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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods
|
|---|---|
| Published in |
PLoS Computational Biology, May 2021
|
| DOI | 10.1371/journal.pcbi.1008959 |
| Pubmed ID | |
| Authors |
Jue Tao Lim, Kenwin Maung, Sok Teng Tan, Suan Ee Ong, Jane Mingjie Lim, Joel Ruihan Koo, Haoyang Sun, Minah Park, Ken Wei Tan, Joanne Yoong, Alex R. Cook, Borame Sue Lee Dickens |
X Demographics
The data shown below were collected from the profiles of 186 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 62 | 33% |
| United States | 4 | 2% |
| United Kingdom | 3 | 2% |
| Singapore | 2 | 1% |
| Indonesia | 2 | 1% |
| Sao Tome and Principe | 1 | <1% |
| South Africa | 1 | <1% |
| Sri Lanka | 1 | <1% |
| Japan | 1 | <1% |
| Other | 7 | 4% |
| Unknown | 102 | 55% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 167 | 90% |
| Scientists | 8 | 4% |
| Science communicators (journalists, bloggers, editors) | 7 | 4% |
| Practitioners (doctors, other healthcare professionals) | 4 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 15% |
| Researcher | 8 | 11% |
| Student > Bachelor | 6 | 8% |
| Student > Postgraduate | 4 | 6% |
| Lecturer | 3 | 4% |
| Other | 10 | 14% |
| Unknown | 30 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 5 | 7% |
| Medicine and Dentistry | 5 | 7% |
| Social Sciences | 4 | 6% |
| Economics, Econometrics and Finance | 4 | 6% |
| Agricultural and Biological Sciences | 3 | 4% |
| Other | 16 | 22% |
| Unknown | 35 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 208. 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 17 November 2022.
All research outputs
#192,138
of 25,806,080 outputs
Outputs from PLoS Computational Biology
#127
of 9,043 outputs
Outputs of similar age
#5,613
of 462,455 outputs
Outputs of similar age from PLoS Computational Biology
#3
of 208 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 99th percentile: it's in the top 5% 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 particularly well, scoring higher than 98% 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 462,455 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 98% of its contemporaries.
We're also able to compare this research output to 208 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.