Evidence map›Paper›PMID 40202943›Full record

ArticlePLOS global public health2025

Near-source wastewater surveillance of SARS-CoV-2, norovirus, influenza virus and RSV across five different sites in the UK.

Jay C Bullen, Mina Mohaghegh, Fatima Tahir, Charlotte Hammer, Jacob Sims, Frederico Myers, Lucas Eisinger, Ali Reza Kasmati, Claire F Trant

Abstract read
In one paragraph

Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jay C BullenUntap Health, London, United Kingdom.ORCID https://orcid.org/0000-0002-4173-5850
Mina MohagheghUntap Health, London, United Kingdom.ORCID https://orcid.org/0009-0007-4143-084X
Fatima TahirUntap Health, London, United Kingdom.ORCID https://orcid.org/0009-0009-3221-0081
Charlotte HammerCambridge Infectious Diseases, Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-8288-0288
Jacob SimsUntap Health, London, United Kingdom.ORCID https://orcid.org/0009-0002-8599-5192
Frederico MyersUntap Health, London, United Kingdom.ORCID https://orcid.org/0009-0009-8841-6353
Lucas EisingerUntap Health, London, United Kingdom.
Ali Reza KasmatiUntap Health, London, United Kingdom.
Claire F TrantUntap Health, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

By tracking infectious diseases through sewage, municipal-scale wastewater surveillance has provided early warnings of future COVID-19 hospitalisations, identified biases in diagnostic testing, and is rapidly expanding to a broader array of pathogens. Despite applications in the targeted delivery of local interventions, near-source wastewater surveillance has received less attention and we know little about the near-source time series dynamics of contrasting pathogens. To address this, we conducted wastewater surveillance at five sites for SARS-CoV-2 and two sites for norovirus GI, norovirus GII, influenza A virus, influenza B virus, and human respiratory syncytial virus (RSV A and RSV B). Sites were selected for contrasting functions: an office, charity centre, museum, university, and care home. The key findings are (1) near-source wastewater detections were linked to local events (staff sickness, enhanced cleaning, changing populations); (2) wastewater detections decreased in the order norovirus GII > norovirus GI > SARS-CoV-2 ≈ influenza A ≈ RSV A > influenza B ≈ RSV B; (3) correlation between near-source wastewater data and national surveillance data increases as a function of catchment size and viral prevalence (examples include the SARS-CoV-2 BA.4/BA.5 variant peak at a museum and wastewater tracking the winter norovirus season); (4) strong weekday periodicity in near-source wastewater SARS-CoV-2 detections, with the correlation against COVID-19 case numbers increasing when modelling variable lag times between faecal shedding onset and clinical diagnosis (R2 = 0.45 increases to 0.84-0.86); (5) a log-linear relationship between the frequency of wastewater SARS-CoV-2 detection and log(catchment size⋅viral prevalence) (R2 = 0.6914-0.9066). Finally, we propose two use cases. Firstly, for rare or high-risk pathogens, near-source wastewater sentinel systems provide early warning of outbreaks, achieving high frequency community coverage without behaviour change and at low cost versus diagnostic testing. Secondly, for endemic pathogens, near-source wastewater reveals long-term patterns and trends, the effectiveness of local policies, and community vulnerabilities.

Identifiers

PMID40202943
PMCPMC11981152

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.