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The Geographic Spread of Influenza

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  • Eric Bonabeau
  • Laurent Toubiana
  • Antoine Flahault

Abstract

How infectious diseases spread in space within one cycle of an epidemic is an important question that has received considerable theoretical attention. There are, however, few empirical studies to support theoretical approaches, because data is scarce. Weekly reports obtained since 1984 from a network of general practitioners spanning the entire French territory allows the analysis of the spatiotemporal dynamics of influenza over a fine spatial scale. This analysis indicates that diffusion over long distances, possibly due to global transportation systems, is so quick that homogeneous global mixing occurs before the epidemic builds up within infected patches. A simple model in which the total number of cases is given by the empirical time series and cases are randomly assigned to patches according to the population weight of the patches exhibits the same spatiotemporal properties as real epidemic cycles: homogeneous mixing models constitute appropriate descriptions, except in the vicinity of the epidemic's peak, where geographic heterogeneities play a role. To appear in Proceedings of the Royal Society of London B.

Suggested Citation

  • Eric Bonabeau & Laurent Toubiana & Antoine Flahault, 1999. "The Geographic Spread of Influenza," Working Papers 99-01-004, Santa Fe Institute.
  • Handle: RePEc:wop:safiwp:99-01-004
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    References listed on IDEAS

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    1. Eric Bonabeau & Laurent Toubiana & Antoine Flahault, 1998. "Evidence for Global Mixing in Real Influenza Epidemics," Working Papers 98-07-061, Santa Fe Institute.
    2. Valleron, A.-J. & Bouvet, E. & Garnerin, P. & Ménarès, J. & Heard, I. & Letrait, S. & Lefaucheux, J., 1986. "A computer network for the surveillance of communicable diseases: The French experiment," American Journal of Public Health, American Public Health Association, vol. 76(11), pages 1289-1292.
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      Keywords

      Influenza; geographic spread; global mixing;
      All these keywords.

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