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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data
|
|---|---|
| Published in |
PLoS Computational Biology, March 2019
|
| DOI | 10.1371/journal.pcbi.1006930 |
| Pubmed ID | |
| Authors |
Finlay Campbell, Anne Cori, Neil Ferguson, Thibaut Jombart |
X Demographics
The data shown below were collected from the profiles of 28 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 Kingdom | 5 | 18% |
| United States | 4 | 14% |
| Canada | 3 | 11% |
| France | 2 | 7% |
| Australia | 1 | 4% |
| Ireland | 1 | 4% |
| Peru | 1 | 4% |
| Brazil | 1 | 4% |
| Netherlands | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 9 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 50% |
| Members of the public | 12 | 43% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 162 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 162 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 27 | 17% |
| Student > Ph. D. Student | 20 | 12% |
| Student > Doctoral Student | 18 | 11% |
| Student > Master | 17 | 10% |
| Professor | 12 | 7% |
| Other | 34 | 21% |
| Unknown | 34 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 22 | 14% |
| Agricultural and Biological Sciences | 21 | 13% |
| Biochemistry, Genetics and Molecular Biology | 19 | 12% |
| Mathematics | 14 | 9% |
| Nursing and Health Professions | 6 | 4% |
| Other | 35 | 22% |
| Unknown | 45 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 28 May 2021.
All research outputs
#2,364,902
of 25,806,080 outputs
Outputs from PLoS Computational Biology
#2,105
of 9,043 outputs
Outputs of similar age
#51,279
of 365,359 outputs
Outputs of similar age from PLoS Computational Biology
#58
of 200 outputs
Altmetric has tracked 25,806,080 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,043 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 76% 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 365,359 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 200 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.