| Title |
Mathematical models for devising the optimal SARS-CoV-2 strategy for eradication in China, South Korea, and Italy
|
|---|---|
| Published in |
Journal of Translational Medicine, September 2020
|
| DOI | 10.1186/s12967-020-02513-7 |
| Pubmed ID | |
| Authors |
Shuo Jiang, Qiuyue Li, Chaoqun Li, Shanshan Liu, Xiaomeng He, Tao Wang, Hua Li, Christopher Corpe, Xiaoyan Zhang, Jianqing Xu, Jin Wang |
X Demographics
The data shown below were collected from the profiles of 4 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 Kingdom | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 89 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 12% |
| Researcher | 11 | 12% |
| Student > Ph. D. Student | 8 | 9% |
| Student > Bachelor | 7 | 8% |
| Other | 7 | 8% |
| Other | 17 | 19% |
| Unknown | 28 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 19% |
| Nursing and Health Professions | 11 | 12% |
| Biochemistry, Genetics and Molecular Biology | 5 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 6% |
| Social Sciences | 4 | 4% |
| Other | 19 | 21% |
| Unknown | 28 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 November 2020.
All research outputs
#14,497,073
of 23,234,261 outputs
Outputs from Journal of Translational Medicine
#1,822
of 4,091 outputs
Outputs of similar age
#221,463
of 399,528 outputs
Outputs of similar age from Journal of Translational Medicine
#43
of 111 outputs
Altmetric has tracked 23,234,261 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,091 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 50% 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 399,528 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.