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Assessment of Excess Mortality in Italy in 2020–2021 as a Function of Selected Macro-Factors

Author

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  • Emiliano Ceccarelli

    (Statistical Service, Istituto Superiore di Sanità, 00161 Rome, Italy)

  • Giada Minelli

    (Statistical Service, Istituto Superiore di Sanità, 00161 Rome, Italy
    These authors contributed equally to this work.)

  • Viviana Egidi

    (Department of Statistical Sciences, La Sapienza University, 00185 Rome, Italy
    These authors contributed equally to this work.)

  • Giovanna Jona Lasinio

    (Department of Statistical Sciences, La Sapienza University, 00185 Rome, Italy
    These authors contributed equally to this work.)

Abstract

Background: Excess mortality (EM) can reliably capture the impact of a pandemic, this study aims at assessing the numerous factors associated with EM during the COVID-19 pandemic in Italy. Methods: Mortality records (ISTAT 2015–2021) aggregated in the 610 Italian Labour Market Areas (LMAs) were used to obtain the EM P-scores to associate EM with socioeconomic variables. A two-step analysis was implemented: (1) Functional representation of EM and clustering. (2) Distinct functional regression by cluster. Results: The LMAs are divided into four clusters: 1 low EM; 2 moderate EM; 3 high EM; and 4 high EM-first wave. Low-Income showed a negative association with EM clusters 1 and 4. Population density and percentage of over 70 did not seem to affect EM significantly. Bed availability positively associates with EM during the first wave. The employment rate positively associates with EM during the first two waves, becoming negatively associated when the vaccination campaign began. Conclusions: The clustering shows diverse behaviours by geography and time, the impact of socioeconomic characteristics, and local governments and health services’ responses. The LMAs allow to draw a clear picture of local characteristics associated with the spread of the virus. The employment rate trend confirmed that essential workers were at risk, especially during the first wave.

Suggested Citation

  • Emiliano Ceccarelli & Giada Minelli & Viviana Egidi & Giovanna Jona Lasinio, 2023. "Assessment of Excess Mortality in Italy in 2020–2021 as a Function of Selected Macro-Factors," IJERPH, MDPI, vol. 20(4), pages 1-14, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:2812-:d:1058387
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    References listed on IDEAS

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    1. Andrea Ascani & Alessandra Faggian & Sandro Montresor, 2021. "The geography of COVID‐19 and the structure of local economies: The case of Italy," Journal of Regional Science, Wiley Blackwell, vol. 61(2), pages 407-441, March.
    2. Jeff Goldsmith & Tomoko Kitago, 2016. "Assessing systematic effects of stroke on motor control by using hierarchical function-on-scalar regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(2), pages 215-236, February.
    3. Anton Gollwitzer & Cameron Martel & William J. Brady & Philip Pärnamets & Isaac G. Freedman & Eric D. Knowles & Jay J. Van Bavel, 2020. "Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic," Nature Human Behaviour, Nature, vol. 4(11), pages 1186-1197, November.
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