| Title |
A modelling framework to assess the likely effectiveness of facemasks in combination with lock-down in managing the COVID-19 pandemic
|
|---|---|
| Published in |
Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences, June 2020
|
| DOI | 10.1098/rspa.2020.0376 |
| Pubmed ID | |
| Authors |
Richard O. J. H. Stutt, Renata Retkute, Michael Bradley, Christopher A. Gilligan, John Colvin |
X Demographics
The data shown below were collected from the profiles of 5,921 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 | 701 | 12% |
| Mexico | 659 | 11% |
| Spain | 432 | 7% |
| United Kingdom | 181 | 3% |
| Japan | 110 | 2% |
| Chile | 94 | 2% |
| Canada | 73 | 1% |
| Pakistan | 68 | 1% |
| India | 56 | <1% |
| Other | 546 | 9% |
| Unknown | 3001 | 51% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5386 | 91% |
| Scientists | 290 | 5% |
| Practitioners (doctors, other healthcare professionals) | 161 | 3% |
| Science communicators (journalists, bloggers, editors) | 82 | 1% |
| Unknown | 2 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 439 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 439 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 61 | 14% |
| Student > Master | 49 | 11% |
| Student > Bachelor | 46 | 10% |
| Other | 34 | 8% |
| Student > Ph. D. Student | 28 | 6% |
| Other | 90 | 21% |
| Unknown | 131 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 88 | 20% |
| Engineering | 26 | 6% |
| Nursing and Health Professions | 22 | 5% |
| Agricultural and Biological Sciences | 21 | 5% |
| Environmental Science | 16 | 4% |
| Other | 121 | 28% |
| Unknown | 145 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6002. 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 19 March 2024.
All research outputs
#570
of 25,784,004 outputs
Outputs from Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences
#1
of 3,642 outputs
Outputs of similar age
#48
of 434,930 outputs
Outputs of similar age from Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences
#1
of 60 outputs
Altmetric has tracked 25,784,004 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,642 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.1. This one has done particularly well, scoring higher than 99% 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 434,930 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 99% of its contemporaries.
We're also able to compare this research output to 60 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 98% of its contemporaries.