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Timeline
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
Geographical breakdown
Country | Count | As % |
---|---|---|
Malaysia | 60 | 33% |
United Kingdom | 4 | 2% |
United States | 3 | 2% |
Singapore | 2 | 1% |
South Africa | 2 | 1% |
Indonesia | 2 | 1% |
Austria | 1 | <1% |
Switzerland | 1 | <1% |
Japan | 1 | <1% |
Other | 10 | 5% |
Unknown | 97 | 53% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 165 | 90% |
Science communicators (journalists, bloggers, editors) | 7 | 4% |
Scientists | 7 | 4% |
Practitioners (doctors, other healthcare professionals) | 4 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 76 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 11 | 14% |
Researcher | 9 | 12% |
Student > Bachelor | 5 | 7% |
Student > Postgraduate | 4 | 5% |
Lecturer | 3 | 4% |
Other | 13 | 17% |
Unknown | 31 | 41% |
Readers by discipline | Count | As % |
---|---|---|
Nursing and Health Professions | 5 | 7% |
Medicine and Dentistry | 5 | 7% |
Social Sciences | 4 | 5% |
Economics, Econometrics and Finance | 4 | 5% |
Agricultural and Biological Sciences | 3 | 4% |
Other | 19 | 25% |
Unknown | 36 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 205. 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
#207,998
of 26,807,699 outputs
Outputs from PLoS Computational Biology
#132
of 9,256 outputs
Outputs of similar age
#5,856
of 466,673 outputs
Outputs of similar age from PLoS Computational Biology
#3
of 209 outputs
Altmetric has tracked 26,807,699 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 9,256 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.1. 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 466,673 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 209 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.