Entropy-Based Pandemics Forecasting
Umberto Lucia, Thomas S. Deisboeck, Giulia Grisolia
Abstract
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 the epidemics or pandemics. In particular, a statistical projection of the time of maximum diffusion of infected carriers is fundamental in order to prepare healthcare systems and organise 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 the infection.
Topics & Concepts
PandemicCoronavirus disease 2019 (COVID-19)Entropy (arrow of time)EconometricsPrinciple of maximum entropyVariety (cybernetics)DiffusionProjection (relational algebra)OutbreakHealthcare systemStatistical physicsStatisticsComputer scienceData scienceGeographyHealth careEconomicsMathematicsBiologyVirologyEconomic growthInfectious disease (medical specialty)MedicinePhysicsDiseaseAlgorithmPathologyThermodynamicsQuantum mechanicsCOVID-19 epidemiological studiesComplex Systems and Time Series AnalysisStatistical Mechanics and Entropy