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Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm

Overview of attention for article published in BMC Medicine, December 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

policy
1 policy source
twitter
23 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
233 Dimensions

Readers on

mendeley
219 Mendeley
citeulike
1 CiteULike
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Title
Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm
Published in
BMC Medicine, December 2012
DOI 10.1186/1741-7015-10-165
Pubmed ID
Authors

Michele Tizzoni, Paolo Bajardi, Chiara Poletto, José J Ramasco, Duygu Balcan, Bruno Gonçalves, Nicola Perra, Vittoria Colizza, Alessandro Vespignani

Abstract

Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches.

Twitter Demographics

The data shown below were collected from the profiles of 23 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 219 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 3 1%
Italy 3 1%
United States 3 1%
Vietnam 1 <1%
Brazil 1 <1%
India 1 <1%
Germany 1 <1%
Sri Lanka 1 <1%
United Kingdom 1 <1%
Other 2 <1%
Unknown 202 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 55 25%
Researcher 37 17%
Student > Master 22 10%
Other 16 7%
Professor 13 6%
Other 46 21%
Unknown 30 14%
Readers by discipline Count As %
Medicine and Dentistry 35 16%
Computer Science 33 15%
Physics and Astronomy 24 11%
Agricultural and Biological Sciences 20 9%
Mathematics 16 7%
Other 55 25%
Unknown 36 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 December 2020.
All research outputs
#1,950,642
of 22,877,793 outputs
Outputs from BMC Medicine
#1,309
of 3,438 outputs
Outputs of similar age
#19,157
of 279,451 outputs
Outputs of similar age from BMC Medicine
#29
of 64 outputs
Altmetric has tracked 22,877,793 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,438 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one has gotten more attention than average, scoring higher than 61% 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 279,451 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 93% of its contemporaries.
We're also able to compare this research output to 64 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 54% of its contemporaries.