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X Demographics
Mendeley readers
Attention Score in Context
| 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). |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Venezuela, Bolivarian Republic of | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | 2% |
| United States | 1 | 2% |
| France | 1 | 2% |
| Unknown | 57 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 17% |
| Researcher | 10 | 17% |
| Student > Ph. D. Student | 10 | 17% |
| Professor > Associate Professor | 4 | 7% |
| Student > Bachelor | 4 | 7% |
| Other | 7 | 12% |
| Unknown | 15 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 25% |
| Agricultural and Biological Sciences | 7 | 12% |
| Computer Science | 2 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 3% |
| Psychology | 2 | 3% |
| Other | 9 | 15% |
| Unknown | 23 | 38% |
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
#1,256,371
of 22,758,248 outputs
Outputs from BMC Infectious Diseases
#286
of 7,664 outputs
Outputs of similar age
#13,430
of 227,671 outputs
Outputs of similar age from BMC Infectious Diseases
#5
of 156 outputs
Altmetric has tracked 22,758,248 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,664 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has done particularly well, scoring higher than 96% 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 227,671 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 156 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 96% of its contemporaries.