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

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

Water Research X (Aug 2021)

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

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

Affiliations

Hannah D. Greenwald: Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA; Berkeley Water Center, University of California, Berkeley, CA, USA
Lauren C. Kennedy: Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA; Berkeley Water Center, University of California, Berkeley, CA, USA
Adrian Hinkle: Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA; Berkeley Water Center, University of California, Berkeley, CA, USA
Oscar N. Whitney: Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
Vinson B. Fan: Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
Alexander Crits-Christoph: Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA; Innovative Genomics Institute, Berkeley, CA, USA
Sasha Harris-Lovett: Berkeley Water Center, University of California, Berkeley, CA, USA
Avi I. Flamholz: Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
Basem Al-Shayeb: Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA; Innovative Genomics Institute, Berkeley, CA, USA
Lauren D. Liao: School of Public Health, University of California, Berkeley, CA, USA
Matt Beyers: Alameda County Public Health Department, San Leandro, CA, USA
Daniel Brown: Contra Costa Health Services, Martinez, CA, USA
Alicia R. Chakrabarti: East Bay Municipal Utility District, Oakland, CA, USA
Jason Dow: Central Marin Sanitation Agency, San Rafael, CA, USA
Dan Frost: Central Contra Costa Sanitary District, Martinez, CA, USA
Mark Koekemoer: Central Marin Sanitation Agency, San Rafael, CA, USA
Chris Lynch: Contra Costa Health Services, Martinez, CA, USA
Payal Sarkar: San José-Santa Clara Regional Wastewater Facility, San José, CA, USA
Eileen White: East Bay Municipal Utility District, Oakland, CA, USA
Rose Kantor: Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA; Berkeley Water Center, University of California, Berkeley, CA, USA; Corresponding authors.
Kara L. Nelson: Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA; Berkeley Water Center, University of California, Berkeley, CA, USA; Innovative Genomics Institute, Berkeley, CA, USA; Corresponding authors.

Journal volume & issue: Vol. 12
p. 100111

Abstract

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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.

Published in Water Research X

ISSN: 2589-9147 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Environmental technology. Sanitary engineering
Website: https://www.journals.elsevier.com/water-research-x/

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