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Interdisciplinary Perspectives on Infectious Diseases
Volume 2011 (2011), Article ID 194507, 9 pages
Research Article

Assortativity and the Probability of Epidemic Extinction: A Case Study of Pandemic Influenza A (H1N1-2009)

1PRESTO, Japan Science and Technology Agency, Saitama 332-0012, Japan
2Theoretical Epidemiology, University of Utrecht, Yalelaan 7, 3584 CL Utrecht, The Netherlands
3Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546
4School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong

Received 26 May 2010; Accepted 29 November 2010

Academic Editor: Ben Kerr

Copyright © 2011 Hiroshi Nishiura et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Unlike local transmission of pandemic influenza A (H1N1-2009), which was frequently driven by school children, most cases identified in long-distance intranational and international travelers have been adults. The present study examines the relationship between the probability of temporary extinction and the age-dependent next-generation matrix, focusing on the impact of assortativity. Preferred mixing captures as a good approximation the assortativity of a heterogeneously mixing population. We show that the contribution of a nonmaintenance host (i.e., a host type which cannot sustain transmission on its own) to the risk of a major epidemic is greatly diminished as mixing patterns become more assortative, and in such a scenario, a higher proportion of non-maintenance hosts among index cases elevates the probability of extinction. Despite the presence of various other epidemiological factors that undoubtedly influenced the delay between first importations and the subsequent epidemic, these results suggest that the dominance of adults among imported cases represents one of the possible factors explaining the delays in geographic spread observed during the recent pandemic.