The utility of wastewater surveillance for monitoring SARS-CoV-2 prevalence

Public health authorities have increasingly used wastewater-based epidemiology (WBE) to monitor community transmission of SARS-CoV-2 and other agents. In this study, we evaluate the utility of WBE during the COVID-19 pandemic in England for estimating SARS-CoV-2 prevalence. We use wastewater data from the Environmental Monitoring for Health Protection program and prevalence data from the REal-time Assessment of Community Transmission-1 study. Across the pandemic, we describe how wastewater-based modeling can achieve representative SARS-CoV-2 prevalence estimates in fine and coarse spatial resolutions for relatively short-time horizons (of up to 1 month), and thus assist in filling temporal gaps in surveillance. We infer a temporally evolving relationship between wastewater and prevalence which may limit the utility of WBE for estimating SARS-CoV-2 prevalence over longer time horizons without a concurrent prevalence survey. Exploring further our finding of time-varying, population-level fecal shedding, we characterize WBE for SARS-CoV-2 prevalence as (i) vaccination coverage dependent and (ii) variant- specific. Our research suggests that these factors are important considerations in future uses of WBE by public health authorities in infectious disease outbreaks. We further demonstrate that WBE can improve both the cost efficiency and accuracy of community prevalence surveys which on their own may have incomplete geographic coverage and/or small sample sizes. Therefore, in England, for the objective of high spatial resolution prevalence monitoring, strategic use of SARS-CoV-2 wastewater concentration data nationally could have enhanced, but not replaced, community prevalence survey programs.

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Publication Details

Journal
PNAS Nexus
Published
2024-10-01
DOI
https://doi.org/10.1093/pnasnexus/pgae438
Citations
4
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
1.56

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article

The utility of wastewater surveillance for monitoring SARS-CoV-2 prevalence

Christl Ann Donnelly, Paul Elliott, Marc Chadeau‐Hyam, Cathal Mills
4 citations
PNAS Nexus
SARS-CoV-2 detection and testing
1.56
article

The utility of wastewater surveillance for monitoring SARS-CoV-2 prevalence

Christl Ann Donnelly, Paul Elliott, Marc Chadeau‐Hyam, Cathal Mills
article en
4 citations

Abstract

Public health authorities have increasingly used wastewater-based epidemiology (WBE) to monitor community transmission of SARS-CoV-2 and other agents. In this study, we evaluate the utility of WBE during the COVID-19 pandemic in England for estimating SARS-CoV-2 prevalence. We use wastewater data from the Environmental Monitoring for Health Protection program and prevalence data from the REal-time Assessment of Community Transmission-1 study. Across the pandemic, we describe how wastewater-based modeling can achieve representative SARS-CoV-2 prevalence estimates in fine and coarse spatial resolutions for relatively short-time horizons (of up to 1 month), and thus assist in filling temporal gaps in surveillance. We infer a temporally evolving relationship between wastewater and prevalence which may limit the utility of WBE for estimating SARS-CoV-2 prevalence over longer time horizons without a concurrent prevalence survey. Exploring further our finding of time-varying, population-level fecal shedding, we characterize WBE for SARS-CoV-2 prevalence as (i) vaccination coverage dependent and (ii) variant- specific. Our research suggests that these factors are important considerations in future uses of WBE by public health authorities in infectious disease outbreaks. We further demonstrate that WBE can improve both the cost efficiency and accuracy of community prevalence surveys which on their own may have incomplete geographic coverage and/or small sample sizes. Therefore, in England, for the objective of high spatial resolution prevalence monitoring, strategic use of SARS-CoV-2 wastewater concentration data nationally could have enhanced, but not replaced, community prevalence survey programs.

PNAS NexusVol. 3(10)
University of Oxford (GB), Imperial College London (GB)
National Institute for Health Research Health Protection Research Unit, National Institute for Health and Care Research, British Heart Foundation, Department of Health and Social Care, Imperial College London, University of Oxford, Public Health England, UK Dementia Research Institute, MRC-PHE Centre for Environment and Health, Medical Research Council, Engineering and Physical Sciences Research Council, NIHR Imperial Biomedical Research Centre
Openalex Percentile: Top 17%
SARS-CoV-2 detection and testing
1.56
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