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Interpretation of temporal and spatial trends of SARS-CoV-2 RNA in San Francisco Bay Area wastewater

Authors :
Lauren C Kennedy
Jason Dow
Kara L. Nelson
Payal Sarkar
Vinson B. Fan
Chris Lynch
Alexander Crits-Christoph
Basem Al-Shayeb
Matt Beyers
Daniel Brown
Adrian Hinkle
Rose S. Kantor
Oscar N. Whitney
Dan Frost
Hannah D. Greenwald
Lauren D. Liao
Mark Koekemoer
Sasha Harris-Lovett
Avi I. Flamholz
Alicia R. Chakrabarti
Eileen White
Publication Year :
2021
Publisher :
Cold Spring Harbor Laboratory, 2021.

Abstract

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, and wastewater SARS-CoV-2 concentrations 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, crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA were evaluated as normalization biomarkers, and 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). 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 approaches that could be applied to make wastewater signal more interpretable and comparable across studies.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........5c5fd34756ef77e22da661016846effd
Full Text :
https://doi.org/10.1101/2021.05.04.21256418