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Airflow Dynamics of Coughing in Healthy Human Volunteers by Shadowgraph Imaging: An Aid to Aerosol Infection Control

Overview of attention for article published in PLOS ONE, April 2012
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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Title
Airflow Dynamics of Coughing in Healthy Human Volunteers by Shadowgraph Imaging: An Aid to Aerosol Infection Control
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0034818
Pubmed ID
Authors

Julian W. Tang, Andre Nicolle, Jovan Pantelic, Gerald C. Koh, Liang De Wang, Muhammad Amin, Christian A. Klettner, David K. W. Cheong, Chandra Sekhar, Kwok Wai Tham

Abstract

Cough airflow dynamics have been previously studied using a variety of experimental methods. In this study, real-time, non-invasive shadowgraph imaging was applied to obtain additional analyses of cough airflows produced by healthy volunteers. Twenty healthy volunteers (10 women, mean age 32.2±12.9 years; 10 men, mean age 25.3±2.5 years) were asked to cough freely, then into their sleeves (as per current US CDC recommendations) in this study to analyze cough airflow dynamics. For the 10 females (cases 1-10), their maximum detectable cough propagation distances ranged from 0.16-0.55 m, with maximum derived velocities of 2.2-5.0 m/s, and their maximum detectable 2-D projected areas ranged from 0.010-0.11 m(2), with maximum derived expansion rates of 0.15-0.55 m(2)/s. For the 10 males (cases 11-20), their maximum detectable cough propagation distances ranged from 0.31-0.64 m, with maximum derived velocities of 3.2-14 m/s, and their maximum detectable 2-D projected areas ranged from 0.04-0.14 m(2), with maximum derived expansion rates of 0.25-1.4 m(2)/s. These peak velocities were measured when the visibility of the exhaled airflows was optimal and compare favorably with those reported previously using other methods, and may be seen as a validation of these previous approaches in a more natural setting. However, the propagation distances can only represent a lower limit due to the inability of the shadowgraph method to visualize these cough airflows once their temperature cools to that of the ambient air, which is an important limitation of this methodology. The qualitative high-speed video footage of these volunteers coughing into their sleeves demonstrates that although this method rarely completely blocks the cough airflow, it decelerates, splits and redirects the airflow, eventually reducing its propagation. The effectiveness of this intervention depends on optimum positioning of the arm over the nose and mouth during coughing, though unsightly stains on sleeves may make it unacceptable to some.

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X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 1 <1%
Unknown 105 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 16%
Student > Master 13 12%
Student > Ph. D. Student 11 10%
Professor 8 7%
Student > Bachelor 8 7%
Other 21 19%
Unknown 31 28%
Readers by discipline Count As %
Engineering 36 33%
Medicine and Dentistry 10 9%
Agricultural and Biological Sciences 4 4%
Chemical Engineering 4 4%
Physics and Astronomy 3 3%
Other 20 18%
Unknown 32 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 August 2021.
All research outputs
#3,665,017
of 23,511,526 outputs
Outputs from PLOS ONE
#45,505
of 201,404 outputs
Outputs of similar age
#23,758
of 163,000 outputs
Outputs of similar age from PLOS ONE
#743
of 3,712 outputs
Altmetric has tracked 23,511,526 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 201,404 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 163,000 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 3,712 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.