title: Modelling of H1N1 flu in Iran.
abstract: BACKGROUND
  This year's new H1N1 flu strain has rapidly become a serious threat worldwide. This pandemic calls for urgent preparedness to mitigate its impact as much as possible. Employing this knowledge, we simulated a model of the outbreak of H1N1 in two cities of Iran (middle size: Kerman and metropolitan: Tehran).
  
  
  METHODS
  We developed a compartmental model to predict the expected number of patients who might develop severe (S), very severe (VS) disease or die (D). We assumed that, in winter, the Basic Reproductive Number (R0w) would reach 1.6 in Kerman and 1.8 in Tehran, respectively. Corresponding figures in summer varied from 1.2 (R0sMin) to 1.4 (R0sMax) in Kerman and from 1.3 to 1.5 in Tehran. Moreover, we checked the effect of the number of imported infectious cases at the beginning of the outbreak based on predictions.
  
  
  RESULTS
  A minimum lag of six months was observed between introduction of the virus (June 2009) and beginning of the outbreak (December 2009). The lag was sensitive to the number of infectious cases and the R0: a lower R0 postponed the peak. In Kerman, with R0sMax of 1.4, the number of S, VS, and D were 2,728, 546 and 468 respectively. Corresponding numbers in Tehran with R0sMax of 1.5 were 83,363, 16,673, and 14,291.
  
  
  CONCLUSIONS
  Since the number of S and VS cases would be crowded over a short period of time, the health care system most probably would not be able to provide appropriate services unless special measures are taken in advance. By reduction of R0 and the number of introduced infectious cases the peak of the outbreak might be postponed to the end of 2010. This would provide a golden opportunity to vaccinate a considerable proportion of the population.
authors.affiliation: Physiology Research Center, Kerman University of Medical Sciences, Kerman, Iran.
authors.forename: Ali Akbar
authors.initials: AA
authors.lastname: Haghdoost
authors.forename: Mohammad Mehdi
authors.initials: MM
authors.lastname: Gooya
authors.forename: Mohammad Reza
authors.initials: MR
authors.lastname: Baneshi
mesh_terms: D003198:Computer Simulation; D004196:Disease Outbreaks; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology*; D007492:Iran / Q000453:epidemiology