TY - JOUR
T1 - Longitudinal monitoring of SARS-CoV-2 in wastewater using viral genetic markers and the estimation of unconfirmed COVID-19 cases
AU - Li, Lin
AU - Mazurowski, Lauren
AU - Dewan, Aimee
AU - Carine, Madeline
AU - Haak, Laura
AU - Guarin, Tatiana C.
AU - Dastjerdi, Niloufar Gharoon
AU - Gerrity, Daniel
AU - Mentzer, Casey
AU - Pagilla, Krishna R.
N1 - Funding Information:
This study has been funded by the City of Sparks, NV, USA, with funds from CARES Act and American Rescue Plan of the US Department of Treasury. John Martini, Michael Drinkwater from the City of Sparks, and collaborating partners from the City of Reno, Washoe County, and Washoe County Health District are gratefully acknowledged for their support and access to facilities/data to conduct this research. The authors are thankful to Dr. Subhash Verma and Dr. Timsy Uppal of the University of Nevada School of Medicine for their help in conducting the virus recovery studies. The authors have no Conflict of Interest in this research or the manuscript.
Funding Information:
This study has been funded by the City of Sparks, NV, USA, with funds from CARES Act and American Rescue Plan of the US Department of Treasury. John Martini, Michael Drinkwater from the City of Sparks, and collaborating partners from the City of Reno, Washoe County, and Washoe County Health District are gratefully acknowledged for their support and access to facilities/data to conduct this research. The authors are thankful to Dr. Subhash Verma and Dr. Timsy Uppal of the University of Nevada School of Medicine for their help in conducting the virus recovery studies. The authors have no Conflict of Interest in this research or the manuscript. This work was supported by the City of Sparks, Nevada, utilizing United States Treasury Coronavirus Aid, Relief, and Economic Security (CARES) Appropriations [grant number GR 11493, University of Nevada, Reno] and American Rescue Plan (grant number GR 13942) to the University of Nevada, Reno's Nevada Water Innovation Institute.
Funding Information:
This work was supported by the City of Sparks, Nevada , utilizing United States Treasury Coronavirus Aid, Relief, and Economic Security (CARES) Appropriations [grant number GR 11493 , University of Nevada, Reno ] and American Rescue Plan (grant number GR 13942 ) to the University of Nevada, Reno 's Nevada Water Innovation Institute.
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/4/15
Y1 - 2022/4/15
N2 - In this study, wastewater-based surveillance was carried out to establish the correlation between SARS-CoV-2 viral RNA concentrations in wastewater and the incidence of corona virus disease 2019 (COVID-19) from clinical testing. The influent wastewater of three major water reclamation facilities (WRFs) in Northern Nevada, serving a population of 390,750, was monitored for SARS-CoV-2 viral RNA gene markers, N1 and N2, from June 2020 through September 2021. A total of 614 samples were collected and analyzed. The SARS-CoV-2 concentrations in wastewater were observed to peak twice during the study period. A moderate correlation trend between coronavirus disease 2019 (COVID-19) incidence data from clinical testing and SARS-CoV-2 viral RNA concentrations in wastewater was observed (Spearman r = 0.533). This correlation improved when using weekly average SARS-CoV-2 marker concentrations of wastewater and clinical case data (Spearman r = 0.790), presumably by mitigating the inherent variability of the environmental dataset and the effects of clinical testing artifacts (e.g., reporting lags). The research also demonstrated the value of wastewater-based surveillance as an early warning signal for early detection of trends in COVID-19 incidence. This was accomplished by identifying that the reported clinical cases had a stronger correlation to SARS-CoV-2 wastewater monitoring data when they were estimated to lag 7-days behind the wastewater data. The results aided local decision makers in developing strategies to manage COVID-19 in the region and provide a framework for how wastewater-based surveillance can be applied across localities to enhance the public health monitoring of the ongoing pandemic.
AB - In this study, wastewater-based surveillance was carried out to establish the correlation between SARS-CoV-2 viral RNA concentrations in wastewater and the incidence of corona virus disease 2019 (COVID-19) from clinical testing. The influent wastewater of three major water reclamation facilities (WRFs) in Northern Nevada, serving a population of 390,750, was monitored for SARS-CoV-2 viral RNA gene markers, N1 and N2, from June 2020 through September 2021. A total of 614 samples were collected and analyzed. The SARS-CoV-2 concentrations in wastewater were observed to peak twice during the study period. A moderate correlation trend between coronavirus disease 2019 (COVID-19) incidence data from clinical testing and SARS-CoV-2 viral RNA concentrations in wastewater was observed (Spearman r = 0.533). This correlation improved when using weekly average SARS-CoV-2 marker concentrations of wastewater and clinical case data (Spearman r = 0.790), presumably by mitigating the inherent variability of the environmental dataset and the effects of clinical testing artifacts (e.g., reporting lags). The research also demonstrated the value of wastewater-based surveillance as an early warning signal for early detection of trends in COVID-19 incidence. This was accomplished by identifying that the reported clinical cases had a stronger correlation to SARS-CoV-2 wastewater monitoring data when they were estimated to lag 7-days behind the wastewater data. The results aided local decision makers in developing strategies to manage COVID-19 in the region and provide a framework for how wastewater-based surveillance can be applied across localities to enhance the public health monitoring of the ongoing pandemic.
KW - COVID-19
KW - Early warning
KW - Long-term monitoring
KW - SARS-CoV-2
KW - Wastewater
UR - http://www.scopus.com/inward/record.url?scp=85122687271&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2022.152958
DO - 10.1016/j.scitotenv.2022.152958
M3 - Artículo Científico
C2 - 35016937
AN - SCOPUS:85122687271
SN - 0048-9697
VL - 817
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 152958
ER -
