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Background Influenza burden estimates help provide evidence to support influenza prevention and control programs at local and international levels. Methods Through a systematic review, we aimed to identify all published articles estimating rates of influenza-associated hospitalizations, describe methods and data sources used, and identify regions of the world where estimates are still lacking. We evaluated study heterogeneity to determine if we could pool published rates to generate global estimates of influenza-associated hospitalization. Results We identified 98 published articles estimating influenza-associated hospitalization rates from 2007-2018. Most articles (65%) identified were from high-income countries, with 34 of those (53%) presenting estimates from the United States. While we identified fewer publications (18%) from low- and lower-middle-income countries, 50% of those were published from 2015-2018, suggesting an increase in publications from lower-income countries in recent years. Eighty percent (n = 78) used a multiplier approach. Regression modelling techniques were only used with data from upper-middle or high-income countries where hospital administrative data was available. We identified variability in the methods, case definitions, and data sources used, including 91 different age groups and 11 different categories of case definitions. Due to the high observed heterogeneity across articles (I2 >99%), we were unable to pool published estimates. Conclusions The variety of methods, data sources, and case definitions adapted locally suggests that the current literature cannot be synthesized to generate global estimates of influenza-associated hospitalization burden.

Background Influenza causes substantial morbidity and mortality worldwide, however, reliable burden estimates from developing countries are limited, including India. We aimed to quantify influenza-associated mortality for India utilizing 2010-2013 nationally representative data sources for influenza virus circulation and deaths. Methods Virological data were obtained from the influenza surveillance network of 10 laboratories led by National Institute of Virology, Pune covering eight states from 2010-2013. Death data were obtained from the nationally representative Sample Registration System for the same time period. Generalized linear regression with negative binomial distribution was used to model weekly respiratory and circulatory deaths by age group and proportion of specimens positive for influenza by subtype; excess deaths above the seasonal baseline were taken as an estimate of influenza-associated mortality counts and rates. Annual excess death rates and the 2011 India Census data were used to estimate national influenza-associated deaths. Results Estimated annual influenza-associated respiratory mortality rates were highest for those ≥65 years (51.1, 95% confidence interval (CI) = 9.2-93.0 deaths/100 000 population) followed by those