title: Choosing pandemic parameters for pandemic preparedness planning: a comparison of pandemic scenarios prior to and following the influenza A(H1N1) 2009 pandemic.
abstract: BACKGROUND
  Mathematical models are used to explore various possible scenarios with regard to an influenza pandemic. We studied the ranges of parameter values in modelling studies on preparedness prior to 2009 in relation to the estimated parameter values of the influenza A(H1N1) 2009 pandemic.
  
  
  RESULTS
  We conducted two systematic literature searches, one aimed at epidemic parameter values that were used in pre-2009 pandemic influenza models, and the other aimed at estimates of epidemic variables from data collected during the influenza A(H1N1) 2009 pandemic. The range of parameter values used to inform models was broad and covered the range of estimates of these parameters inferred from the influenza A(H1N1) 2009 pandemic.
  
  
  CONCLUSIONS
  The current practice of selecting a range of plausible parameter values for influenza works well for modelling scenarios where effects of different interventions are explored to guide public health decision makers. To narrow down this range of plausible parameter values to the actual value during a pandemic, using incoming data, real-time estimation might provide an additional benefit.
authors: National Institute for Public Health and the Environment (RIVM), Centre for Infectious Disease Control, Preparedness and Response Unit, BA Bilthoven, The Netherlands. c.vanderweijden@ggdflevoland.nl
authors: Charlie P
authors: CP
authors: van der Weijden
authors: Mart L
authors: ML
authors: Stein
authors: André J
authors: AJ
authors: Jacobi
authors: Mirjam E E
authors: ME
authors: Kretzschmar
authors: Ralf
authors: R
authors: Reintjes
authors: Jim E
authors: JE
authors: van Steenbergen
authors: Aura
authors: A
authors: Timen
mesh_terms: D006285:Health Planning / Q000379:methods*; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D055256:Infectious Disease Incubation Period; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology* / Q000517:prevention & control / Q000628:therapy; D008962:Models, Theoretical; D058873:Pandemics / Q000517:prevention & control / Q000706:statistics & numerical data