Classification of weekly provincial overall age- and gender-specific mortality patterns during the COVID-19 epidemics in Italy.

Abstract

to provide a time-varying classification of the Italian provinces based on the weekly age- and gender-specific relative risks (RR) for overall mortality, obtained comparing the number of deaths from 13 weeks from the beginning of the COVID-19 epidemics, with the average number of deaths from the same period in 2015-19. population overall mortality data provided by the Italian National Statistical Office (Istat). Italian residents 60 years or older from 7,357/7,904 Italian municipalities. For the included municipalities, the number of deaths from any cause from 1 January to 30 May 2020 was available for each day of the 2015-2020 period. Data were stratified by gender, 4 age categories (60-69, 70-79, 80-89, 90+), week, and province. province- and gender-specific weekly RR curves (age category vs RR), obtained for 13 weeks between 26 February and 26 May; excess mortality; time-varying/weekly classification of provinces. these results provide a weekly classification of the Italian provinces based on their RR curves in 5 groups, 2 of which had high and very high excess mortality during the epidemics. Most of the provinces that appeared at least once in the highest-risk group are neighbouring provinces in the Northern Regions of Lombardy, Emilia-Romagna, Piedmont, and Marche (in central Italy), where most of the COVID-19 cases and deaths were identified. Temporally, most of these provinces remained in the highest-risk group for 4 or 5 weeks; those that entered the group later, improved faster. The overall RR curves for groups differed in magnitude, but also in the shape, which varied markedly also between men and women and, most importantly, in the highest-risk group. this study gives timely re-analysis of the Istat data at weekly level and provides a classification of the geographical and temporal characteristics of the excess mortality in the Italian provinces during the COVID-19 epidemics. As expected, the used clustering method groups the provinces that have similar RR values in the two gender-specific curves. The results facilitate the presentation of the spatio-temporal mortality patterns of the epidemics and provide evidence of high heterogeneity in the group of provinces that were defined as high-risk groups by others, based on their geographical position or on the time of the observed spread of the virus.