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Small-scale Spatial Analysis Shows the Specular Distribution of Excess Mortality Between the First and Second Wave of the COVID-19 Pandemic in Italy

Overview
Journal Public Health
Publisher Elsevier
Specialty Public Health
Date 2021 May 7
PMID 33962094
Citations 4
Authors
Affiliations
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Abstract

Objectives: The objective of the study is to compare excess mortality (EM) patterns and spatial correlation between the first and second wave of the pandemic in Lombardy, the Italian region that paid an extremely high COVID-19-related mortality toll in March and April 2020.

Study Design: We conducted a longitudinal study using municipality-level mortality data.

Methods: We investigated the patterns and spatial correlation of EM of men aged ≥75 years during the first two pandemic waves (March-April 2020 vs November 2020) of COVID-19, using the mortality data released by the Italian National Institute of Statistics. EM was estimated at the municipality level to accurately detect the critical areas within the region.

Results: The areas that were mostly hit during the first wave of COVID-19 were generally spared by the second wave: EM of men aged ≥75 years in the municipality of Bergamo plummeted from +472% in March and April to -13% in November, and in Cremona the variation was from +344% to -19%. Conversely, in November 2020 EM was higher in some areas that had been protected in the first wave of the pandemic. Spatial correlation widely corroborates these findings, as large sections of the hot spots of EM detected in the first wave of the pandemic changed into cold spots in the second wave, and vice versa.

Conclusions: Our results reveal the specular distribution of EM between the first and second wave of the pandemic, which may entail the consequences of social distancing measures and individual behaviors, local management strategies, 'harvesting' of the frailer population and, possibly, acquired immune protection. In conclusion, our findings support the need for continuous monitoring and analysis of mortality data using detailed spatial resolution.

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