ArticleInternational journal of environmental research and public health2023
Assessment of Excess Mortality in Italy in 2020-2021 as a Function of Selected Macro-Factors.
Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Excess Mortality in Türkiye during 2020-2022: Regional and Time-Based Analysis.Balkan medical journal · 2025Article
- Data from Emergency Medical Service Activities: A Novel Approach to Monitoring COVID-19 and Other Infectious Diseases.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- The spread in time and space of COVID-19 pandemic waves: the Italian experience from mortality data analyses.Frontiers in public health · 2024Article
- Mortality rates from asbestos-related diseases in Italy during the first year of the COVID-19 pandemic.Frontiers in public health · 2023Article
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4 authors.
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Abstract
backgroundExcess 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.
methodsMortality 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.
resultsThe 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.
conclusionsThe 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.
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