Evidence map›Paper›PMID 38909097›Full record

ArticleScientific reports2024

Estimating the COVID-19 prevalence from wastewater.

Jan Mohring, Neele Leithäuser, Jarosław Wlazło, Marvin Schulte, Maximilian Pilz, Johanna Münch, Karl-Heinz Küfer

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Review
  8. 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

7 authors.

Jan MohringFraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany. jan.mohring@itwm.fraunhofer.de.
Neele LeithäuserFraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany.
Jarosław WlazłoFraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany.
Marvin SchulteFraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany.
Maximilian PilzFraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany.
Johanna MünchFraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany.
Karl-Heinz KüferFraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany.

Funding

Bundesministerium für Bildung und Forschung 031L0295B
6 · The paper itself

Abstract

Wastewater based epidemiology has become a widely used tool for monitoring trends of concentrations of different pathogens, most notably and widespread of SARS-CoV-2. Therefore, in 2022, also in Rhineland-Palatinate, the Ministry of Science and Health has included 16 wastewater treatment sites in a surveillance program providing biweekly samples. However, the mere viral load data is subject to strong fluctuations and has limited value for political deciders on its own. Therefore, the state of Rhineland-Palatinate has commissioned the University Medical Center at Johannes Gutenberg University Mainz to conduct a representative cohort study called SentiSurv, in which an increasing number of up to 12,000 participants have been using sensitive antigen self-tests once or twice a week to test themselves for SARS-CoV-2 and report their status. This puts the state of Rhineland-Palatinate in the fortunate position of having time series of both, the viral load in wastewater and the prevalence of SARS-CoV-2 in the population. Our main contribution is a calibration study based on the data from 2023-01-08 until 2023-10-01 where we identified a scaling factor (

Indexed as

COVID-19SARS-CoV-2Viral LoadWastewaterGermanyHumansPrevalenceWastewater-Based Epidemiological MonitoringWastewaterCohort studyCovid-19ForecastMathematical modellingWastewater-based epidemiology

Identifiers

PMID38909097
PMCPMC11193770

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.