| Title |
Dynamically adjusting case reporting policy to maximize privacy and public health utility in the face of a pandemic
|
|---|---|
| Published in |
Journal of the American Medical Informatics Association, February 2022
|
| DOI | 10.1093/jamia/ocac011 |
| Pubmed ID | |
| Authors |
J Thomas Brown, Chao Yan, Weiyi Xia, Zhijun Yin, Zhiyu Wan, Aris Gkoulalas-Divanis, Murat Kantarcioglu, Bradley A Malin |
X Demographics
The data shown below were collected from the profiles of 10 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 States | 6 | 60% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 70% |
| Members of the public | 2 | 20% |
| Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 21% |
| Student > Master | 3 | 16% |
| Other | 2 | 11% |
| Researcher | 2 | 11% |
| Lecturer | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 5 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 21% |
| Social Sciences | 4 | 21% |
| Veterinary Science and Veterinary Medicine | 1 | 5% |
| Economics, Econometrics and Finance | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 6 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 10 May 2022.
All research outputs
#2,486,365
of 25,392,582 outputs
Outputs from Journal of the American Medical Informatics Association
#707
of 3,303 outputs
Outputs of similar age
#59,173
of 450,775 outputs
Outputs of similar age from Journal of the American Medical Informatics Association
#13
of 51 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,303 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.8. This one has done well, scoring higher than 78% 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 450,775 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 86% of its contemporaries.
We're also able to compare this research output to 51 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 74% of its contemporaries.