Social encounter networks: Collective properties and disease transmission

Leon Danon, Thomas A. House, Jonathan M. Read, Matt J. Keeling*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

54 Citations (Scopus)

Abstract

A fundamental challenge of modern infectious disease epidemiology is to quantify the networks of social and physical contacts through which transmission can occur. Understanding the collective properties of these interactions is critical for both accurate prediction of the spread of infection and determining optimal control measures. However, even the basic properties of such networks are poorly quantified, forcing predictions to be made based on strong assumptions concerning network structure. Here, we report on the results of a large-scale survey of social encounters mainly conducted in Great Britain. First, we characterize the distribution of contacts, which possesses a lognormal body and a power-law tail with an exponent of -2.45; we provide a plausible mechanistic model that captures this form. Analysis of the high level of local clustering of contacts reveals additional structure within the network, implying that social contacts are degree assortative. Finally, we describe the epidemiological implications of this local network structure: these contradict the usual predictions from networks with heavy-tailed degree distributions and contain public-health messages about control. Our findings help us to determine the types of realistic network structure that should be assumed in future population level studies of infection transmission, leading to better interpretations of epidemiological data and more appropriate policy decisions.

Original languageEnglish
Pages (from-to)2826-2833
Number of pages8
JournalJournal of the Royal Society Interface
Volume9
Issue number76
DOIs
Publication statusPublished - 7 Nov 2012

Keywords

  • Epidemic
  • Infectious disease
  • Power law
  • Social contact
  • Survey

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