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Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared

Author

Listed:
  • Claudio Barbiellini Amidei

    (Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy)

  • Ugo Fedeli

    (Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy)

  • Nicola Gennaro

    (Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy)

  • Laura Cestari

    (Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy)

  • Elena Schievano

    (Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy)

  • Manuel Zorzi

    (Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy)

  • Paolo Girardi

    (Department of Environmental Sciences, Informatics and Statistics, Ca’ Foscari University of Venice, 30172 Venice, Italy)

  • Veronica Casotto

    (Epidemiological Department, Azienda Zero, Veneto Region, 35131 Padova, Italy)

Abstract

During the COVID-19 pandemic, excess mortality has been reported worldwide, but its magnitude has varied depending on methodological differences that hinder between-study comparability. Our aim was to estimate variability attributable to different methods, focusing on specific causes of death with different pre-pandemic trends. Monthly mortality figures observed in 2020 in the Veneto Region (Italy) were compared with those forecasted using: (1) 2018–2019 monthly average number of deaths; (2) 2015–2019 monthly average age-standardized mortality rates; (3) Seasonal Autoregressive Integrated Moving Average (SARIMA) models; (4) Generalized Estimating Equations (GEE) models. We analyzed deaths due to all-causes, circulatory diseases, cancer, and neurologic/mental disorders. Excess all-cause mortality estimates in 2020 across the four approaches were: +17.2% (2018–2019 average number of deaths), +9.5% (five-year average age-standardized rates), +15.2% (SARIMA), and +15.7% (GEE). For circulatory diseases (strong pre-pandemic decreasing trend), estimates were +7.1%, −4.4%, +8.4%, and +7.2%, respectively. Cancer mortality showed no relevant variations (ranging from −1.6% to −0.1%), except for the simple comparison of age-standardized mortality rates (−5.5%). The neurologic/mental disorders (with a pre-pandemic growing trend) estimated excess corresponded to +4.0%/+5.1% based on the first two approaches, while no major change could be detected based on the SARIMA and GEE models (−1.3%/+0.3%). The magnitude of excess mortality varied largely based on the methods applied to forecast mortality figures. The comparison with average age-standardized mortality rates in the previous five years diverged from the other approaches due to the lack of control over pre-existing trends. Differences across other methods were more limited, with GEE models probably representing the most versatile option.

Suggested Citation

  • Claudio Barbiellini Amidei & Ugo Fedeli & Nicola Gennaro & Laura Cestari & Elena Schievano & Manuel Zorzi & Paolo Girardi & Veronica Casotto, 2023. "Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared," IJERPH, MDPI, vol. 20(11), pages 1-13, May.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:11:p:5941-:d:1154508
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    References listed on IDEAS

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    1. Ugo Fedeli & Claudio Barbiellini Amidei & Alessandro Marcon & Veronica Casotto & Francesco Grippo & Enrico Grande & Thomas Gaisl & Stefano Barco, 2022. "Mortality Related to Chronic Obstructive Pulmonary Disease during the COVID-19 Pandemic: An Analysis of Multiple Causes of Death through Different Epidemic Waves in Veneto, Italy," IJERPH, MDPI, vol. 19(19), pages 1-9, October.
    2. Singh, Sarbjit & Parmar, Kulwinder Singh & Kumar, Jatinder & Makkhan, Sidhu Jitendra Singh, 2020. "Development of new hybrid model of discrete wavelet decomposition and autoregressive integrated moving average (ARIMA) models in application to one month forecast the casualties cases of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    3. Andrew C Stokes & Dielle J Lundberg & Irma T Elo & Katherine Hempstead & Jacob Bor & Samuel H Preston, 2021. "COVID-19 and excess mortality in the United States: A county-level analysis," PLOS Medicine, Public Library of Science, vol. 18(5), pages 1-18, May.
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