Using symbolic networks to analyse dynamical properties of disease outbreaks-Reference-Cited by-同舟云学术

Using symbolic networks to analyse dynamical properties of disease outbreaks

Published:2020-04 Issue:2236 Volume:476 Page:20190777
ISSN:1364-5021
Container-title:Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
language:en
Short-container-title:Proc. R. Soc. A.

Author:

Herrera-Diestra José L.¹²^ORCID,Buldú Javier M.³⁴⁵,Chavez Mario⁶,Martínez Johann H.¹³⁷^ORCID

Affiliation:

1. ICTP South American Institute for Fundamental Research, Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo, Brazil

2. CeSiMo, Facultad de Ingeniería, Universidad de Los Andes, Mérida, Venezuela

3. Grupo Interdisciplinar de Sistemas Complejos (GISC), Madrid, Spain

4. Laboratory of Biological Networks, Center for Biomedical Technology - UPM, Madrid, Spain

5. Complex Systems Group, Universidad Rey Juan Carlos, Móstoles, Spain

6. CNRS UMR7225, Hôpital Pitié Salpêtrière, Paris, France

7. Department of Biomedical Engineering, Universidad de los Andes, Bogotá, Colombia

Abstract

We introduce a new methodology, which is based on the construction of epidemic networks, to analyse the evolution of epidemic time series. First, we translate the time series into ordinal patterns containing information about local fluctuations in disease prevalence. Each pattern is associated with a node of a network, whose (directed) connections arise from consecutive appearances in the series. The analysis of the network structure and the role of each pattern allows them to be classified according to the enhancement of entropy/complexity along the series, giving a different point of view about the evolution of a given disease.

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Ministerio de Economía, Industria y Competitividad, Gobierno de España

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Link

https://royalsocietypublishing.org/doi/pdf/10.1098/rspa.2019.0777

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