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Modelling the transmission of healthcare associated infections: a systematic review

Overview of attention for article published in BMC Infectious Diseases, June 2013
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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 (86th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
15 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
71 Dimensions

Readers on

mendeley
217 Mendeley
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Title
Modelling the transmission of healthcare associated infections: a systematic review
Published in
BMC Infectious Diseases, June 2013
DOI 10.1186/1471-2334-13-294
Pubmed ID
Authors

Esther van Kleef, Julie V Robotham, Mark Jit, Sarah R Deeny, William J Edmunds

Abstract

Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time.

Twitter Demographics

The data shown below were collected from the profiles of 15 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 217 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 6 3%
United States 6 3%
France 2 <1%
India 1 <1%
Brazil 1 <1%
Australia 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Unknown 198 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 24%
Researcher 40 18%
Student > Master 33 15%
Student > Bachelor 16 7%
Student > Doctoral Student 14 6%
Other 62 29%
Readers by discipline Count As %
Medicine and Dentistry 56 26%
Agricultural and Biological Sciences 44 20%
Unspecified 36 17%
Mathematics 20 9%
Biochemistry, Genetics and Molecular Biology 9 4%
Other 52 24%

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 04 October 2013.
All research outputs
#1,531,912
of 11,648,643 outputs
Outputs from BMC Infectious Diseases
#510
of 4,351 outputs
Outputs of similar age
#18,954
of 137,133 outputs
Outputs of similar age from BMC Infectious Diseases
#19
of 148 outputs
Altmetric has tracked 11,648,643 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,351 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 88% 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 137,133 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 86% of its contemporaries.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.