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Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches
Claudio Barbiellini Amidei1, Ugo Fedeli1, Nicola Gennaro1
1Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy.
Summary
Estimating excess mortality during COVID-19 requires careful method selection. Different approaches yield varying results, especially when accounting for pre-pandemic trends in causes of death.
Area of Science:
- Epidemiology
- Biostatistics
- Public Health
Background:
- The COVID-19 pandemic caused significant global excess mortality.
- Methodological variations in studies hinder comparability of excess mortality estimates.
- Pre-existing mortality trends for specific causes complicate accurate assessment.
Purpose of the Study:
- To estimate the variability in excess mortality figures due to different statistical methods.
- To analyze how pre-pandemic trends influence excess mortality estimates for specific causes of death.
- To compare forecasting methods for assessing excess mortality during the COVID-19 pandemic.
Main Methods:
- Compared monthly mortality data from Italy's Veneto Region in 2020 with forecasted figures.
- Utilized four forecasting approaches: 2018-2019 death averages, 5-year average age-standardized rates, Seasonal Autoregressive Integrated Moving Average (SARIMA) models, and Generalized Estimating Equations (GEE) models.
- Analyzed excess mortality for all-causes, circulatory diseases, cancer, and neurologic/mental disorders.
Main Results:
- Excess all-cause mortality estimates ranged from +9.5% to +17.2% across methods.
- Circulatory disease mortality estimates varied significantly, from -4.4% to +8.4%, influenced by decreasing pre-pandemic trends.
- Cancer mortality showed minimal variation, except when using simple age-standardized rates. Neurologic/mental disorder estimates differed based on method, with SARIMA and GEE showing minimal change.
Conclusions:
- The magnitude of excess mortality estimates is highly dependent on the chosen forecasting methodology.
- Comparing age-standardized rates without trend adjustment can lead to divergent results.
- Generalized Estimating Equations (GEE) models appear to be a versatile and reliable option for excess mortality assessment.
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