Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review

Am J Epidemiol. 2018 Feb 1;187(2):378-388. doi: 10.1093/aje/kwx270.


Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from -0.3-1.3 and 0.6-8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4-119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No "average" estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future.

Keywords: epidemiologic methods; influenza; mortality; systematic reviews.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Systematic Review

MeSH terms

  • Global Health / statistics & numerical data*
  • Humans
  • Influenza A virus
  • Influenza, Human / mortality*
  • Regression Analysis
  • Statistics as Topic / methods*