Using symbolic networks to analyse dynamical properties of disease outbreaks.
complex networks
entropy
epidemics
ordinal patterns
time series
Journal
Proceedings. Mathematical, physical, and engineering sciences
ISSN: 1364-5021
Titre abrégé: Proc Math Phys Eng Sci
Pays: England
ID NLM: 9891746
Informations de publication
Date de publication:
Apr 2020
Apr 2020
Historique:
received:
09
11
2019
accepted:
19
03
2020
entrez:
14
5
2020
pubmed:
14
5
2020
medline:
14
5
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 32398936
doi: 10.1098/rspa.2019.0777
pii: rspa20190777
pmc: PMC7209146
doi:
Types de publication
Journal Article
Langues
eng
Pagination
20190777Informations de copyright
© 2020 The Author(s).
Déclaration de conflit d'intérêts
We declare we have no competing interests.
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