Evidence map›Paper›PMID 35831373›Full record

ArticleScientific reports2022

Simulation of group testing scenarios can boost COVID-19 screening power.

Vinicius Henrique da Silva, Carolina Purcell Goes, Priscila Anchieta Trevisoli, Raquel Lello, Luan Gaspar Clemente, Talita Bonato de Almeida, Juliana Petrini, Luiz Lehmann Coutinho

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Vinicius Henrique da SilvaDepartment of Animal Science, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil.
Carolina Purcell GoesDepartment of Animal Science, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil.
Priscila Anchieta TrevisoliDepartment of Animal Science, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil.
Raquel LelloDepartment of Animal Science, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil.
Luan Gaspar ClementeDepartment of Animal Science, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil.
Talita Bonato de AlmeidaAnhembi Morumbi University, Piracicaba, Brazil.
Juliana PetriniDepartment of Animal Science, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil.
Luiz Lehmann CoutinhoDepartment of Animal Science, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, Brazil. llcoutinho@usp.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 has severely affected economies and health systems around the world. Mass testing could work as a powerful alternative to restrain disease dissemination, but the shortage of reagents is a limiting factor. A solution to optimize test usage relies on 'grouping' or 'pooling' strategies, which combine a set of individuals in a single reaction. To compare different group testing configurations, we developed the poolingr package, which performs an innovative hybrid in silico/in vitro approach to search for optimal testing configurations. We used 6759 viral load values, observed in 2389 positive individuals, to simulate a wide range of scenarios. We found that larger groups (>100) framed into multi-stage setups (up to six stages) could largely boost the power to detect spreaders. Although the boost was dependent on the disease prevalence, our method could point to cheaper grouping schemes to better mitigate COVID-19 dissemination through identification and quarantine recommendation for positive individuals.

Indexed as

COVID-19HumansMass ScreeningQuarantineSARS-CoV-2Serologic Tests

Identifiers

PMID35831373
PMCPMC9277601

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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.