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

Natalia R. Jones*, Richard Elson, Matthew J. Wade, Shannon McIntyre-Nolan, Andrew Woods, James Lewis, Diane Hatziioanou, Roberto Vivancos, Paul R. Hunter, Iain R. Lake

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number178455
JournalScience of the Total Environment, The
Volume962
DOIs
Publication statusPublished - 25 Jan 2025

Bibliographical note

Publisher Copyright:
© 2025 The Authors

Keywords

  • Censored regression
  • Correlation
  • Sewage treatment work catchments
  • Sewer network site catchments
  • Socio-demographic characteristics
  • Wastewater-based surveillance

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