Evidence map›Paper›PMID 34304074›Full record

ReviewWater research2021

Making waves: Defining the lead time of wastewater-based epidemiology for COVID-19.

Scott W Olesen, Maxim Imakaev, Claire Duvallet

Abstract readReview
In one paragraph

Review in Water research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.

0numbers the graph read from it
0cells of the map it votes in
79citing 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

79 citing papers in PubMed.

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  19. Optimized Aluminum Hydroxide Adsorption-Precipitation for Improved Viral Detection in Wastewater.International journal of environmental research and public health · 2025
    Article
  20. Article

19 more citing papers are in PubMed but not listed here.

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

3 authors.

Scott W OlesenBiobot Analytics, Inc., Cambridge, MA, USA.
Maxim ImakaevBiobot Analytics, Inc., Cambridge, MA, USA.
Claire DuvalletBiobot Analytics, Inc., Cambridge, MA, USA. Electronic address: claire@biobot.io.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individuals infected with SARS-CoV-2, the virus that causes COVID-19, may shed the virus in stool before developing symptoms, suggesting that measurements of SARS-CoV-2 concentrations in wastewater could be a "leading indicator" of COVID-19 prevalence. Multiple studies have corroborated the leading indicator concept by showing that the correlation between wastewater measurements and COVID-19 case counts is maximized when case counts are lagged. However, the meaning of "leading indicator" will depend on the specific application of wastewater-based epidemiology, and the correlation analysis is not relevant for all applications. In fact, the quantification of a leading indicator will depend on epidemiological, biological, and health systems factors. Thus, there is no single "lead time" for wastewater-based COVID-19 monitoring. To illustrate this complexity, we enumerate three different applications of wastewater-based epidemiology for COVID-19: a qualitative "early warning" system; an independent, quantitative estimate of disease prevalence; and a quantitative alert of bursts of disease incidence. The leading indicator concept has different definitions and utility in each application.

Indexed as

COVID-19Wastewater-Based Epidemiological MonitoringHumansLeadSARS-CoV-2WastewaterLeadWastewaterCOVID-19SARS-CoV-2SurveillanceWastewater-based epidemiology

Identifiers

PMID34304074
PMCPMC8282235

What OpenQuestion holds

Textmetadata
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.