Abstract

BackgroundOfficial statistics under-estimate influenza deaths. Time series methods allow the estimation of influenza-attributable mortality. The methods often model background, non-influenza mortality using a cyclic, harmonic regression model based on the Serfling approach. This approach assumes that the seasonal pattern of non-influenza mortality is the same each year, which may not always be accurate.AimTo estimate Australian seasonal and pandemic influenza-attributable mortality from 2003 to 2009, and to assess a more flexible influenza mortality estimation approach.MethodsWe used a semi-parametric generalized additive model (GAM) to replace the conventional seasonal harmonic terms with a smoothing spline of time (‘spline model’) to estimate influenza-attributable respiratory, respiratory and circulatory, and all-cause mortality in persons aged <65 and ≥65 years. Influenza A(H1N1)pdm09, seasonal influenza A and B virus laboratory detection time series were used as independent variables. Model fit and estimates were compared with those of a harmonic model.ResultsCompared with the harmonic model, the spline model improved model fit by up to 20%. In <65 year-olds, the estimated respiratory mortality attributable to pandemic influenza A(H1N1)pdm09 was 0.5 (95% confidence interval (CI), 0.3, 0.7) per 100,000; similar to that of the years with the highest seasonal influenza A mortality, 2003 and 2007 (A/H3N2 years). In ≥65 year-olds, the highest annual seasonal influenza A mortality estimate was 25.8 (95% CI 22.2, 29.5) per 100,000 in 2003, five-fold higher than the non-statistically significant 2009 pandemic influenza estimate in that age group. Seasonal influenza B mortality estimates were negligible.ConclusionsThe spline model achieved a better model fit. The study provides additional evidence that seasonal influenza, particularly A/H3N2, remains an important cause of mortality in Australia and that the epidemic of pandemic influenza A (H1N1)pdm09 virus in 2009 did not result in mortality greater than seasonal A/H3N2 influenza mortality, even in younger age groups.

Highlights

  • Since the work of Farr examining influenza in 1848 [1], it has been recognised that mortality due to influenza will be underascertained and misclassified in official mortality statistics [2,3]

  • In $65 year-olds, the highest annual seasonal influenza A mortality estimate was 25.8 per 100,000 in 2003, five-fold higher than the non-statistically significant 2009 pandemic influenza estimate in that age group

  • Between 1997 and 2004 in Australia, official statistics reported an average 83 deaths annually with influenza listed as the underlying cause [4]

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Summary

Introduction

Since the work of Farr examining influenza in 1848 [1], it has been recognised that mortality due to influenza will be underascertained and misclassified in official mortality statistics [2,3]. Between 1997 and 2004 in Australia, official statistics reported an average 83 deaths annually with influenza listed as the underlying cause [4]. This compares with time series estimates of more than 2000 influenza-attributable all-cause deaths per year in persons aged $50 years alone [5]. The methods often model background, non-influenza mortality using a cyclic, harmonic regression model based on the Serfling approach This approach assumes that the seasonal pattern of non-influenza mortality is the same each year, which may not always be accurate

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