Abstract
BackgroundPoisson regression modelling has been widely used to estimate the disease burden attributable to influenza, though not without concerns that some of the excess burden could be due to other causes. This study aims to provide annual estimates of the mortality and hospitalization burden attributable to both seasonal influenza and the 2009 A/H1N1 pandemic influenza for Canada, and to discuss issues related to the reliability of these estimates.MethodsWeekly time-series for all-cause mortality and regression models were used to estimate the number of deaths in Canada attributable to influenza from September 1992 to December 2009. To assess their robustness, the annual estimates derived from different parameterizations of the regression model for all-cause mortality were compared. In addition, the association between the annual estimates for mortality and hospitalization by age group, underlying cause of death or primary reason for admission and discharge status is discussed.ResultsThe crude influenza-attributed mortality rate based on all-cause mortality and averaged over 17 influenza seasons prior to the 2009 A/H1N1 pandemic was 11.3 (95%CI, 10.5 - 12.1) deaths per 100 000 population per year, or an average of 3,500 (95%CI, 3,200 - 3,700) deaths per year attributable to seasonal influenza. The estimated annual rates ranged from undetectable at the ecological level to more than 6000 deaths per year over the three A/Sydney seasons. In comparison, we attributed an estimated 740 deaths (95%CI, 350–1500) to A(H1N1)pdm09. Annual estimates from different model parameterizations were strongly correlated, as were estimates for mortality and morbidity; the higher A(H1N1)pdm09 burden in younger age groups was the most notable exception.InterpretationWith the exception of some of the Serfling models, differences in the ecological estimates of the disease burden attributable to influenza were small in comparison to the variation in disease burden from one season to another.
Highlights
Regression modelling is widely used to estimate the disease burden attributable to seasonal and pandemic influenza [1], with this approach recently endorsed by the World Health Organization (WHO) [2], along with a caution not to compare the number of laboratory-confirmed deaths from the 2009 pandemic with estimates of the number of seasonal influenza deaths
With the availability of a proxy variable for the weekly level of influenza activity, all weeks can be included in the analysis and the regression model can simultaneously estimate the seasonal baseline and the number of deaths directly associated with the weekly level of influenza activity
The average number of deaths attributable to seasonal influenza over the 17 seasons prior to the 2009 pandemic was estimated at 3,500 for an average crude mortality rate of 11.3 deaths per 100,000 population per year
Summary
Regression modelling is widely used to estimate the disease burden attributable to seasonal and pandemic influenza [1], with this approach recently endorsed by the World Health Organization (WHO) [2], along with a caution not to compare the number of laboratory-confirmed deaths from the 2009 pandemic with estimates of the number of seasonal influenza deaths Applying these statistical methods to Canadian data has allowed us to study the full burden of seasonal or pandemic influenza on mortality [3,4], and admissions to hospital [5], visits to emergency departments [6], and workplace absenteeism [7], thereby gaining a better understanding of the relative risks of severe disease that age and health status poses. This study aims to provide annual estimates of the mortality and hospitalization burden attributable to both seasonal influenza and the 2009 A/H1N1 pandemic influenza for Canada, and to discuss issues related to the reliability of these estimates
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
