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4Flu - an individual based simulation tool to study the effects of quadrivalent vaccination on seasonal influenza in Germany

Overview of attention for article published in BMC Infectious Diseases, July 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#32 of 2,996)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
3 news outlets
twitter
1 tweeter

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
37 Mendeley
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Title
4Flu - an individual based simulation tool to study the effects of quadrivalent vaccination on seasonal influenza in Germany
Published in
BMC Infectious Diseases, July 2014
DOI 10.1186/1471-2334-14-365
Pubmed ID
Authors

Martin Eichner, Markus Schwehm, Johannes Hain, Helmut Uphoff, Bernd Salzberger, Markus Knuf, Ruprecht Schmidt-Ott

Abstract

Influenza vaccines contain Influenza A and B antigens and are adjusted annually to match the characteristics of circulating viruses. In Germany, Influenza B viruses belonged to the B/Yamagata lineage, but since 2001, the antigenically distinct B/Victoria lineage has been co-circulating. Trivalent influenza vaccines (TIV) contain antigens of the two A subtypes A(H3N2) and A(H1N1), yet of only one B lineage, resulting in frequent vaccine mismatches. Since 2012, the WHO has been recommending vaccine strains from both B lineages, paving the way for quadrivalent influenza vaccines (QIV).

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
United States 1 3%
Korea, Republic of 1 3%
Unknown 34 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 24%
Student > Ph. D. Student 7 19%
Student > Master 6 16%
Unspecified 4 11%
Professor > Associate Professor 4 11%
Other 7 19%
Readers by discipline Count As %
Medicine and Dentistry 11 30%
Unspecified 9 24%
Agricultural and Biological Sciences 6 16%
Mathematics 2 5%
Psychology 2 5%
Other 7 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 05 October 2015.
All research outputs
#227,581
of 6,354,657 outputs
Outputs from BMC Infectious Diseases
#32
of 2,996 outputs
Outputs of similar age
#7,796
of 135,660 outputs
Outputs of similar age from BMC Infectious Diseases
#1
of 155 outputs
Altmetric has tracked 6,354,657 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,996 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 98% 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 135,660 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 94% of its contemporaries.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.