Výsledky vyhledávání - "Bonifazi, Gianluca"

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A statistical model to identify excess mortality in Italy in the period 2011-2022

Autor: Bella, Antonino, Bonifazi, Gianluca, Lista, Luca, Menasce, Dario, Mezzetto, Mauro, Pedrini, Daniele, Pezzotti, Patrizio, Rota, Maria Cristina, Spighi, Roberto, Zoccoli, Antonio

Publikováno v: Eur. Phys. J. Plus (2024) 139:348

Excess mortality is defined as an increase in the number of deaths above what is expected based on historical trends, hereafter called baseline. In a previous paper, we introduced a statistical method that allows an unbiased and robust determination

Externí odkaz: http://arxiv.org/abs/2404.06111

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Study on the effects of the restrictive measures for containment of the COVID-19 pandemic on the reproduction number $R_t$ in Italian regions

Autor: Bonifazi, Gianluca, Lista, Luca, Menasce, Dario, Mezzetto, Mauro, Pedrini, Daniele, Spighi, Roberto, Zoccoli, Antonio

Since November 6$^{\mathrm{th}}$, 2020, Italian regions have been classified according to four levels, corresponding to specific risk scenarios, for which specific restrictive measures have been foreseen. By analyzing the time evolution of the reprod

Externí odkaz: http://arxiv.org/abs/2106.02603

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Akademický článek

A model-agnostic, network theory-based framework for supporting XAI on classifiers

Autor: Bonifazi, Gianluca, Cauteruccio, Francesco, Corradini, Enrico, Marchetti, Michele, Terracina, Giorgio, Ursino, Domenico, Virgili, Luca

Publikováno v: In Expert Systems With Applications 1 May 2024 241

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A statistical analysis of death rates in Italy for the years 2015-2020 and a comparison with the casualties reported for the COVID-19 pandemic

Autor: Bonifazi, Gianluca, Lista, Luca, Menasce, Dario, Mezzetto, Mauro, Oliva, Alberto, Pedrini, Daniele, Spighi, Roberto, Zoccoli, Antonio

We analyze the data about casualties in Italy in the period 01/01/2015 to 30/09/2020 released by the Italian National Institute of Statistics (ISTAT). The data exhibit a clear sinusoidal behavior, whose fit allows for a robust subtraction of the base

Externí odkaz: http://arxiv.org/abs/2102.01629

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A study on the possible merits of using symptomatic cases to trace the development of the COVID-19 pandemic

Autor: Bonifazi, Gianluca, Lista, Luca, Menasce, Dario, Mezzetto, Mauro, Pedrini, Daniele, Spighi, Roberto, Zoccoli, Antonio

In a recent work we introduced a novel method to compute the effective reproduction number $R_t$ and we applied it to describe the development of the COVID-19 outbreak in Italy. The study is based on the number of daily positive swabs as reported by

Externí odkaz: http://arxiv.org/abs/2101.01414

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A simplified estimate of the Effective Reproduction Number $R_t$ using its relation with the doubling time and application to Italian COVID-19 data

Autor: Bonifazi, Gianluca, Lista, Luca, Menasce, Dario, Mezzetto, Mauro, Pedrini, Daniele, Spighi, Roberto, Zoccoli, Antonio

Publikováno v: The European Physical Journal Plus, 136(4), 1-14, April 11th 2021

A simplified method to compute $R_t$, the Effective Reproduction Number, is presented. The method relates the value of $R_t$ to the estimation of the doubling time performed with a local exponential fit. The condition $R_t = 1$ corresponds to a growt

Externí odkaz: http://arxiv.org/abs/2012.05194

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