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1.
Entropy (Basel) ; 26(5)2024 Apr 30.
Artículo en Inglés | MEDLINE | ID: mdl-38785646

RESUMEN

This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, including movement trends and population density. By employing a collisional model, we establish statistical relationships between entropy measures and mobility variables. Furthermore, our research addresses three primary objectives: firstly, validating the model; secondly, exploring correlations between aggregated mobility and entropy measures in comparison to five economic indicators; and finally, demonstrating the utility of entropy measures. Specifically, we provide an effective population density estimate that offers a more realistic understanding of social interactions. This estimation takes into account both movement regularities and intensity, utilizing real-time data analysis conducted during the peak period of the COVID-19 pandemic.

2.
Sci Rep ; 11(1): 23286, 2021 12 02.
Artículo en Inglés | MEDLINE | ID: mdl-34857840

RESUMEN

The reproduction number of an infectious disease, such as CoViD-19, can be described through a modified version of the susceptible-infected-recovered (SIR) model with time-dependent contact rate, where mobility data are used as proxy of average movement trends and interpersonal distances. We introduce a theoretical framework to explain and predict changes in the reproduction number of SARS-CoV-2 in terms of aggregated individual mobility and interpersonal proximity (alongside other epidemiological and environmental variables) during and after the lockdown period. We use an infection-age structured model described by a renewal equation. The model predicts the evolution of the reproduction number up to a week ahead of well-established estimates used in the literature. We show how lockdown policies, via reduction of proximity and mobility, reduce the impact of CoViD-19 and mitigate the risk of disease resurgence. We validate our theoretical framework using data from Google, Voxel51, Unacast, The CoViD-19 Mobility Data Network, and Analisi Distribuzione Aiuti.


Asunto(s)
Número Básico de Reproducción/estadística & datos numéricos , COVID-19/epidemiología , COVID-19/transmisión , Movimiento , Trazado de Contacto , Humanos , Italia/epidemiología , Modelos Teóricos , Distanciamiento Físico , Cuarentena , SARS-CoV-2 , Estados Unidos/epidemiología
3.
Chaos Solitons Fractals ; 146: 110854, 2021 May.
Artículo en Inglés | MEDLINE | ID: mdl-33746372

RESUMEN

Estimation of the prevalence of undocumented SARS-CoV-2 infections is critical for understanding the overall impact of CoViD-19, and for implementing effective public policy intervention strategies. We discuss a simple yet effective approach to estimate the true number of people infected by SARS-CoV-2, using raw epidemiological data reported by official health institutions in the largest EU countries and the USA.

4.
Phys Rev Lett ; 107(7): 078103, 2011 Aug 12.
Artículo en Inglés | MEDLINE | ID: mdl-21902433

RESUMEN

We show that the intelligence of a swarm of cooperative units (birds) emerges at criticality, as an effect of the joint action of frequent organizational collapses and of spatial correlation as extended as the flock size. The organizational collapses make the birds become independent of one another, thereby allowing the flock to follow the direction of the lookout birds. Long-range correlation violates the principle of locality, making the lookout birds transmit information on either danger or resources with a time delay determined by the time distance between two consecutive collapses.

5.
Phys Rev E Stat Nonlin Soft Matter Phys ; 82(2 Pt 1): 020102, 2010 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-20866763

RESUMEN

We study the regression to the origin of a walker driven by dynamically generated fractional Brownian motion (FBM) and we prove that when the FBM scaling, i.e., the Hurst exponent H<1/3 , the emerging inverse power law is characterized by a power index that is a compelling signature of the infinitely extended memory of the system. Strong memory effects leads to the relation H=θ/2 between the Hurst exponent and the persistent exponent θ , which is different from the widely used relation H=1-θ . The latter is valid for 1/3

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