The evolution of Ebola virus: Insights from the 2013–2016 epidemic

Overview of attention for article published in Nature, October 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
11 news outlets
twitter
245 tweeters
facebook
4 Facebook pages

Readers on

mendeley
67 Mendeley
citeulike
1 CiteULike
Title
The evolution of Ebola virus: Insights from the 2013–2016 epidemic
Published in
Nature, October 2016
DOI 10.1038/nature19790
Pubmed ID
Authors

Edward C. Holmes, Gytis Dudas, Andrew Rambaut, Kristian G. Andersen, Holmes, Edward C, Dudas, Gytis, Rambaut, Andrew, Andersen, Kristian G

Abstract

The 2013-2016 epidemic of Ebola virus disease in West Africa was of unprecedented magnitude and changed our perspective on this lethal but sporadically emerging virus. This outbreak also marked the beginning of large-scale real-time molecular epidemiology. Here, we show how evolutionary analyses of Ebola virus genome sequences provided key insights into virus origins, evolution and spread during the epidemic. We provide basic scientists, epidemiologists, medical practitioners and other outbreak responders with an enhanced understanding of the utility and limitations of pathogen genomic sequencing. This will be crucially important in our attempts to track and control future infectious disease outbreaks.

Twitter Demographics

The data shown below were collected from the profiles of 245 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 4%
Australia 1 1%
Brazil 1 1%
United States 1 1%
Unknown 61 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 39%
Student > Ph. D. Student 12 18%
Student > Bachelor 11 16%
Student > Master 6 9%
Professor 4 6%
Other 8 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 43%
Biochemistry, Genetics and Molecular Biology 11 16%
Immunology and Microbiology 11 16%
Medicine and Dentistry 6 9%
Nursing and Health Professions 2 3%
Other 8 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 233. 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 07 March 2017.
All research outputs
#22,038
of 7,414,133 outputs
Outputs from Nature
#3,494
of 45,447 outputs
Outputs of similar age
#2,122
of 236,830 outputs
Outputs of similar age from Nature
#235
of 1,022 outputs
Altmetric has tracked 7,414,133 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 45,447 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 69.7. 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 236,830 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 1,022 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.