| Title |
Incorporating Real-time Influenza Detection Into the Test-negative Design for Estimating Influenza Vaccine Effectiveness: The Real-time Test-negative Design (rtTND)
|
|---|---|
| Published in |
Clinical Infectious Diseases, September 2020
|
| DOI | 10.1093/cid/ciaa1453 |
| Pubmed ID | |
| Authors |
Leora R Feldstein, Wesley H Self, Jill M Ferdinands, Adrienne G Randolph, Michael Aboodi, Adrienne H Baughman, Samuel M Brown, Matthew C Exline, D Clark Files, Kevin Gibbs, Adit A Ginde, Michelle N Gong, Carlos G Grijalva, Natasha Halasa, Akram Khan, Christopher J Lindsell, Margaret Newhams, Ithan D Peltan, Matthew E Prekker, Todd W Rice, Nathan I Shapiro, Jay Steingrub, H Keipp Talbot, M Elizabeth Halloran, Manish Patel, Michele Kong, Ronald C Sanders, Katherine Irby, Mary Gaspers, Barry Markovitz, Natalie Cvijanovich, Adam Schwarz, Peter Mourani, Aline Maddux, Natalia Martinez Schlurmann, Keiko Tarquinio, Bria M Coates, Janice Sullivan, Vicki Montgomery, Heidi R Flori, Janet Hume, Jennifer E Schuster, Melissa Cullimore, Russell McCulloh, Sidharth Mahapatra, Shira J Gertz, Ryan Nofziger, Steven L Shein, Mark W Hall, Neal Thomas, Scott L Weiss, Laura L Loftis, Janet A Englund, Lincoln S Smith |
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 States | 2 | 50% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 42% |
| Lecturer | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Unknown | 5 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 1 | 8% |
| Nursing and Health Professions | 1 | 8% |
| Economics, Econometrics and Finance | 1 | 8% |
| Social Sciences | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 7 | 58% |
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 09 October 2020.
All research outputs
#14,218,837
of 23,243,271 outputs
Outputs from Clinical Infectious Diseases
#12,046
of 15,888 outputs
Outputs of similar age
#218,215
of 409,454 outputs
Outputs of similar age from Clinical Infectious Diseases
#309
of 394 outputs
Altmetric has tracked 23,243,271 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,888 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.0. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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 409,454 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 394 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.