| Title |
Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China
|
|---|---|
| Published in |
Frontiers in Medicine, May 2020
|
| DOI | 10.3389/fmed.2020.00169 |
| Pubmed ID | |
| Authors |
Jia Wangping, Han Ke, Song Yang, Cao Wenzhe, Wang Shengshu, Yang Shanshan, Wang Jianwei, Kou Fuyin, Tai Penggang, Li Jing, Liu Miao, He Yao |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 2 | 7% |
| Canada | 2 | 7% |
| Kenya | 2 | 7% |
| Costa Rica | 1 | 4% |
| Ecuador | 1 | 4% |
| Colombia | 1 | 4% |
| Germany | 1 | 4% |
| Venezuela, Bolivarian Republic of | 1 | 4% |
| Chile | 1 | 4% |
| Other | 4 | 15% |
| Unknown | 11 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 21 | 78% |
| Practitioners (doctors, other healthcare professionals) | 4 | 15% |
| Scientists | 1 | 4% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 232 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 232 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 13% |
| Student > Bachelor | 28 | 12% |
| Student > Master | 24 | 10% |
| Student > Ph. D. Student | 22 | 9% |
| Student > Doctoral Student | 13 | 6% |
| Other | 41 | 18% |
| Unknown | 73 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 38 | 16% |
| Engineering | 18 | 8% |
| Computer Science | 16 | 7% |
| Mathematics | 15 | 6% |
| Nursing and Health Professions | 9 | 4% |
| Other | 57 | 25% |
| Unknown | 79 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 93. 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 22 July 2020.
All research outputs
#382,741
of 22,738,543 outputs
Outputs from Frontiers in Medicine
#104
of 5,565 outputs
Outputs of similar age
#12,571
of 381,147 outputs
Outputs of similar age from Frontiers in Medicine
#9
of 156 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,565 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.9. 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 381,147 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 156 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 94% of its contemporaries.