Evidence map›Paper›PMID 37535602›Full record

ArticlePloS one2023

Understanding the efficacy of wastewater surveillance for SARS-CoV-2 in two diverse communities.

Matthew T Flood, Josh Sharp, Jennifer Bruggink, Molly Cormier, Bailey Gomes, Isabella Oldani, Lauren Zimmy, Joan B Rose

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Wastewater Surveillance of SARS-CoV-2 in Zambia: An Early Warning Tool.International journal of molecular sciences · 2024
    Article
  4. A survey of the representativeness and usefulness of wastewater-based surveillance systems in 10 countries across Europe in 2023.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2024
    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

8 authors.

Matthew T FloodDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0002-3363-6713
Josh SharpDepartment of Biology, Northern Michigan University, Marquette, Michigan, United States of America.
Jennifer BrugginkDepartment of Biology, Northern Michigan University, Marquette, Michigan, United States of America.
Molly CormierDepartment of Biology, Northern Michigan University, Marquette, Michigan, United States of America.
Bailey GomesDepartment of Biology, Northern Michigan University, Marquette, Michigan, United States of America.
Isabella OldaniDepartment of Biology, Northern Michigan University, Marquette, Michigan, United States of America.
Lauren ZimmyDepartment of Biology, Northern Michigan University, Marquette, Michigan, United States of America.
Joan B RoseDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the COVID-19 pandemic, wastewater-based surveillance has been shown to be a useful tool for monitoring the spread of disease in communities and the emergence of new viral variants of concern. As the pandemic enters its fourth year and clinical testing has declined, wastewater offers a consistent non-intrusive way to monitor community health in the long term. This study sought to understand how accurately wastewater monitoring represented the actual burden of disease between communities. Two communities varying in size and demographics in Michigan were monitored for SARS-CoV-2 in wastewater between March of 2020 and February of 2022. Additionally, each community was monitored for SARS-CoV-2 variants of concern from December 2020 to February 2022. Wastewater results were compared with zipcode and county level COVID-19 case data to determine which scope of clinical surveillance was most correlated with wastewater loading. Pearson r correlations were highest in the smaller of the two communities (population of 25,000) for N1 GC/person/day with zipcode level case data, and date of the onset of symptoms (r = 0.81). A clear difference was seen with more cases and virus signals in the wastewater of the larger community (population 110,000) when examined based on vaccine status, which reached only 50%. While wastewater levels of SARS-CoV-2 had a lower correlation to cases in the larger community, the information was still seen as valuable in supporting public health actions and further data including vaccination status should be examined in the future.

Indexed as

COVID-19SARS-CoV-2HumansPandemicsRNA, ViralWastewaterWastewater-Based Epidemiological MonitoringRNA, ViralWastewater

Identifiers

PMID37535602
PMCPMC10399835

What OpenQuestion holds

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LicenceCC BY
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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.