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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Cost-effective length and timing of school closure during an influenza pandemic depend on the severity
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, January 2014
|
| DOI | 10.1186/1742-4682-11-5 |
| Pubmed ID | |
| Authors |
Hiroshi Nishiura, Keisuke Ejima, Kenji Mizumoto, Shinji Nakaoka, Hisashi Inaba, Seiya Imoto, Rui Yamaguchi, Masaya M Saito |
| Abstract |
There has been a variation in published opinions toward the effectiveness of school closure which is implemented reactively when substantial influenza transmissions are seen at schools. Parameterizing an age-structured epidemic model using published estimates of the pandemic H1N1-2009 and accounting for the cost effectiveness, we examined if the timing and length of school closure could be optimized. |
X Demographics
The data shown below were collected from the profiles of 8 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 | 1 | 13% |
| United States | 1 | 13% |
| Singapore | 1 | 13% |
| United Kingdom | 1 | 13% |
| Unknown | 4 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 50% |
| Members of the public | 4 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| Indonesia | 1 | 2% |
| France | 1 | 2% |
| Unknown | 46 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 24% |
| Student > Ph. D. Student | 9 | 18% |
| Student > Bachelor | 5 | 10% |
| Professor | 4 | 8% |
| Student > Doctoral Student | 2 | 4% |
| Other | 8 | 16% |
| Unknown | 10 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 24% |
| Mathematics | 5 | 10% |
| Social Sciences | 4 | 8% |
| Agricultural and Biological Sciences | 3 | 6% |
| Economics, Econometrics and Finance | 3 | 6% |
| Other | 9 | 18% |
| Unknown | 14 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 11 August 2020.
All research outputs
#7,206,686
of 25,377,790 outputs
Outputs from Theoretical Biology and Medical Modelling
#85
of 287 outputs
Outputs of similar age
#79,047
of 321,184 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#3
of 6 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 287 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has gotten more attention than average, scoring higher than 70% 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 321,184 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 75% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.