Evidence map›Paper›PMID 32287972›Full record

ArticleBuilding and environment2017

Evaluation of airborne disease infection risks in an airliner cabin using the Lagrangian-based Wells-Riley approach.

Yihuan Yan, Xiangdong Li, Yidan Shang, Jiyuan Tu

Abstract read
In one paragraph

Article in Building and environment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

34 citing papers in PubMed, 111 citations in OpenAlex.

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  13. Numerical evaluation of face masks for prevention of COVID-19 airborne transmission.Environmental science and pollution research international · 2022
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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

4 authors at 1 institution in 2 countries.

Yihuan YanSchool of Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia.
Xiangdong LiSchool of Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia.
Yidan ShangSchool of Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia.
Jiyuan TuSchool of Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia.
RMIT University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An urgent demand of assessing passengers' exposure risks in airliner cabins was raised as commercial airliners are one of the major media that carrying and transmitting infectious disease worldwide. In this study, simulations were conducted using a Boeing 737 cabin model to study the transport characteristics of airborne droplets and the associated infection risks of passengers. The numerical results of the airflow field were firstly compared against the experimental data in the literature to validate the reliability of the simulations. Airborne droplets were assumed to be released by passengers through coughing and their transport characteristics were modelled using the Lagrangian approach. Numerical results found that the particle travel distance was very sensitive to the release locations, and the impact was more significant along the longitudinal and horizontal directions. Particles released by passengers sitting next to the windows could travel much further than the others. A quantifiable approach was then applied to assess the individual infection risks of passengers. The key particle transport information such as the particle residence time yielded from the Lagrangian tracking process was extracted and integrated into the Wells-Riley equation to estimate the risks of infection. Compared to the Eulerian-based approach, the Lagrangian-based approach presented in this study is more robust as it addresses both the particle concentration and particle residence time in the breathing zone of every individual passenger.

Indexed as

Airborne particlesAirliner cabinsCFDInfection risksLagrangianWells-riley

Identifiers

PMID32287972
PMCPMC7111330
OpenAlexW2613448330

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.