiable detection. This indicates higher levels of SARS-CoV-2 RNA in wastewater and greater infections in the community linked to that sewer system.
Sequencing Data
Samples with positive SARS-CoV-2 results are genetically sequenced to identify the multiple variants or lineages of SARS-CoV-2 and to estimate the relative proportions of these lineages. Unlike patient samples, wastewater samples contain multiple lineages of SARS-CoV-2. Samples are only sequenced if SARS-CoV-2 is detected and therefore sample results that are Not detected will show up as No SARS-CoV-2 detected on the lineage map. Some samples fail sequencing and these are represented by No sequencing data available.
Sometimes sequencing of the viral genome from the wastewater sample fails. If quantifiable virus was detected, but the sequence fails, these samples are described as No sequencing data available
Toggle between the intensity plot, gene copies, and sequencing data using the buttons on the left sidebar.
There are two aggregations for sequencing data. Aggregation 1 (NWSS groupings) is based on the US CDC NWSS lineage aggregations for SARS-CoV-2 wastewater data. Aggregation 2 (clinical groupings) is based on the NYS DOH lineage aggregations NYS DOH lineage aggregations for SARS-CoV-2 clinical data. Both datasets represent wastewater results from the same sample in two different grouping methods. The second aggregation is intended to ease comparison of wastewater sequencing data, presented on this dashboard, with publicly reported clinical sequencing data reported by NYS DOH.
Download data from NY DOH website.
COVID-19 hospitalization data
Hospitalizations plot description
Hospitalization graphs
New COVID-19 hospitalization data are downloaded from the NYS Department of Health website and displayed at the regional level. New hospital admissions are in-patient only and include all newly reported COVID-19 hospitalizations on that day.
You can change the graph to show the total number hopsitalized or new admissions using the toggle buttons on the left sidebar.
Key terms
Intensity of SARS CoV-2 RNA in wastewater - the natural log-adjusted ratio of SARS-CoV-2 RNA copies detected to total human fecal indicator detected.
Natural log of raw gene copies - SARS-CoV-2 RNA copies are natural log transformed to provide a more linear fit to the data for calculating trends over time.
Sewershed - a term used to refer to the service area of a treatment plant. Sewersheds can represent the entire service area for a plant or a portion of the service area. These smaller portions are sometimes called catchments and represent sampling at manholes or pump stations before the influent reaches the primary treatment facility.
crAssphage - bacteriophage commonly excreted from humans which is used to determine the relative level of SARS-CoV-2 RNA in the wastewater. The ratio of crAssphage to SARS-CoV-2 helps estimate if there is small amount of SARS-CoV-2 or if detection levels indicate greater infection in the population. It is one of the fecal indicators used to normalize data and calculate the intensity value.
PMMoV - pepper mild mottle virus - common virus found in peppers that is excreted in human waste. It is one of the human fecal indicators used to normalize wastewater sample results to adjust for different population sizes.
WWTP - wastewater treatment plant
Variant - A variant is a viral genome (genetic code) that may contain one or more mutations.
Lineage - A lineage is a group of closely related viruses with a common ancestor. SARS-CoV-2 has many lineages; all cause COVID-19.
Wastewater surveillance toolkit
The links below are to documents that Local Health Departments (LHDs) might find useful for understanding and communicating wastewater results. These documents are meant to supplement existing forms of communication between LHDs and communities and not replace current methods.
Sample press release
Who to inform
Suggested social media posts
FAQs
This table displays all of the current variants of concern, of interest, or under monitoring that have been detected anywhere in New York State in wastewater in the most recent 4 and 6 weeks of wastewater data. Variants of concern are listed by either the US Centers for Disease Control (CDC) or the World Health Organization (WHO). Variants of concern have some biological significance in their genetic structure that makes them of interest for public health officials to monitor.
Variants of concern are tracked if they are listed in the U.S. CDC Nowcast table or the World Health Organization (WHO) list.
Project description
The SARS-CoV-2 early warning wastewater surveillance platform began in early March of 2020. Participating counties and wastewater treatment plants provide wastewater samples weekly or semi-weekly (two to three times per week). Lab analyses are caried out at partner organizations, several of which are listed below. Trends and maps are created using the results of surveillance to help guide response to the coronavirus pandemic. In addition, trends can help inform public health actions that can be taken to protect communities where increased transmission is detected and when transmission is declining or very low.
Methods
Trend calculations
Wastewater data are normalized for fluctuations in human fecal content contribution. Two human fecal indicators are used: crAssphage and PMMoV. The specific fecal indicator measured for the sample varies based on the lab analyzing the sample. The ratio of SARS CoV-2 RNA to human fecal indicator is a unitless ratio indicating the intensity of coronavirus gene copies detected in the wastewater. Higher values indicate higher viral load and potentially higher transmission in the community that the sample is from. Trend plots use natural log-adjusted values for this intensity metric to reduce the influence of large spikes or declines in detection due to things like high intensity rain events that can make accurate detection difficult. Single samples show a snapshot in time for the level of coronavirus detected in wastewater, while several data points over time provide indicators of viral trends in a community. This dashboard provides two-week trend metrics to display if viral detection is increasing or decreasing by comparing samples taken over a fourteen-day window.
For some counties and jurisdictions, the natural log of gene copies is used to determine the two-week trend instead of intensity. The natural log of gene copies was found to correlate best with lab-confirmed case data and is suitable for sampling sites that do not collect fecal indicator data. Current sites using this method are in Genesee, Orleans, Allegany, and Suffolk Counties as well as New York City.
Comparing these trends to the observed case data is useful for confirming trends seen among clinical case data and provides additional information about viral transmission in communities. Wastewater samples are an excellent supplement to clinical testing and provide additional information about large populations quickly to understand and track the spread of COVID-19.
Dashboard
This dashboard was created in R version 4.1.1 using the R Shiny package. Additional packages include shinydashboard, sf, dplyr, lubridate, tigris, rgdal, leaflet, ggplot2, htmlwidgets, htmltools, leaflet.extras, tidyr, scales, plotly, shinyBS, magrittr, and stringr. Documentation for these packages is available online.
Detection level calculations
Note on change from community transmission language to detection level In March of 2022, we began reporting correlations between levels in wastewater and probability of community transmission. The label for this set of categories was updated in May 2022 to reflect the current state of the science and understanding of what different detection levels mean related to estimated case counts. The previous levels remain valid; however, it is more accurate to report the metric as detection level of SARS-CoV-2 RNA in the wastewater since that is what is being measured. Low, Moderate, and Substantial to High levels of SARS-CoV-2 in the wastewater correlate with estimated levels of community transmission and active case counts within the community contributing wastewater to the sample site. The new levels are:
TRUE
Detection levels were determined based on statistical correlation between active case thresholds and wastewater detection. Detailed methods and documentation are available here. The figure below provides a visual representation of correlations between case thresholds and each detection level used.
Detection levels of SARS-CoV-2 are categorized into groups to reflect community level transmission: high (>50 cases/100,000), moderate (10-50 cases/100,000), and low (<10 cases/ 100,000). Low and moderate transmission categories correspond approximately to laboratory results of non-detections (wastewater intensity = 0) and detections below the limit of quantification (wastewater intensity< .2), respectively. High transmission corresponds to quantifiable detections. As this is an expansive categorical result, we further break the high transmission category into quantiles. The quantiles use all historical data, by method, as we have multiple laboratories analyzing wastewater samples. The historical data computes the quantiles that recent data (again by method) is compared to. This returns a numerical percentile of exactly where the recent data point falls along the historical data set.
COVID-19 Incidence and Detection Levels Figure: Estimates of the limits of detection (in terms of cases reported in the health system) of SARS-CoV-2 testing in wastewater relative to classification of transmission risk. Clear differentiation in the level of measured community-level COVID-19 incidence when categorizing wastewater results as quantifiable, detected but below the level of quantification, and not detected. Size of the circles represents the number of individuals tested. Nondetection of SARS-CoV-2 RNA clusters around < 10 cases per 100,000.
Data
NOTE Erie county data are available on the Erie County Dashboard. The New York State Network is in the process of adding data from all participating counties in both the state program and the CDC national program to this dashboard. Data are added as they are received. CDC data undergoes different data processing and trends displayed on the national dashboard might differ from trends displayed here.
Access data for SARS-CoV-2 wastewater quantification here.
Access SARS-CoV-2 wastewater variant data here.
Download data from NY DOH website.
NOTE Data from wastewater treatment plants or sewersheds of population < 3,000 are not reported on this dashboard.
Wastewater samples are collected at participating treatment plants usually at influent points where the pipes run into the treatment plant.
Wastewater data download
Wastewater data for New York are available to download at health.data.ny.gov
Notes on lab methods
Labs that are contributing wastewater results in New York State use different methods. Comparison of data between and across sites analyzed by different labs may not correlate and is not recommend particularly for raw gene copies. If a method changes at the lab analyzing that site, past data may also not correlate.
Quadrant Biosciences
Quadrant biosciences is analyzing wastewater samples for most New York State counties. The limit of quantification for Quadrant's analysis method is 5 gene copies per milliliter.
University at Buffalo - SUNY
UB-SUNY is analyzing wastewater samples for most of the Western Region of NYS. The limit of quantification for the method used by UB-SUNY is 1 gene copy per milliliter. UB-SUNY changed their methods to magnetic bead processing the week of April 17, 2022. It is recommended that data not be compared before and after this time point for UB-SUNY sites. This is noted on the gene copies plot for those locations (e.g., Erie County WWTPs).
Stony Brook University
Stony Brook is analyzing wastewater samples for Suffolk and Nassau Counties.
Genesee and Orleans County Public Health Department
Genesee and Orleaans County data are analyzed by Genesee and Orleans County Public Health Department.
New York City
Data for New York City's five boroughs are analyzed by the City Health Department. Real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used for SARS-CoV-2 N1 gene copy determinations for samples collected August 31, 2020-March 7, 2023. Starting with samples collected on March 12,2023, digital reverse transcription quantitative polymerase chain reaction (dPCR) has been used. Due to differences in methodology, dPCR viral load values are ~10-20 times higher than RT-qPCR values. Therefore, increases in viral load between March 7th, 2023, and March 12, 2023 are due in part to changes in methods. The method change is noted on the raw gene copy plots for NYC sites with a hashed line on March 12, 2023.
New York City data are reported weekly. For more information on methods used for SARS-CoV-2 detection in New York City, please visit this website. For access to New York City historical data, please visit: this website.
Genetic Sequencing Methods and Data
Samples with positive SARS-CoV-2 results are genetically sequenced to identify the multiple variants or lineages of SARS-CoV-2 and to estimate the relative proportions of these lineages. Unlike patient samples, wastewater samples contain multiple lineages of SARS-CoV-2. Because of this complexity, the sequence data is analyzed by a lineage decomposition mixture model to assess the different lineages that make up the sample and the relative proportions of these lineages. These samples are distributed to the NYS SARS-CoV-2 Genetic Sequencing Laboratory Consortium, which consists of the NYSDOH Wadsworth Center and four contracted academic laboratories: New York Medical Center, SUNY Upstate, University at Buffalo SUNY, and University of Rochester. Following sequencing, whole-genome sequence data files are sent to Syracuse University for data interpretation and dissemination.
Why is there a difference in the dates for sequencing data from the SARS-CoV-2 concentration data?
Samples are taken at each WWTP at different times during the week then sent to a laboratory for extraction and quantification of viral particles in the sample. Quantification data are the first results available and usually available in 1 to 4 days after the sample is collected. These data are added to the dashboard as soon as they are available. Sequencing data takes longer to generate results because the sample extracts are sent to different laboratories around the state for viral genome sequencing of SARS-CoV-2. The shipping time is 1 to 2 days, but then the samples need to be sequenced and then uploaded and processed. The typical lag time for sequencing data is a total of 7 to 14 days, however it can take longer if there are unexpected delays anywhere along the way. Data for quantification of SARS-CoV-2 and data for sequencing will therefore have different dates for what is considered most recent for the location. The most recent data available will always be displayed for each location.
Hospitalization data
COVID-19 hospital admissions data can be obtained from New York State Department of Health website. Hospitalizations data are from the HERDS or Health Electronic Response System data. These data are reported at the facility level and then aggregated to the region level. Hospital admissions are inclusive of individuals that are admitted to the hosptial for in-patient services due to COVID-19.
Case data
COVID-19 Case data can be obtained from New York State Department of Health. Please note that COVID-19 case data are still reported at the county level but we no longer display case data on our wastewater dashboard as of December 2023.
Spatial data
Sewershed boundaries are created from several sources including physical maps provided by treatment plant operators, existing GIS data from participants, and digitized using NYS parcel data. Boundaries indicated the estimated service area for the treatment plant providing information on the community represented by each wastewater sample.
Treatment plant locations are from the NYS GIS data clearinghouse and available here.
Partners
- New York State Department of Health
- New York State Department of Environmental Conservation
- Syracuse University
- SUNY ESF
- SUNY Upstate Medical University
- Quadrant Biosciences
- University at Buffalo - SUNY
- Stony Brook University
- Genesee and Orleans County Public Health Department
- CDC National Wastewater Surveillance System
Genetic Sequencing Labortories
- University at Buffalo
- New York Medical Center
- University of Rochester
- SUNY Upstate Medical University
- Wadsworth Center NYSDOH
Dashboard design and analysis contributors
- David Larsen, Department of Public Health, Syracuse University: Supervision, method development, data analysis
- Hyatt Green, Department of Environmental and Forest Biology, SUNY-ESF: Method development, data analysis
- Dustin Hill, Department of Public Health, Syracuse University: Web development, data analysis, data visualization
- Mary Collins, Department of Environmental Studies, Center for Environmental Medicine and Informatics, SUNY-ESF: Web development, data visualization
- Christopher Dunham, Director Research & Decision Support, Syracuse University: Web development, data management, quality assurance.
Contact us
For questions about wastewater data and results, contact Dr. David Larsen at dalarsen@syr.edu
For bug reports and issues with the dashboard, contact Dr. Dustin Hill at dthill@syr.edu