Evidence map›Paper›PMID 35241744›Full record

ArticleScientific reports2022

Scaling SARS-CoV-2 wastewater concentrations to population estimates of infection.

Edward H Kaplan, Alessandro Zulli, Marcela Sanchez, Jordan Peccia

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  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

4 authors.

Edward H KaplanYale School of Management, Yale University, New Haven, CT, 06520, USA. edward.kaplan@yale.edu.ORCID 0000-0002-8722-7667
Alessandro ZulliDepartment of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale University, New Haven, CT, 06520, USA.ORCID 0000-0003-3636-0211
Marcela SanchezDepartment of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale University, New Haven, CT, 06520, USA.
Jordan PecciaDepartment of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale University, New Haven, CT, 06520, USA.ORCID 0000-0002-6482-2084

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring the progression of SARS-CoV-2 outbreaks requires accurate estimation of the unobservable fraction of the population infected over time in addition to the observed numbers of COVID-19 cases, as the latter present a distorted view of the pandemic due to changes in test frequency and coverage over time. The objective of this report is to describe and illustrate an approach that produces representative estimates of the unobservable cumulative incidence of infection by scaling the daily concentrations of SARS-CoV-2 RNA in wastewater from the consistent population contribution of fecal material to the sewage collection system.

Indexed as

COVID-19HumansIncidenceSARS-CoV-2WastewaterWastewater

Identifiers

PMID35241744
PMCPMC8894397

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.