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American Journal of Epidemiology Advance Access originally published online on September 12, 2006
American Journal of Epidemiology 2006 164(10):936-944; doi:10.1093/aje/kwj317
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American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

Original Contribution

Using Data on Social Contacts to Estimate Age-specific Transmission Parameters for Respiratory-spread Infectious Agents

Jacco Wallinga1, Peter Teunis1 and Mirjam Kretzschmar1,2

1 National Institute for Public Health and the Environment, Bilthoven, the Netherlands
2 Present address: Department of Public Health Medicine, School of Public Health, University of Bielefeld, Bielefeld, Germany

Correspondence to Dr. Jacco Wallinga, National Institute for Public Health and the Environment, Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, the Netherlands (e-mail: jacco.wallinga{at}rivm.nl).

The estimation of transmission parameters has been problematic for diseases that rely predominantly on transmission of pathogens from person to person through small infectious droplets. Age-specific transmission parameters determine how such respiratory agents will spread among different age groups in a human population. Estimating the values of these parameters is essential in planning an effective response to potentially devastating pandemics of smallpox or influenza and in designing control strategies for diseases such as measles or mumps. In this study, the authors estimated age-specific transmission parameters by augmenting infectious disease data with auxiliary data on self-reported numbers of conversational partners per person. They show that models that use transmission parameters based on these self-reported social contacts are better able to capture the observed patterns of infection of endemically circulating mumps, as well as observed patterns of spread of pandemic influenza. The estimated age-specific transmission parameters suggested that school-aged children and young adults will experience the highest incidence of infection and will contribute most to further spread of infections during the initial phase of an emerging respiratory-spread epidemic in a completely susceptible population. These findings have important implications for controlling future outbreaks of novel respiratory-spread infectious agents.

disease outbreaks; disease transmission, horizontal; infection; influenza, human; models, statistical; mumps; statistics

Abbreviations: BIC, Bayesian Information Criterion; CI, confidence interval

Editor's note: An invited commentary on this article is published on page 945.


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