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Tools for interpretation of wastewater SARS-CoV-2 temporal and spatial trends demonstrated with data collected in the San Francisco Bay Area

Greenwald, Hannah D. and Kennedy, Lauren C. and Hinkle, Adrian and Whitney, Oscar N. and Fan, Vinson B. and Crits-Christoph, Alexander and Harris-Lovett, Sasha and Flamholz, Avi I. and Al-Shayeb, Basem and Liao, Lauren D. and Beyers, Matt and Brown, Daniel and Chakrabarti, Alicia R. and Dow, Jason and Frost, Dan and Koekemoer, Mark and Lynch, Chris and Sarkar, Payal and White, Eileen and Kantor, Rose and Nelson, Kara L. (2021) Tools for interpretation of wastewater SARS-CoV-2 temporal and spatial trends demonstrated with data collected in the San Francisco Bay Area. Water Research X, 12 . Art. No. 100111. ISSN 2589-9147. PMCID PMC8325558. doi:10.1016/j.wroa.2021.100111.

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Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be integrated with COVID-19 case data to inform timely pandemic response. However, more research is needed to apply and develop systematic methods to interpret the true SARS-CoV-2 signal from noise introduced in wastewater samples (e.g., from sewer conditions, sampling and extraction methods, etc.). In this study, raw wastewater was collected weekly from five sewersheds and one residential facility. The concentrations of SARS-CoV-2 in wastewater samples were compared to geocoded COVID-19 clinical testing data. SARS-CoV-2 was reliably detected (95% positivity) in frozen wastewater samples when reported daily new COVID-19 cases were 2.4 or more per 100,000 people. To adjust for variation in sample fecal content, four normalization biomarkers were evaluated: crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA. Of these, crAssphage displayed the least spatial and temporal variability. Both unnormalized SARS-CoV-2 RNA signal and signal normalized to crAssphage had positive and significant correlation with clinical testing data (Kendall's Tau-b (τ)=0.43 and 0.38, respectively), but no normalization biomarker strengthened the correlation with clinical testing data. Locational dependencies and the date associated with testing data impacted the lead time of wastewater for clinical trends, and no lead time was observed when the sample collection date (versus the result date) was used for both wastewater and clinical testing data. This study supports that trends in wastewater surveillance data reflect trends in COVID-19 disease occurrence and presents tools that could be applied to make wastewater signal more interpretable and comparable across studies.

Item Type:Article
Related URLs:
URLURL TypeDescription CentralArticle Paper ItemData/Code
Greenwald, Hannah D.0000-0001-5213-421X
Kennedy, Lauren C.0000-0002-4451-2361
Hinkle, Adrian0000-0002-2444-0874
Whitney, Oscar N.0000-0002-4858-2615
Fan, Vinson B.0000-0002-1688-7780
Flamholz, Avi I.0000-0002-9278-5479
Al-Shayeb, Basem0000-0002-3120-3201
Kantor, Rose0000-0002-5402-8979
Nelson, Kara L.0000-0001-8899-2662
Alternate Title:Interpretation of temporal and spatial trends of SARS-CoV-2 RNA in San Francisco Bay Area wastewater
Additional Information:© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. Received 30 April 2021, Revised 30 June 2021, Accepted 25 July 2021, Available online 31 July 2021. We thank Matt Metzger, Melissa Thornton, and the whole COVID-WEB team for support. We also thank our wastewater utility partners for facilitating and assisting with wastewater sampling and physicochemical measurements, including from East Bay Municipal Utility District (Florencio Gonzalez, Bill Chan, Gabriela Esparza, Paula Hansen, Kiley Kinnon, Nick Klumpp, Debra Mapp, Christine Pagtakhan, Daniel Siu, Dave Williams, Zach Wu, and Cheryl Yee), Central Contra Costa Sanitary District (Lori Schectel, Mary Lou Esparza, Blake Brown, Amanda Cauble), San Jose-Santa Clara Regional Wastewater Facility (RWF) Operations and Laboratory staff, and Central Marin Sanitation Agency. We are grateful to the wastewater treatment agencies as well as the San Francisco Estuary Institute for providing us with sewershed shape files. We thank the COVID-19 WBE Collaborative ( community for discussions of methods and approaches. Additionally, we thank Robert Tjian, Sarah Stanley, Erik Van Dis, Thomas Graham, and Mira Chaplin. We gratefully acknowledge funding from The Catena Foundation as well as rapid response grants from the Center for Information Technology Research in the Interest of Society and the Innovative Genomics Institute at UC Berkeley to K.L.N.. H.D.G. and L.C.K were supported by the National Science Foundation (NSF) Graduate Research Fellowship [grant number DGE-1752814]. In addition, H.D.G was supported by the Berkeley Fellowship, and L.C.K. was supported by NSF INTERN through Re-Inventing the Nation's Urban Water Infrastructure [grant number: 28139880-50542-C]. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Funding AgencyGrant Number
Catena FoundationUNSPECIFIED
University of California, BerkeleyUNSPECIFIED
NSF Graduate Research FellowshipDGE-1752814
Subject Keywords:COVID-19; Wastewater-based epidemiology; Pepper mild mottle virus; CrAssphage; Bacteroides; Human 18S rRNA
PubMed Central ID:PMC8325558
Record Number:CaltechAUTHORS:20210510-105354773
Persistent URL:
Official Citation:Hannah D. Greenwald, Lauren C. Kennedy, Adrian Hinkle, Oscar N. Whitney, Vinson B. Fan, Alexander Crits-Christoph, Sasha Harris-Lovett, Avi I. Flamholz, Basem Al-Shayeb, Lauren D. Liao, Matt Beyers, Daniel Brown, Alicia R. Chakrabarti, Jason Dow, Dan Frost, Mark Koekemoer, Chris Lynch, Payal Sarkar, Eileen White, Rose Kantor, Kara L. Nelson, Tools for interpretation of wastewater SARS-CoV-2 temporal and spatial trends demonstrated with data collected in the San Francisco Bay Area, Water Research X, Volume 12, 2021, 100111, ISSN 2589-9147, (
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109033
Deposited By: Tony Diaz
Deposited On:10 May 2021 19:42
Last Modified:18 Aug 2021 16:39

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