Evidence map›Paper›PMID 35002201›Full record

ArticlePhysics of fluids (Woodbury, N.Y. : 1994)2021

Estimates of the stochasticity of droplet dispersion by a cough.

Shrey Trivedi, Savvas Gkantonas, Léo C C Mesquita, Salvatore Iavarone, Pedro M de Oliveira, Epaminondas Mastorakos

Open access · bronzeAbstract read
In one paragraph

Article in Physics of fluids (Woodbury, N.Y. : 1994), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
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

5 citing papers in PubMed, 24 citations in OpenAlex.

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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

6 authors at 1 institution in 2 countries.

Shrey TrivediDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom.ORCID https://orcid.org/0000-0003-2683-8699
Savvas GkantonasDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom.ORCID https://orcid.org/0000-0002-5354-578X
Léo C C MesquitaDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom.ORCID https://orcid.org/0000-0001-5086-696X
Salvatore IavaroneDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom.ORCID https://orcid.org/0000-0003-1763-0378
Pedro M de OliveiraDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom.ORCID https://orcid.org/0000-0002-5527-8128
Epaminondas MastorakosDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom.ORCID https://orcid.org/0000-0001-8245-5188
University of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, the statistical distributions of the position and the size of the evaporating droplets after a cough are evaluated, thus characterizing the inherent stochasticity of respiratory releases due to turbulence. For that, ten independent realizations of a cough with realistic initial conditions and in a room at 20 °C and 40% relative humidity were performed with large eddy simulations and Lagrangian tracking of the liquid phase. It was found that although turbulence decreases far from the emitter, it results in large variations in the spatial distribution of the droplets. The total suspended liquid mass after 60 s from the cough is in good agreement with that estimated by a one-dimensional model accounting for settling and evaporation under quiescent conditions, while deposition times of droplets in the 10-100

Identifiers

PMID35002201
PMCPMC8726635
OpenAlexW3216854528

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LicenceCC BY
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Registered trials

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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.