ArticleClinical cardiology2026
Mortality Related to Different Circulatory Diseases Before, During and After the COVID-19 Pandemic.
Article in Clinical cardiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Mortality Related to Different Circulatory Diseases Before, During and After the COVID-19 Pandemic.Clinical cardiology · 2026Article
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4 authors.
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Abstract
backgroundThe COVID-19 pandemic caused a global rise in cardiovascular mortality. In Italy, a large excess deaths from ischemic heart disease (IHD), cerebrovascular disease (CVD), hypertensive diseases (HD), and atrial fibrillation (AF) was observed early during the pandemic. Whether mortality has since returned to pre-pandemic levels remains uncertain.
methodsThis study analyzed mortality data for residents aged ≥ 40 in the Veneto Region, Italy, using multiple causes of death (MCOD) from death certificates. Age-standardized monthly mortality rates were computed for IHD, CVD, HD, and AF. Forecasts for 2023 were generated using two scenarios: excluding the pandemic period (2008-2019) and including it (2008-2022). Seasonal ARIMA and Lee-Carter models were applied, and observed 2023 rates were compared with forecasts.
resultsIn 2020, all circulatory disease categories showed a mortality peak, especially HD (+29%). Although rates decreased in 2021-2022, they remained significantly above pre-pandemic levels. In 2023, observed rates for all conditions were close to those forecasted using the 2008-2019 baseline. By contrast, observed rates were significantly lower than expected when using the 2008-2022 baseline. Seasonal peaks were still observed in December 2023, associated with the circulation of multiple respiratory viruses. Lee-Carter model results confirmed a general re-alignment of 2023 mortality with pre-pandemic patterns.
conclusionsBy 2023, mortality from major circulatory diseases in the Veneto Region largely returned to pre-pandemic trends, suggesting limited long-term excess mortality. The findings underscore the value of MCOD data and time-series modeling in capturing both short-term disruptions and long-term recovery patterns in population health.
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