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Time series methods for obtaining excess mortality attributable to influenza epidemics
Baltazar Nunes1, Isabel Natário, M Lucília Carvalho
1Departamento de Epidemiologia, Instituto Nacional de Saúde Dr. Ricardo Jorge, Av. Padre Cruz, Lisbon, Portugal. baltazar.nunes@insa.min-saude.pt
Statistical Methods in Medical Research
|March 10, 2010
Summary
Influenza epidemics cause excess mortality. This study unifies methods for estimating influenza-associated deaths using interrupted time series analysis, finding the chosen period type significantly impacts results.
Area of Science:
- Epidemiology
- Biostatistics
- Public Health
Background:
- Influenza epidemics in the Northern Hemisphere are linked to increased all-cause mortality.
- Estimating influenza-associated deaths from mortality time series is crucial for public health.
- Existing methods for estimation vary significantly.
Purpose of the Study:
- To unify and compare statistical methods for estimating influenza-associated deaths.
- To categorize existing methods based on key parameters.
- To develop a generalized framework and R-package for these methods.
Main Methods:
- Focus on statistical models fitting interrupted mortality time series.
- Categorization based on baseline model, period selection, and fitting procedure (iterative/non-iterative).
- Development of the R-package 'flubase' implementing these models.
Main Results:
- A unified classification of interrupted time series methods was established.
- The R-package 'flubase' was created, offering user-friendly implementation.
- Analysis of Portuguese mortality data revealed period selection as the most impactful parameter.
Conclusions:
- A generalized approach effectively unifies diverse methods for estimating influenza-associated deaths.
- The 'flubase' package provides a practical tool for applying these methods.
- Careful consideration of period selection is critical for accurate influenza mortality estimation.
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