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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A versatile web app for identifying the drivers of COVID-19 epidemics
|
|---|---|
| Published in |
Journal of Translational Medicine, March 2021
|
| DOI | 10.1186/s12967-021-02736-2 |
| Pubmed ID | |
| Authors |
Wayne M. Getz, Richard Salter, Ludovica Luisa Vissat, Nir Horvitz |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 13% |
| Other | 5 | 6% |
| Student > Postgraduate | 5 | 6% |
| Researcher | 5 | 6% |
| Student > Ph. D. Student | 5 | 6% |
| Other | 13 | 16% |
| Unknown | 36 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 18% |
| Nursing and Health Professions | 12 | 15% |
| Social Sciences | 3 | 4% |
| Economics, Econometrics and Finance | 2 | 3% |
| Agricultural and Biological Sciences | 2 | 3% |
| Other | 11 | 14% |
| Unknown | 35 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 11 September 2021.
All research outputs
#15,676,645
of 23,295,606 outputs
Outputs from Journal of Translational Medicine
#2,303
of 4,109 outputs
Outputs of similar age
#260,437
of 426,137 outputs
Outputs of similar age from Journal of Translational Medicine
#47
of 91 outputs
Altmetric has tracked 23,295,606 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,109 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 426,137 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.