The Contribution of Social Behaviour to the Transmission of Influenza A in a Human Population

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  • Kucharski, A.J
    • Other Affiliation: Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
  • Kwok, K.O
    • Other Affiliation: School of Public Health, The University of Hong Kong, Hong Kong
  • Wei, V.W.I
    • Other Affiliation: School of Public Health, The University of Hong Kong, Hong Kong
  • Cowling, B.J
    • Other Affiliation: School of Public Health, The University of Hong Kong, Hong Kong
  • Read, J.M
    • Other Affiliation: Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
  • Lessler, J
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
  • Cummings, D.A
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
  • Riley, S
    • Other Affiliation: MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
Abstract
  • Variability in the risk of transmission for respiratory pathogens can result from several factors, including the intrinsic properties of the pathogen, the immune state of the host and the host's behaviour. It has been proposed that self-reported social mixing patterns can explain the behavioural component of this variability, with simulated intervention studies based on these data used routinely to inform public health policy. However, in the absence of robust studies with biological endpoints for individuals, it is unclear how age and social behaviour contribute to infection risk. To examine how the structure and nature of social contacts influenced infection risk over the course of a single epidemic, we designed a flexible disease modelling framework: the population was divided into a series of increasingly detailed age and social contact classes, with the transmissibility of each age-contact class determined by the average contacts of that class. Fitting the models to serologically confirmed infection data from the 2009 Hong Kong influenza A/H1N1p pandemic, we found that an individual's risk of infection was influenced strongly by the average reported social mixing behaviour of their age group, rather than by their personal reported contacts. We also identified the resolution of social mixing that shaped transmission: epidemic dynamics were driven by intense contacts between children, a post-childhood drop in risky contacts and a subsequent rise in contacts for individuals aged 35-50. Our results demonstrate that self-reported social contact surveys can account for age-associated heterogeneity in the transmission of a respiratory pathogen in humans, and show robustly how these individual-level behaviours manifest themselves through assortative age groups. Our results suggest it is possible to profile the social structure of different populations and to use these aggregated data to predict their inherent transmission potential.
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  • Article
License
  • Attribution 4.0 International
Journal title
  • PLoS Pathogens
Journal volume
  • 10
Journal issue
  • 6
Language
  • English
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  • Publisher
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  • MR/J008761/1
  • National Institute of General Medical Sciences, NIGMS: U01GM076497
  • Seventh Framework Programme, FP7: 278433
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  • Public Library of Science

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