| Title |
Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution
|
|---|---|
| Published in |
eLife, September 2020
|
| DOI | 10.7554/elife.60067 |
| Pubmed ID | |
| Authors |
John Huddleston, John R Barnes, Thomas Rowe, Xiyan Xu, Rebecca Kondor, David E Wentworth, Lynne Whittaker, Burcu Ermetal, Rodney Stuart Daniels, John W McCauley, Seiichiro Fujisaki, Kazuya Nakamura, Noriko Kishida, Shinji Watanabe, Hideki Hasegawa, Ian Barr, Kanta Subbarao, Pierre Barrat-Charlaix, Richard A Neher, Trevor Bedford |
X Demographics
The data shown below were collected from the profiles of 44 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 14 | 32% |
| Switzerland | 3 | 7% |
| United Kingdom | 3 | 7% |
| Australia | 2 | 5% |
| India | 2 | 5% |
| Netherlands | 1 | 2% |
| Italy | 1 | 2% |
| China | 1 | 2% |
| Ireland | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 13 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 23 | 52% |
| Scientists | 20 | 45% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 20% |
| Researcher | 12 | 19% |
| Student > Bachelor | 5 | 8% |
| Professor | 5 | 8% |
| Student > Master | 3 | 5% |
| Other | 4 | 6% |
| Unknown | 22 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 14% |
| Immunology and Microbiology | 7 | 11% |
| Agricultural and Biological Sciences | 7 | 11% |
| Medicine and Dentistry | 6 | 9% |
| Veterinary Science and Veterinary Medicine | 3 | 5% |
| Other | 10 | 16% |
| Unknown | 22 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 78. 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 23 October 2023.
All research outputs
#557,428
of 25,753,031 outputs
Outputs from eLife
#1,661
of 15,839 outputs
Outputs of similar age
#16,457
of 426,629 outputs
Outputs of similar age from eLife
#60
of 524 outputs
Altmetric has tracked 25,753,031 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,839 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.9. This one has done well, scoring higher than 89% 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 426,629 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 96% of its contemporaries.
We're also able to compare this research output to 524 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.