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]
Summary
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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