↓ Skip to main content

Potential for airborne transmission of infection in the waiting areas of healthcare premises: stochastic analysis using a Monte Carlo model

Overview of attention for article published in BMC Infectious Diseases, August 2010
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)

Mentioned by

blogs
1 blog
twitter
6 tweeters

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
113 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Potential for airborne transmission of infection in the waiting areas of healthcare premises: stochastic analysis using a Monte Carlo model
Published in
BMC Infectious Diseases, August 2010
DOI 10.1186/1471-2334-10-247
Pubmed ID
Authors

Clive B Beggs, Simon J Shepherd, Kevin G Kerr

Abstract

Although many infections that are transmissible from person to person are acquired through direct contact between individuals, a minority, notably pulmonary tuberculosis (TB), measles and influenza are known to be spread by the airborne route. Airborne infections pose a particular threat to susceptible individuals whenever they are placed together with the index case in confined spaces. With this in mind, waiting areas of healthcare facilities present a particular challenge, since large numbers of people, some of whom may have underlying conditions which predispose them to infection, congregate in such spaces and can be exposed to an individual who may be shedding potentially pathogenic microorganisms. It is therefore important to understand the risks posed by infectious individuals in waiting areas, so that interventions can be developed to minimise the spread of airborne infections.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Poland 1 <1%
Unknown 107 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 24%
Student > Master 20 18%
Student > Ph. D. Student 13 12%
Student > Bachelor 9 8%
Other 9 8%
Other 18 16%
Unknown 17 15%
Readers by discipline Count As %
Medicine and Dentistry 35 31%
Engineering 17 15%
Agricultural and Biological Sciences 5 4%
Environmental Science 5 4%
Computer Science 4 4%
Other 20 18%
Unknown 27 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 12 September 2020.
All research outputs
#1,657,653
of 17,360,236 outputs
Outputs from BMC Infectious Diseases
#439
of 6,154 outputs
Outputs of similar age
#16,355
of 162,113 outputs
Outputs of similar age from BMC Infectious Diseases
#1
of 1 outputs
Altmetric has tracked 17,360,236 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,154 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done particularly well, scoring higher than 92% 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 162,113 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 89% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them