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Revista de Matemática Teoría y Aplicaciones

Print version ISSN 1409-2433

Rev. Mat vol.30 n.1 San José Jan./Jun. 2023

http://dx.doi.org/10.15517/rmta.v30i1.50554 

Artículo

Information quantifiers and unpredictability in the COVID-19 time-series data

Cuantificadores de información e impredictibilidad en las series temporales asociadas a la COVID-19

Victoria Vampa1 

Andres M. Kowalski2 

Marcelo Losada3 

Mariela Portesi4 

Federico Holik5 

1Universidad Nacional de La Plata, Facultad de Ingeniería, Departamento de Ciencias Basicas, Uidet Matemática Aplicada, La Plata, Argentina; victoria.vampa@ing.unlp.edu.ar

2 CONICET-UNLP, Instituto de Física La Plata (IFLP), La Plata, Argentina; kowalski@fisica.unlp.edu.ar

3Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, Córdoba, Argentina; marcelolosada@yahoo.com

4CONICET-UNLP, Instituto de Física La Plata (IFLP), La Plata, Argentina; portesi@fisica.unlp.edu.ar

5CONICET-UNLP, Instituto de Física La Plata (IFLP), La Plata, Argentina; holik@fisica.unlp.edu.ar

Abstract

We apply different information quantifiers to the study of COVID-19 time series. First, we analyze how the fact of smoothing the curves alters the informational content of the series, by applying the permutation and wavelet entropies to the series of daily new cases using a sliding-window method. In addition, to study how coupled the curves associated with daily new cases of infections and deaths are, we compute the wavelet coherence. Our results show how information quantifiers can be used to analyze the unpredictable behavior of this pandemic in the short and medium terms.

Keywords: Information theory; Permutation entropy; Statistical complexity; Bandt-Pompe methodology; Wavelet transform.

Resumen

Aplicamos diferentes cuantificadores de información al estudio de series temporales de COVID-19. En primer lugar, analizamos como el hecho de suavizar las curvas altera el contenido de información de la serie, aplicando la entropía de permutaciones y la entropía wavelet a la serie de casos diarios nuevos mediante un método de ventana móvil. Además, para estudiar que tan acopladas están las curvas asociadas con los nuevos casos diarios de infecciones y muertes, calculamos la coherencia wavelet. Nuestros resultados muestran como se pueden utilizar cuantificadores de información para analizar el comportamiento impredecible de esta pandemia en el corto y mediano plazo.

Palabras clave: Teoría de la información; Entropía de permutaciones; Complejidad estadística; Metodología de Bandt-Pompe; Transformada Wavelet.

Mathematics Subject Classification: 05C15, 05C30, 05C38, 05C51, 05C82

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Acknowledgments and funding

ML, MP and FH acknowledge support from the National Research Council (CONICET), Argentina. AMK is supported by Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CICPBA), Argentina. Financial assistance from UNLP under the projects 11/I250 and 11/X812, and from CONICET under the project PIP 519, is also acknowledged. FH was partially funded by the project “Per un’estensione semantica della Logica Computazionale Quantistica- Impatto teorico e ricadute implementative”, Regione Autonoma della Sardegna, (RAS: RASSR40341), L.R. 7/2017, annualita 2017- Fondo di

Sviluppo e Coesione (FSC) 2014-2020.

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Received: April 01, 2022; Revised: March 03, 2022; Accepted: October 18, 2022

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