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An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices

Overview of attention for article published in BMC Infectious Diseases, April 2013
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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)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
1 news outlet
twitter
19 X users

Citations

dimensions_citation
99 Dimensions

Readers on

mendeley
159 Mendeley
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Title
An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices
Published in
BMC Infectious Diseases, April 2013
DOI 10.1186/1471-2334-13-185
Pubmed ID
Authors

Anna Machens, Francesco Gesualdo, Caterina Rizzo, Alberto E Tozzi, Alain Barrat, Ciro Cattuto

Abstract

The integration of empirical data in computational frameworks designed to model the spread of infectious diseases poses a number of challenges that are becoming more pressing with the increasing availability of high-resolution information on human mobility and contacts. This deluge of data has the potential to revolutionize the computational efforts aimed at simulating scenarios, designing containment strategies, and evaluating outcomes. However, the integration of highly detailed data sources yields models that are less transparent and general in their applicability. Hence, given a specific disease model, it is crucial to assess which representations of the raw data work best to inform the model, striking a balance between simplicity and detail.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 5%
France 2 1%
Switzerland 2 1%
Italy 2 1%
Kenya 1 <1%
Malaysia 1 <1%
South Africa 1 <1%
Australia 1 <1%
Unknown 141 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 25%
Researcher 32 20%
Student > Master 22 14%
Student > Bachelor 11 7%
Student > Doctoral Student 8 5%
Other 32 20%
Unknown 15 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 13%
Physics and Astronomy 19 12%
Mathematics 19 12%
Medicine and Dentistry 18 11%
Computer Science 16 10%
Other 43 27%
Unknown 24 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 27 May 2020.
All research outputs
#1,757,892
of 25,193,883 outputs
Outputs from BMC Infectious Diseases
#448
of 8,488 outputs
Outputs of similar age
#13,791
of 200,262 outputs
Outputs of similar age from BMC Infectious Diseases
#6
of 141 outputs
Altmetric has tracked 25,193,883 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,488 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 94% 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 200,262 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 141 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.