Using symbolic networks to analyse dynamical properties of disease outbreaks
arXiv:1911.05646 · doi:10.1098/rspa.2019.0777
Abstract
We introduce a new methodology to analyze the evolution of epidemic time series, which is based on the construction of epidemic networks. First, we translate the time series into ordinal patterns containing information about local fluctuations of the disease prevalence. Each pattern is associated to 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 classifying them according to the enhancement of entropy/complexity along the series, giving a different point of view about the evolution of a given disease.
20 pages, 10 figures
References in corpus (8)
- From time series to complex networks: the visibility graph
- Complex network approaches to nonlinear time series analysis
- Combining complex networks and data mining: why and how
- Forbidden patterns in financial time series
- Visibility graphs for image processing
- Detection of time reversibility in time series by ordinal patterns analysis
- Quantifying sudden changes in dynamical systems using symbolic networks
- Permutation complexity of interacting dynamical systems