Entropy-Based Pandemics Forecasting

Umberto Lucia; Thomas S. Deisboeck; Giulia Grisolia

doi:10.3389/fphy.2020.00274

Frontiers in Physics (Jun 2020)

Entropy-Based Pandemics Forecasting

Umberto Lucia,
Thomas S. Deisboeck,
Giulia Grisolia

Affiliations

Umberto Lucia: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Torino, Italy
Thomas S. Deisboeck: Department of Radiology, Harvard-MIT Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
Giulia Grisolia: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Torino, Italy

DOI: https://doi.org/10.3389/fphy.2020.00274
Journal volume & issue: Vol. 8

Abstract

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A great variety of natural phenomena follows some statistical distributions. In epidemiology, such as for the current COVID 19 outbreak, it is essential to develop reliable predictions of the evolution of an infectious disease. In particular, a statistical projection of the time of maximum diffusion of infected carriers is fundamental in order to prepare healthcare systems and organize a robust public health response. In this paper, we develop a thermodynamic approach based on the infection statistics related to the total citizenry of a country. It represents a novel tool for evaluating the time of maximum diffusion of an epidemic or pandemic.

Published in Frontiers in Physics

ISSN: 2296-424X (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Science: Physics
Website: https://www.frontiersin.org/journals/physics

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