| Title |
Optimizing COVID-19 surveillance in long-term care facilities: a modelling study
|
|---|---|
| Published in |
BMC Medicine, December 2020
|
| DOI | 10.1186/s12916-020-01866-6 |
| Pubmed ID | |
| Authors |
David R. M. Smith, Audrey Duval, Koen B. Pouwels, Didier Guillemot, Jérôme Fernandes, Bich-Tram Huynh, Laura Temime, Lulla Opatowski |
X Demographics
The data shown below were collected from the profiles of 37 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 9 | 24% |
| United Kingdom | 5 | 14% |
| France | 2 | 5% |
| Canada | 1 | 3% |
| Unknown | 20 | 54% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 33 | 89% |
| Scientists | 3 | 8% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 177 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 177 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 25 | 14% |
| Other | 18 | 10% |
| Researcher | 18 | 10% |
| Student > Bachelor | 15 | 8% |
| Student > Ph. D. Student | 10 | 6% |
| Other | 26 | 15% |
| Unknown | 65 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 44 | 25% |
| Nursing and Health Professions | 15 | 8% |
| Agricultural and Biological Sciences | 6 | 3% |
| Computer Science | 5 | 3% |
| Psychology | 5 | 3% |
| Other | 34 | 19% |
| Unknown | 68 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 65. 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 16 March 2021.
All research outputs
#632,393
of 24,752,377 outputs
Outputs from BMC Medicine
#450
of 3,831 outputs
Outputs of similar age
#17,758
of 520,086 outputs
Outputs of similar age from BMC Medicine
#15
of 121 outputs
Altmetric has tracked 24,752,377 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 3,831 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.7. This one has done well, scoring higher than 88% 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 520,086 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 121 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.