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Measured Dynamic Social Contact Patterns Explain the Spread of H1N1v Influenza

Overview of attention for article published in PLoS Computational Biology, March 2012
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  • 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 (93rd percentile)

Mentioned by

news
2 news outlets
blogs
2 blogs
policy
2 policy sources
twitter
7 X users
facebook
1 Facebook page

Citations

dimensions_citation
187 Dimensions

Readers on

mendeley
182 Mendeley
citeulike
3 CiteULike
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Title
Measured Dynamic Social Contact Patterns Explain the Spread of H1N1v Influenza
Published in
PLoS Computational Biology, March 2012
DOI 10.1371/journal.pcbi.1002425
Pubmed ID
Authors

Ken T. D. Eames, Natasha L. Tilston, Ellen Brooks-Pollock, W. John Edmunds

Abstract

Patterns of social mixing are key determinants of epidemic spread. Here we present the results of an internet-based social contact survey completed by a cohort of participants over 9,000 times between July 2009 and March 2010, during the 2009 H1N1v influenza epidemic. We quantify the changes in social contact patterns over time, finding that school children make 40% fewer contacts during holiday periods than during term time. We use these dynamically varying contact patterns to parameterise an age-structured model of influenza spread, capturing well the observed patterns of incidence; the changing contact patterns resulted in a fall of approximately 35% in the reproduction number of influenza during the holidays. This work illustrates the importance of including changing mixing patterns in epidemic models. We conclude that changes in contact patterns explain changes in disease incidence, and that the timing of school terms drove the 2009 H1N1v epidemic in the UK. Changes in social mixing patterns can be usefully measured through simple internet-based surveys.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Italy 3 2%
United Kingdom 3 2%
France 2 1%
Brazil 1 <1%
Portugal 1 <1%
Australia 1 <1%
Israel 1 <1%
Unknown 164 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 44 24%
Student > Ph. D. Student 38 21%
Student > Master 20 11%
Professor > Associate Professor 14 8%
Student > Bachelor 10 5%
Other 33 18%
Unknown 23 13%
Readers by discipline Count As %
Medicine and Dentistry 41 23%
Agricultural and Biological Sciences 26 14%
Mathematics 25 14%
Social Sciences 12 7%
Computer Science 9 5%
Other 37 20%
Unknown 32 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 43. 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 26 November 2021.
All research outputs
#958,858
of 25,371,288 outputs
Outputs from PLoS Computational Biology
#734
of 8,958 outputs
Outputs of similar age
#4,581
of 168,677 outputs
Outputs of similar age from PLoS Computational Biology
#7
of 110 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,958 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 91% 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 168,677 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 110 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 93% of its contemporaries.