title: Estimation of potential global pandemic influenza mortality on the basis of vital registry data from the 1918-20 pandemic: a quantitative analysis.
abstract: BACKGROUND
  The threat of an avian influenza pandemic is causing widespread public concern and health policy response, especially in high-income countries. Our aim was to use high-quality vital registration data gathered during the 1918-20 pandemic to estimate global mortality should such a pandemic occur today.
  
  
  METHODS
  We identified all countries with high-quality vital registration data for the 1918-20 pandemic and used these data to calculate excess mortality. We developed ordinary least squares regression models that related excess mortality to per-head income and absolute latitude and used these models to estimate mortality had there been an influenza pandemic in 2004.
  
  
  RESULTS
  Excess mortality data show that, even in 1918-20, population mortality varied over 30-fold across countries. Per-head income explained a large fraction of this variation in mortality. Extrapolation of 1918-20 mortality rates to the worldwide population of 2004 indicates that an estimated 62 million people (10th-90th percentile range 51 million-81 million) would be killed by a similar influenza pandemic; 96% (95% CI 95-98) of these deaths would occur in the developing world. If this mortality were concentrated in a single year, it would increase global mortality by 114%.
  
  
  CONCLUSIONS
  This analysis of the empirical record of the 1918-20 pandemic provides a plausible upper bound on pandemic mortality. Most deaths will occur in poor countries--ie, in societies whose scarce health resources are already stretched by existing health priorities.
authors.affiliation: Harvard Initiative for Global Health, Harvard University, Cambridge, MA 02138, USA. christopher_murray@harvard.edu
authors.forename: Christopher J L
authors.initials: CJ
authors.lastname: Murray
authors.forename: Alan D
authors.initials: AD
authors.lastname: Lopez
authors.forename: Brian
authors.initials: B
authors.lastname: Chin
authors.forename: Dennis
authors.initials: D
authors.lastname: Feehan
authors.forename: Kenneth H
authors.initials: KH
authors.lastname: Hill
mesh_terms: D017677:Age Distribution; D004196:Disease Outbreaks / Q000266:history* / Q000706:statistics & numerical data; D005260:Female; D049673:History, 20th Century; D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology / Q000266:history* / Q000401:mortality; D008297:Male; D012042:Registries; D012044:Regression Analysis