Localised wastewater SARS-CoV-2 levels linked to COVID-19 cases: A long-term multisite study in England

Jones, Natalia R. ORCID: https://orcid.org/0000-0003-4025-2985, Elson, Richard ORCID: https://orcid.org/0000-0001-6350-5274, Wade, Matthew J., McIntyre-Nolan, Shannon, Woods, Andrew, Lewis, James, Hatziioanou, Diane, Vivancos, Roberto, Hunter, Paul R. ORCID: https://orcid.org/0000-0002-5608-6144 and Lake, Iain R. ORCID: https://orcid.org/0000-0003-4407-5357 (2025) Localised wastewater SARS-CoV-2 levels linked to COVID-19 cases: A long-term multisite study in England. Science of the Total Environment, 962. ISSN 0048-9697

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Abstract

Wastewater-based surveillance (WBS) can monitor for the presence of human health pathogens in the population. During COVID-19, WBS was widely used to determine wastewater SARS-CoV-2 RNA concentration (concentrations) providing information on community COVID-19 cases (cases). However, studies examining the relationship between concentrations and cases tend to be localised or focussed on small-scale institutional settings. Few have examined this relationship in multiple settings, over long periods, with large sample numbers, nor attempted to quantify the relationship between concentrations and cases or detail how catchment characteristics affected these.   This 18-month study (07/20-12/21) explored the correlation and quantitative relationship between concentrations and cases using censored regression. Our analysis used >94,000 wastewater samples collected from 452 diverse sampling sites (259 Sewage Treatment Works (STW) and 193 Sewer Network Sites (SNS)) covering ~65% of the English population. Wastewater concentrations were linked to ~6 million diagnostically confirmed COVID-19 cases.   High correlation coefficients were found between concentrations and cases (STW: median r=0.66, IQR:0.57–0.74; SNS: median r=0.65, IQR:0.54–0.74). The quantitative relationship (regression coefficient) between concentrations and cases was variable between catchments. Catchment and sampling characteristics (e.g. size of population and grab vs automated sampling) had significant but small effects on correlation and regression coefficients.   During the last six months of the study correlation coefficients reduced and regression coefficients became highly variable between catchments. This coincided with a shift towards younger cases, a highly vaccinated population and rapid emergence of the variant Omicron.   The English WBS programme was rapidly introduced at scale during COVID-19. Laboratory methods evolved and study catchments were highly diverse in size and characteristics. Despite this diversity, findings indicate that WBS provides an effective proxy for establishing COVID-19 dynamics across a wide variety of communities. While there is potential for predicting COVID-19 cases from wastewater concentration, this may be more effective at smaller scales.

Item Type:	Article
Additional Information:	Data availability statement: The UKHSA welcomes applications from organisations looking to use these data, and all applications will be rigorously reviewed using an objective, standards-based process. Potential applicants should contact DataAccess@ukhsa.gov.uk. Funding information: NRJ, RE, PH and IRL are funded by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response a partnership between the UK Health Security Agency, King's College London, and the University of East Anglia.
Uncontrolled Keywords:	wastewater-based surveillance,correlation,censored regression,socio-demographic characteristics,sewer network site catchments,water science and technology,epidemiology,sdg 3 - good health and well-being,3*,probably 3* but a good 3*! ,/dk/atira/pure/subjectarea/asjc/2300/2312
Faculty \ School:	Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA Faculty of Science Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups:	Faculty of Science > Research Centres > Centre for Ecology, Evolution and Conservation University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research Faculty of Science > Research Groups > Environmental Social Sciences Faculty of Medicine and Health Sciences > Research Groups > Epidemiology and Public Health Faculty of Social Sciences > Research Centres > Water Security Research Centre Faculty of Medicine and Health Sciences > Research Centres > Population Health
Depositing User:	LivePure Connector
Date Deposited:	14 Jan 2025 00:58
Last Modified:	16 Jan 2025 01:08
URI:	https://ueaeprints.uea.ac.uk/id/eprint/98181
DOI:	10.1016/j.scitotenv.2025.178455

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