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Metapopulation epidemic models with heterogeneous mixing and travel behaviour

Overview of attention for article published in Theoretical Biology and Medical Modelling, January 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
96 Mendeley
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Title
Metapopulation epidemic models with heterogeneous mixing and travel behaviour
Published in
Theoretical Biology and Medical Modelling, January 2014
DOI 10.1186/1742-4682-11-3
Pubmed ID
Authors

Andrea Apolloni, Chiara Poletto, José J Ramasco, Pablo Jensen, Vittoria Colizza

Abstract

Determining the pandemic potential of an emerging infectious disease and how it depends on the various epidemic and population aspects is critical for the preparation of an adequate response aimed at its control. The complex interplay between population movements in space and non-homogeneous mixing patterns have so far hindered the fundamental understanding of the conditions for spatial invasion through a general theoretical framework. To address this issue, we present an analytical modelling approach taking into account such interplay under general conditions of mobility and interactions, in the simplifying assumption of two population classes.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 5%
United Kingdom 2 2%
France 2 2%
Canada 1 1%
Italy 1 1%
South Africa 1 1%
Sri Lanka 1 1%
Russia 1 1%
Spain 1 1%
Other 1 1%
Unknown 80 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 29%
Researcher 20 21%
Professor > Associate Professor 9 9%
Student > Master 9 9%
Student > Postgraduate 7 7%
Other 18 19%
Unknown 5 5%
Readers by discipline Count As %
Mathematics 18 19%
Agricultural and Biological Sciences 16 17%
Computer Science 12 13%
Physics and Astronomy 11 11%
Engineering 9 9%
Other 21 22%
Unknown 9 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 31 January 2014.
All research outputs
#6,633,516
of 13,130,225 outputs
Outputs from Theoretical Biology and Medical Modelling
#75
of 232 outputs
Outputs of similar age
#89,185
of 251,446 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#2
of 27 outputs
Altmetric has tracked 13,130,225 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 232 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 67% 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 251,446 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 27 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 92% of its contemporaries.