↓ Skip to main content

PLOS

Measured Dynamic Social Contact Patterns Explain the Spread of H1N1v Influenza

Overview of attention for article published in PLoS Computational Biology, March 2012
Altmetric Badge

Mentioned by

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

Citations

dimensions_citation
186 Dimensions

Readers on

mendeley
182 Mendeley
citeulike
3 CiteULike
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%