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Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program

Overview of attention for article published in BMC Infectious Diseases, April 2022
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
14 news outlets
twitter
6 X users

Readers on

mendeley
56 Mendeley
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Title
Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program
Published in
BMC Infectious Diseases, April 2022
DOI 10.1186/s12879-022-07374-7
Pubmed ID
Authors

Chirayu Goswami, Michael Sheldon, Christian Bixby, Mehdi Keddache, Alexander Bogdanowicz, Yihe Wang, Jonathan Schultz, Jessica McDevitt, James LaPorta, Elaine Kwon, Steven Buyske, Dana Garbolino, Glenys Biloholowski, Alex Pastuszak, Mary Storella, Amit Bhalla, Florence Charlier-Rodriguez, Russ Hager, Robin Grimwood, Shareef A. Nahas

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 9%
Student > Master 5 9%
Professor 4 7%
Student > Bachelor 4 7%
Student > Doctoral Student 2 4%
Other 9 16%
Unknown 27 48%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 13%
Medicine and Dentistry 4 7%
Agricultural and Biological Sciences 3 5%
Social Sciences 3 5%
Environmental Science 2 4%
Other 9 16%
Unknown 28 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 89. 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 16 September 2023.
All research outputs
#478,632
of 25,490,562 outputs
Outputs from BMC Infectious Diseases
#120
of 8,632 outputs
Outputs of similar age
#12,755
of 446,877 outputs
Outputs of similar age from BMC Infectious Diseases
#7
of 215 outputs
Altmetric has tracked 25,490,562 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 8,632 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. 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 446,877 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 97% of its contemporaries.
We're also able to compare this research output to 215 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 97% of its contemporaries.