↓ Skip to main content

Estimating the generation interval for COVID-19 based on symptom onset data

Overview of attention for article published in medRxiv, March 2020
Altmetric Badge

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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
72 news outlets
blogs
5 blogs
policy
1 policy source
twitter
2416 tweeters
facebook
2 Facebook pages
video
1 video uploader

Citations

dimensions_citation
77 Dimensions

Readers on

mendeley
222 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Estimating the generation interval for COVID-19 based on symptom onset data
Published in
medRxiv, March 2020
DOI 10.1101/2020.03.05.20031815
Authors

Tapiwa, Ganyani, Cécile, Kremer, Dongxuan, Chen, Andrea, Torneri, Christel, Faes, Jacco, Wallinga, Niel, Hens, Tapiwa Ganyani, Cecile Kremer, Dongxuan Chen, Andrea Torneri, Christel Faes, Jacco Wallinga, Niel Hens

Twitter Demographics

The data shown below were collected from the profiles of 2,416 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 222 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 222 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 18%
Student > Ph. D. Student 26 12%
Other 22 10%
Student > Master 19 9%
Student > Bachelor 17 8%
Other 52 23%
Unknown 47 21%
Readers by discipline Count As %
Medicine and Dentistry 55 25%
Biochemistry, Genetics and Molecular Biology 12 5%
Agricultural and Biological Sciences 11 5%
Pharmacology, Toxicology and Pharmaceutical Science 9 4%
Social Sciences 9 4%
Other 68 31%
Unknown 58 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 2310. 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 06 January 2021.
All research outputs
#1,479
of 16,650,998 outputs
Outputs from medRxiv
#67
of 15,664 outputs
Outputs of similar age
#167
of 378,587 outputs
Outputs of similar age from medRxiv
#10
of 2,137 outputs
Altmetric has tracked 16,650,998 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 15,664 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 54.1. 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 378,587 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 2,137 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 99% of its contemporaries.