Flow dynamics and characterization of a cough

Flow dynamics and characterization of a cough Abstract Airborne disease transmission has always been a topic of wide interests in various fields for decades. Cough is found to be one of the prime sources of airborne diseases as it has high velocity and large quantity of droplets. To understand and characterize the flow dynamics of a cough can help to control the airborne disease transmission. This study has measured flow dynamics of coughs with human subjects. The flow rate variation of a cough with time can be represented as a combination of gamma‐probability‐distribution functions. The variables needed to define the gamma‐probability‐distribution functions can be represented by some medical parameters. A robust multiple linear regression analysis indicated that these medical parameters can be obtained from the physiological details of a person. However, the jet direction and mouth opening area during a cough seemed not related to the physiological parameters of the human subjects. Combining the flow characteristics reported in this study with appropriate virus and droplet distribution information, the infectious source strength by coughing can be evaluated. Practical Implications There is a clear need for the scientific community to accurately predict and control the transmission of airborne diseases. Transportation of airborne viruses is often predicted using Computational Fluid Dynamics (CFD) simulations. CFD simulations are inexpensive but need accurate source boundary conditions for the precise prediction of disease transmission. Cough is found to be the prime source for generating infectious viruses. The present study was designed to develop an accurate source model to define thermo‐fluid boundary conditions for a cough. The model can aid in accurately predicting the disease transmission in various indoor environments, such as aircraft cabins, office spaces and hospitals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Indoor Air Wiley

Flow dynamics and characterization of a cough

Indoor Air, Volume 19 (6) – Dec 1, 2009

Loading next page...
 
/lp/wiley/flow-dynamics-and-characterization-of-a-cough-YIfm90rXRm
Publisher
Wiley
Copyright
© 2009 John Wiley & Sons A/S
ISSN
0905-6947
eISSN
1600-0668
D.O.I.
10.1111/j.1600-0668.2009.00619.x
Publisher site
See Article on Publisher Site

Abstract

Abstract Airborne disease transmission has always been a topic of wide interests in various fields for decades. Cough is found to be one of the prime sources of airborne diseases as it has high velocity and large quantity of droplets. To understand and characterize the flow dynamics of a cough can help to control the airborne disease transmission. This study has measured flow dynamics of coughs with human subjects. The flow rate variation of a cough with time can be represented as a combination of gamma‐probability‐distribution functions. The variables needed to define the gamma‐probability‐distribution functions can be represented by some medical parameters. A robust multiple linear regression analysis indicated that these medical parameters can be obtained from the physiological details of a person. However, the jet direction and mouth opening area during a cough seemed not related to the physiological parameters of the human subjects. Combining the flow characteristics reported in this study with appropriate virus and droplet distribution information, the infectious source strength by coughing can be evaluated. Practical Implications There is a clear need for the scientific community to accurately predict and control the transmission of airborne diseases. Transportation of airborne viruses is often predicted using Computational Fluid Dynamics (CFD) simulations. CFD simulations are inexpensive but need accurate source boundary conditions for the precise prediction of disease transmission. Cough is found to be the prime source for generating infectious viruses. The present study was designed to develop an accurate source model to define thermo‐fluid boundary conditions for a cough. The model can aid in accurately predicting the disease transmission in various indoor environments, such as aircraft cabins, office spaces and hospitals.

Journal

Indoor AirWiley

Published: Dec 1, 2009

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off