title: [Percolation of influenza AH1N1 epidemic in the world: Usefulness of the spatial-connectivity models].
abstract: BACKGROUND
  The 2009 AH1N1 epidemics expanded rapidly around the world by the current connectivity conditions. The spread of epidemics can be described by the phenomenon of percolation, that allows the estimation of the threshold conditions that produce connectivity between different regions and that has been used to describe physical and ecological phenomena.
  
  
  OBJECTIVE
  To analyze the spread of AH1N1 epidemic based on information from the WHO.
  
  
  METHODS
  The world was considered as composed of a set of countries and regular cells. The moment when the percolation occurred was analyzed and logistic regressions were adjusted to the change in the proportion of infected units versus time, comparing predicted and observed rates.
  
  
  RESULTS
  Percolation occurred in America on day 15, in Eurasia on day 32 and in the world on day 74. The models showed adequate predictive capacity. The predictions for the percolation of the epidemic in the world varied between days 66 and 75. The prediction based on countries was better than that based on cells.
  
  
  CONCLUSIONS
  These results show that percolation theory fts well to the spread of epidemics. Predictions based only on data on-off (infected non infected) and in the progression of the proportion of infected cells are a good way of predicting the spread of an epidemic and when this crosses a region geographically.
authors.affiliation: Departmento de Ciencias Ecológicas, Facultad de Ciencias, Unicersidad de Chile, Chile. mcanals@uchile.cl
authors.forename: Mauricio
authors.initials: M
authors.lastname: Canals
authors.forename: Andrea
authors.initials: A
authors.lastname: Canals
mesh_terms: D002677:Chile / Q000453:epidemiology; D058872:Epidemics; D004812:Epidemiologic Methods; D014943:Global Health; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology* / Q000635:transmission; D008954:Models, Biological; D013997:Time Factors; D014944:World Health Organization