Literature DB >> 32398936

Using symbolic networks to analyse dynamical properties of disease outbreaks.

José L Herrera-Diestra1,2, Javier M Buldú3,4,5, Mario Chavez6, Johann H Martínez1,3,7.   

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.
© 2020 The Author(s).

Keywords:  complex networks; entropy; epidemics; ordinal patterns; time series

Year:  2020        PMID: 32398936      PMCID: PMC7209146          DOI: 10.1098/rspa.2019.0777

Source DB:  PubMed          Journal:  Proc Math Phys Eng Sci        ISSN: 1364-5021            Impact factor:   2.704


  11 in total

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Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  2000-08

2.  Permutation entropy: a natural complexity measure for time series.

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Journal:  Phys Rev Lett       Date:  2007-10-12       Impact factor: 9.161

4.  Forbidden patterns in financial time series.

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5.  From time series to complex networks: the visibility graph.

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Journal:  Proc Natl Acad Sci U S A       Date:  2008-03-24       Impact factor: 11.205

Review 6.  Ordinal symbolic analysis and its application to biomedical recordings.

Authors:  José M Amigó; Karsten Keller; Valentina A Unakafova
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2015-02-13       Impact factor: 4.226

Review 7.  Next-Generation Machine Learning for Biological Networks.

Authors:  Diogo M Camacho; Katherine M Collins; Rani K Powers; James C Costello; James J Collins
Journal:  Cell       Date:  2018-06-07       Impact factor: 41.582

8.  Detection of time reversibility in time series by ordinal patterns analysis.

Authors:  J H Martínez; J L Herrera-Diestra; M Chavez
Journal:  Chaos       Date:  2018-12       Impact factor: 3.642

9.  A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.

Authors:  Patrick Aboagye-Sarfo; Qun Mai; Frank M Sanfilippo; David B Preen; Louise M Stewart; Daniel M Fatovich
Journal:  J Biomed Inform       Date:  2015-07-04       Impact factor: 6.317

10.  Functional brain networks reveal the existence of cognitive reserve and the interplay between network topology and dynamics.

Authors:  Johann H Martínez; María Eugenia López; Pedro Ariza; Mario Chavez; José A Pineda-Pardo; David López-Sanz; Pedro Gil; Fernando Maestú; Javier M Buldú
Journal:  Sci Rep       Date:  2018-07-12       Impact factor: 4.379

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