TY - JOUR
T1 - Monitoring SARS-CoV-2 in wastewater during New York City's second wave of COVID-19
T2 - sewershed-level trends and relationships to publicly available clinical testing data
AU - Hoar, Catherine
AU - Chauvin, Francoise
AU - Clare, Alexander
AU - McGibbon, Hope
AU - Castro, Esmeraldo
AU - Patinella, Samantha
AU - Katehis, Dimitrios
AU - Dennehy, John J.
AU - Trujillo, Monica
AU - Smyth, Davida S.
AU - Silverman, Andrea I.
N1 - Funding Information:
Funding for this work was provided by the New York City Department of Environmental Protection and the Alfred P. Sloan Foundation. An extensive team at the NYC DEP made this monitoring program possible, including Samantha MacBride, Peter Williamsen, Gina Behnke, Jasmin Torres, and Jorge Villacis; members of the NYC DEP Microbiology Lab, including William Kelly, Naudet Joasil, Patrick Hoyes, Donnovan Johnson, Manzura Kopusov, Oren Sachs, and Samantha Cruickshank; the NYC DEP transportation team, including Lateef Franklin, Samuel Young, and John Congemi; and Abeba Negatu, Patrick Jagessar, Max Verastegui and their process control laboratory teams at NYC DEP. Several researchers at CUNY provided support and assistance for protocol development, optimization, and training, including Sherin Kannoly, Kaung Myat “Zach” San, Kristen Cheung, Anna Gao, Michelle Markman, Nanami Kubota, and Irene Hoxie. We thank Vikram Kapoor, Associate Professor in the Department of Civil and Environmental Engineering at the University of Texas San Antonio, and the Kapoor Lab for generously quantifying the synthetic RNA control using RT-ddPCR. We thank Professors Alexandria Boehm (Stanford University) and Sandra McLellan (University of Wisconsin-Milwaukee) for their support and guidance during program development. We also acknowledge the many insights gained from the interactions through the NSF Research Coordination Network (RCN) on Wastewater Surveillance for SARS-CoV-2. A script automating the download of New York City's publicly available COVID-19 clinical testing data was generously provided by Charlie Mydlarz (NYU Center for Urban Science and Progress). The GIS data used for the NYC sewershed map in the table of contents entry art was retrieved from Open Sewer Atlas NYC.
Funding Information:
Funding for this work was provided by the New York City Department of Environmental Protection and the Alfred P. Sloan Foundation. An extensive team at the NYC DEP made this monitoring program possible, including Samantha MacBride, Peter Williamsen, Gina Behnke, Jasmin Torres, and Jorge Villacis; members of the NYC DEP Microbiology Lab, including William Kelly, Naudet Joasil, Patrick Hoyes, Donnovan Johnson, Manzura Kopusov, Oren Sachs, and Samantha Cruickshank; the NYC DEP transportation team, including Lateef Franklin, Samuel Young, and John Congemi; and Abeba Negatu, Patrick Jagessar, Max Verastegui and their process control laboratory teams at NYC DEP. Several researchers at CUNY provided support and assistance for protocol development, optimization, and training, including Sherin Kannoly, Kaung Myat “Zach” San, Kristen Cheung, Anna Gao, Michelle Markman, Nanami Kubota, and Irene Hoxie. We thank Vikram Kapoor, Associate Professor in the Department of Civil and Environmental Engineering at the University of Texas San Antonio, and the Kapoor Lab for generously quantifying the synthetic RNA control using RT-ddPCR. We thank Professors Alexandria Boehm (Stanford University) and Sandra McLellan (University of Wisconsin-Milwaukee) for their support and guidance during program development. We also acknowledge the many insights gained from the interactions through the NSF Research Coordination Network (RCN) on Wastewater Surveillance for SARS-CoV-2. A script automating the download of New York City's publicly available COVID-19 clinical testing data was generously provided by Charlie Mydlarz (NYU Center for Urban Science and Progress). The GIS data used for the NYC sewershed map in the table of contents entry art was retrieved from Open Sewer Atlas NYC.51
Publisher Copyright:
© 2022 The Royal Society of Chemistry.
PY - 2022/3/16
Y1 - 2022/3/16
N2 - New York City's wastewater monitoring program tracked trends in sewershed-level SARS-CoV-2 loads starting in the fall of 2020, just before the start of the city's second wave of the COVID-19 outbreak. During a five-month study period, from November 8, 2020 to April 11, 2021, viral loads in influent wastewater from each of New York City's 14 wastewater treatment plants were measured and compared to new laboratory-confirmed COVID-19 cases for the populations in each corresponding sewershed, estimated from publicly available clinical testing data. We found significant positive correlations between viral loads in wastewater and new COVID-19 cases. The strength of the correlations varied depending on the sewershed, with Spearman's rank correlation coefficients ranging between 0.38 and 0.81 (mean = 0.55). Based on a linear regression analysis of a combined data set for New York City, we found that a 1 log10 change in the SARS-CoV-2 viral load in wastewater corresponded to a 0.6 log10 change in the number of new laboratory-confirmed COVID-19 cases per day in a sewershed. An estimated minimum detectable case rate between 2-8 cases per day/100 000 people was associated with the method limit of detection in wastewater. This work offers a preliminary assessment of the relationship between wastewater monitoring data and clinical testing data in New York City. While routine monitoring and method optimization continue, information on the development of New York City's wastewater monitoring program may provide insights for similar wastewater-based epidemiology efforts in the future.
AB - New York City's wastewater monitoring program tracked trends in sewershed-level SARS-CoV-2 loads starting in the fall of 2020, just before the start of the city's second wave of the COVID-19 outbreak. During a five-month study period, from November 8, 2020 to April 11, 2021, viral loads in influent wastewater from each of New York City's 14 wastewater treatment plants were measured and compared to new laboratory-confirmed COVID-19 cases for the populations in each corresponding sewershed, estimated from publicly available clinical testing data. We found significant positive correlations between viral loads in wastewater and new COVID-19 cases. The strength of the correlations varied depending on the sewershed, with Spearman's rank correlation coefficients ranging between 0.38 and 0.81 (mean = 0.55). Based on a linear regression analysis of a combined data set for New York City, we found that a 1 log10 change in the SARS-CoV-2 viral load in wastewater corresponded to a 0.6 log10 change in the number of new laboratory-confirmed COVID-19 cases per day in a sewershed. An estimated minimum detectable case rate between 2-8 cases per day/100 000 people was associated with the method limit of detection in wastewater. This work offers a preliminary assessment of the relationship between wastewater monitoring data and clinical testing data in New York City. While routine monitoring and method optimization continue, information on the development of New York City's wastewater monitoring program may provide insights for similar wastewater-based epidemiology efforts in the future.
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U2 - 10.1039/d1ew00747e
DO - 10.1039/d1ew00747e
M3 - Article
AN - SCOPUS:85128150782
VL - 8
SP - 1021
EP - 1035
JO - Environmental Science: Water Research and Technology
JF - Environmental Science: Water Research and Technology
SN - 2053-1400
IS - 5
ER -