Mortality attributable to seasonal and pandemic influenza, Australia, 2003 to 2009, using a novel time series smoothing approach

Abstract

Background: Official 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.

Aim: To estimate Australian seasonal and pandemic influenza-attributable mortality from 2003 to 2009, and to assess a more flexible influenza mortality estimation approach.

Methods: We 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.

Results: Compared 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.

Conclusions: The 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.

Figure 1. Influenza laboratory detection time series, persons of all ages, Australia, 2003 to 2009.

Notes: 1. The values shown are the moving average of the current and previous two weeks, as used in the regression models (see Table S1 in File S1).

Figure 2. Spline model estimates of weekly influenza and non-influenza-attributable respiratory mortality in persons aged <65 and ≥65, by virus type, Australia, 2003 to 2009.

Notes: 1. The influenza A laboratory detection time series was included in the regression models as a separate variable for each year, to allow for variation in laboratory reporting and testing methods, virulence of influenza strains and susceptibility of the population (see Table S1 in File S1). 2. For 2009, the seasonal influenza A laboratory detection time series was unable to be included in the regression model for <65 year-olds (see Table S1 in File S1).

Figure 3. Harmonic model estimates of weekly influenza and non-influenza-attributable respiratory mortality in persons aged <65 and ≥65, by virus type, Australia, 2003 to 2009.

Notes: 1. The influenza A laboratory detection time series was included in the regression models as a separate variable for each year, to allow for variation in laboratory reporting and testing methods, virulence of influenza strains and susceptibility of the population (see Table S1 in File S1). 2. For 2009, the seasonal influenza A laboratory detection time series was unable to be included in the regression model for <65 year-olds (see Table S1 in File S1).