English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We use data from 107 Italian provinces to characterize and compare mortalitypatterns in the first two COVID-19 epidemic waves, which occurred prior to theintroduction of vaccines. We also associate these patterns with mobility,timing of government restrictions, and socio-demographic, infrastructural, andenvironmental covariates. Notwithstanding limitations in the accuracy andreliability of publicly available data, we are able to exploit information incurves and shapes through Functional Data Analysis techniques. Specifically, wedocument differences in magnitude and variability between the two waves; whileboth were characterized by a co-occurrence of 'exponential' and 'mild'mortality patterns, the second spread much more broadly and asynchronouslythrough the country. Moreover, we find evidence of a significant positiveassociation between local mobility and mortality in both epidemic waves andcorroborate the effectiveness of timely restrictions in curbing mortality. Thetechniques we describe could capture additional signals of interest if applied,for instance, to data on cases and positivity rates. However, we show that thequality of such data, at least in the case of Italian provinces, was too poorto support meaningful analyses.

Contrasting pre-vaccine COVID-19 waves in Italy through Functional Data Analysis