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. FINDINGS: 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%. INTERPRETATION: 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.
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. FINDINGS: 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%. INTERPRETATION: 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: Eduardo Azziz-Baumgartner; A S M Alamgir; Mustafizur Rahman; Nusrat Homaira; Badrul Munir Sohel; M A Yushuf Sharker; Rashid Uz Zaman; Jacob Dee; Emily S Gurley; Abdullah Al Mamun; Syeda Mah-E-Muneer; Alicia M Fry; Marc-Alain Widdowson; Joseph Bresee; Stephen Lindstrom; Tasnim Azim; Abdullah Brooks; Goutam Podder; M Jahangir Hossain; Mahmudur Rahman; Stephen P Luby Journal: Bull World Health Organ Date: 2011-10-04 Impact factor: 9.408
Authors: G Chowell; C Viboud; L Simonsen; M A Miller; J Hurtado; G Soto; R Vargas; M A Guzman; M Ulloa; C V Munayco Journal: Vaccine Date: 2011-07-22 Impact factor: 3.641
Authors: M Elizabeth Halloran; Neil M Ferguson; Stephen Eubank; Ira M Longini; Derek A T Cummings; Bryan Lewis; Shufu Xu; Christophe Fraser; Anil Vullikanti; Timothy C Germann; Diane Wagener; Richard Beckman; Kai Kadau; Chris Barrett; Catherine A Macken; Donald S Burke; Philip Cooley Journal: Proc Natl Acad Sci U S A Date: 2008-03-10 Impact factor: 11.205
Authors: Chelsea L Wood; Alex McInturff; Hillary S Young; DoHyung Kim; Kevin D Lafferty Journal: Philos Trans R Soc Lond B Biol Sci Date: 2017-06-05 Impact factor: 6.237