Evidence map›Paper›PMID 34983870›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Pooled testing efficiency increases with test frequency.

Ned Augenblick, Jonathan Kolstad, Ziad Obermeyer, Ao Wang

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. 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. Article
  4. 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.

Ned AugenblickHaas School of Business, University of California, Berkeley, CA 94720; augenblick@berkeley.edu.
Jonathan KolstadHaas School of Business, University of California, Berkeley, CA 94720.ORCID 0000-0002-6028-8750
Ziad ObermeyerSchool of Public Health, University of California, Berkeley, CA 94704.
Ao WangDepartment of Economics, University of California, Berkeley, CA 94720.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by

Indexed as

Cost-Benefit AnalysisCOVID-19COVID-19 TestingHumansMass ScreeningPopulation SurveillancePrevalenceSARS-CoV-2UncertaintyCOVID-19pooled testingsurveillance testing

Identifiers

PMID34983870
PMCPMC8764680

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.