Site specific relationships between COVID-19 cases and SARS-CoV-2 viral load in wastewater treatment plant influent

Fitzgerald, Stephen F.; Rossi, Gianluigi; Low, Alison S.; McAteer, Sean P.; O’Keefe, Brian; Findlay, David; Cameron, Graeme J.; Pollard, Peter; Singleton, Peter T.R.; Ponton, George; Singer, Andrew C. ORCID: https://orcid.org/0000-0003-4705-6063; Farkas, Kata; Jones, Davey; Graham, David W.; Quintela-Baluja, Marcos; Tait-Burkard, Christine; Gally, David L.; Kao, Rowland; Corbishley, Alexander. 2021 Site specific relationships between COVID-19 cases and SARS-CoV-2 viral load in wastewater treatment plant influent. Environmental Science & Technology, 55 (22). 15276-15286. 10.1021/acs.est.1c05029

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Abstract/Summary

Wastewater based epidemiology (WBE) has become an important tool during the COVID-19 pandemic, however the relationship between SARS-CoV-2 RNA in wastewater treatment plant influent (WWTP) and cases in the community is not well-defined. We report here the development of a national WBE program across 28 WWTPs serving 50% of the population of Scotland, including large conurbations, as well as low-density rural and remote island communities. For each WWTP catchment area, we quantified spatial and temporal relationships between SARS-CoV-2 RNA in wastewater and COVID-19 cases. Daily WWTP SARS-CoV-2 influent viral RNA load, calculated using daily influent flow rates, had the strongest correlation (ρ > 0.9) with COVID-19 cases within a catchment. As the incidence of COVID-19 cases within a community increased, a linear relationship emerged between cases and influent viral RNA load. There were significant differences between WWTPs in their capacity to predict case numbers based on influent viral RNA load, with the limit of detection ranging from 25 cases for larger plants to a single case in smaller plants. SARS-CoV-2 viral RNA load can be used to predict the number of cases detected in the WWTP catchment area, with a clear statistically significant relationship observed above site-specific case thresholds.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1021/acs.est.1c05029
UKCEH and CEH Sections/Science Areas:	Pollution (Science Area 2017-)
ISSN:	0013-936X
Additional Keywords:	epidemiology, sewage, influent, coronavirus, RNA
NORA Subject Terms:	Health Biology and Microbiology
Date made live:	10 Jan 2022 16:37 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531731

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