Excess mortality during the COVID-19 outbreak in Italy: a two-stage interrupted time-series analysis.

Matteo Scortichini ORCID logo; Rochelle Schneider Dos Santos ORCID logo; Francesca De' Donato; Manuela De Sario; Paola Michelozzi; Marina Davoli; Pierre Masselot ORCID logo; Francesco Sera ORCID logo; Antonio Gasparrini ORCID logo; (2020) Excess mortality during the COVID-19 outbreak in Italy: a two-stage interrupted time-series analysis. International Journal of Epidemiology, 49 (6). pp. 1909-1917. ISSN 0300-5771 DOI: 10.1093/ije/dyaa169
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BACKGROUND: Italy was the first country outside China to experience the impact of the COVID-19 pandemic, which resulted in a significant health burden. This study presents an analysis of the excess mortality across the 107 Italian provinces, stratified by sex, age group and period of the outbreak. METHODS: The analysis was performed using a two-stage interrupted time-series design using daily mortality data for the period January 2015-May 2020. In the first stage, we performed province-level quasi-Poisson regression models, with smooth functions to define a baseline risk while accounting for trends and weather conditions and to flexibly estimate the variation in excess risk during the outbreak. Estimates were pooled in the second stage using a mixed-effects multivariate meta-analysis. RESULTS: In the period 15 February-15 May 2020, we estimated an excess of 47 490 [95% empirical confidence intervals (eCIs): 43 984 to 50 362] deaths in Italy, corresponding to an increase of 29.5% (95% eCI: 26.8 to 31.9%) from the expected mortality. The analysis indicates a strong geographical pattern, with the majority of excess deaths occurring in northern regions, where few provinces experienced increases up to 800% during the peak in late March. There were differences by sex, age and area both in the overall impact and in its temporal distribution. CONCLUSION: This study offers a detailed picture of excess mortality during the first months of the COVID-19 pandemic in Italy. The strong geographical and temporal patterns can be related to the implementation of lockdown policies and multiple direct and indirect pathways in mortality risk.


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