Building New York State’s Wastewater Surveillance Network

This entry is part 4 of 11 in the series Nov 2023

We built New York State’s wastewater surveillance network to empower local health departments to respond to emerging public health threats.

We were largely unprepared for the COVID-19 pandemic, at least in terms of our infectious disease surveillance systems. In those early months of the year 2020 we relied on increasing hospitalizations as the primary indication that COVID-19 transmission was spreading. Wuhan, the Lombardi region of Italy, and New York City were overwhelmed early. Diagnostic tests helped to inform us of the threat once they became more widely available, but it was already too late to control the outbreak. A pandemic was upon us, and a wide shutdown was inevitable. We had to stop the spread and flatten the curve. In our newly published work, “Establishing a Statewide Wastewater Surveillance System in Response to the COVID-19 Pandemic: A Reliable Model for Continuous and Emerging Public Health Threats,” we outline the development and operation of the New York State Wastewater Surveillance Network which grew out of a response to COVID-19.

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Wastewater had long been known to be a useful tool in polio surveillance, but polio is a fecal-oral transmitted pathogen and is expected to be found in wastewater. The majority of epidemiologists did not think to look in wastewater for a respiratory-transmitted pathogen such as COVID-19. That all changed in March of 2020 when a tweet from Dutch scientists confirmed that SARS-CoV-2 could be found in wastewater.

Wastewater surveillance is advantageous for two primary reasons. First, everybody poops. In contrast, not everybody becomes symptomatic, not everyone seeks treatment for their symptoms, not everyone gets tested if they do seek treatment, and not every test gets reported into an infectious disease surveillance system. Wastewater is more inclusive and therefore more representative of trends in infectious disease transmission. Second, wastewater treatment plants provide a convenient and low-cost method of collecting a community-representative sample. Wastewater treatment plants test their influent wastewater regularly, up to twice per week depending upon the size of the treatment plant in New York State. So if the treatment plant is already collecting the sample, we can add one more additional test to better understand trends in infectious disease transmission. With wastewater, we are able to cost-effectively estimate trends in infectious disease transmission and communicate infectious disease risk over broad geographic areas.

We began establishing the New York State wastewater surveillance network in May of 2020. Our primary goal was to build a system to support local county health departments in their understanding of COVID-19 transmission. To that end, we sought at least one wastewater treatment plant in every county. We also wanted as much population coverage as possible. New York State has more than 600 municipal treatment plants, but just 200 of those serve 95% of the population connected to municipal sewers. We were able to scale to these 200 wastewater treatment plants permitted to discharge at least 1 million gallons per day. Wastewater treatment plant operators pull the samples and send the samples to participating laboratories for SARS-CoV-2 testing. Once analyzed, the data are sent to Syracuse University for processing and reporting. Within 3 days of sampling the majority of data are up on the public-facing dashboard, and every week our epidemiologists return a memo to the local health departments and participating wastewater treatment plants outlining the inference gained from the most recent wastewater testing result.

The feedback loop of the data interpretation to the local health departments is incredibly important. The local health departments are charged with responding to infectious disease threats – they more than any other civil society organization need support in that regard. In our publication “Establishing a Statewide Wastewater Surveillance System in Response to the COVID-19 Pandemic: A Reliable Model for Continuous and Emerging Public Health Threats,” we outline how we are training them to interpret and use wastewater surveillance data. With these tools established and the ongoing training, we will be better prepared for the next emerging pathogen or pandemic threat, at least in terms of our infectious disease surveillance.

Other Study Authors 

Mila Neyra, MPH, is project director of the NYS Wastewater Surveillance Network at Syracuse University. She earned an MPH from Johns Hopkins Bloomberg School of Public Health and was recently awarded the Network of Practice grant by the Bloomberg American Health Initiative to continue her work in population surveillance and racial/health equity.

Dustin T. Hill, PhD, is an environmental scientist and completed his PhD at SUNY ESF with research focusing on environmental health through the lens of spatial exposures to air pollution. Dustin has contributed to the fields of air pollution metals exposure in children, and spatial modelling of infectious diseases using wastewater surveillance data.

Christopher N. Dunham, MS, is an assistant teaching professor at Syracuse University’s School of Information Studies. In addition to teaching courses in big data analytics and deep learning, Chris is a data scientist with the New York State Wastewater Surveillance Network. He earned an MS in Economics from SUNY at Buffalo.

Lydia Bennett served as an epidemiologist in the scale-up of the New York State Wastewater Surveillance network. She is now pursuing a physician assistant degree.

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