2020 •
Covid-19 Signal Analysis: Effect of Lockdown and Unlockdowns on Normalized Entropy in Italy
Authors:
Francesco Benedetto, Gaetano Giunta, Chiara Losquadro, Luca Pallotta
Abstract:
Entropy concept is related to uncertainty and predictability of random time series. The estimated trend of such a parameter can provide useful information and possibly predict future behavior of a number of non-stationary noisy signals. The goal of this paper consists of analyzing the Covid19 signal made by the number of registered infections in Italy during the first four months of the pandemic epidemy (March-June 2020). Finally, some considerations are drawn after matching historical dates of some Covid-19 related Acts made by the Italian Gov (...)
Entropy concept is related to uncertainty and predictability of random time series. The estimated trend of such a parameter can provide useful information and possibly predict future behavior of a number of non-stationary noisy signals. The goal of this paper consists of analyzing the Covid19 signal made by the number of registered infections in Italy during the first four months of the pandemic epidemy (March-June 2020). Finally, some considerations are drawn after matching historical dates of some Covid-19 related Acts made by the Italian Government (i.e., lockdown and unlockdowns). Based on the obtained results, we could conjecture that the provisions have inducted people to a common behavior concerning local mobility during the lockdowns and the progressive unlockdowns of the quarantine period in Italy. (Read More)
Francesco Benedetto, Gaetano Giunta, Chiara Losquadro, Luca Pallotta
2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) ·
2020
Econometrics |
Statistics |
Statistical physics |
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