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Real-time tracking of self-reported symptoms to predict potential COVID-19

Overview of attention for article published in Nature Medicine, May 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#39 of 9,485)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Citations

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1247 Dimensions

Readers on

mendeley
1132 Mendeley
Title
Real-time tracking of self-reported symptoms to predict potential COVID-19
Published in
Nature Medicine, May 2020
DOI 10.1038/s41591-020-0916-2
Pubmed ID
Authors

Cristina Menni, Ana M. Valdes, Maxim B. Freidin, Carole H. Sudre, Long H. Nguyen, David A. Drew, Sajaysurya Ganesh, Thomas Varsavsky, M. Jorge Cardoso, Julia S. El-Sayed Moustafa, Alessia Visconti, Pirro Hysi, Ruth C. E. Bowyer, Massimo Mangino, Mario Falchi, Jonathan Wolf, Sebastien Ourselin, Andrew T. Chan, Claire J. Steves, Tim D. Spector

X Demographics

X Demographics

The data shown below were collected from the profiles of 3,353 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1132 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 148 13%
Student > Master 130 11%
Student > Bachelor 118 10%
Student > Ph. D. Student 107 9%
Other 73 6%
Other 233 21%
Unknown 323 29%
Readers by discipline Count As %
Medicine and Dentistry 262 23%
Biochemistry, Genetics and Molecular Biology 76 7%
Computer Science 74 7%
Engineering 52 5%
Agricultural and Biological Sciences 49 4%
Other 250 22%
Unknown 369 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3000. 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 15 April 2023.
All research outputs
#2,244
of 25,909,281 outputs
Outputs from Nature Medicine
#39
of 9,485 outputs
Outputs of similar age
#193
of 420,994 outputs
Outputs of similar age from Nature Medicine
#6
of 162 outputs
Altmetric has tracked 25,909,281 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,485 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 103.0. This one has done particularly well, scoring higher than 99% 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 420,994 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 99% of its contemporaries.
We're also able to compare this research output to 162 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 96% of its contemporaries.