Publicação: Using symbolic networks to analyse dynamical properties of disease outbreaks
dc.contributor.author | Herrera-Diestra, Jose L. [UNESP] | |
dc.contributor.author | Buldu, Javier M. | |
dc.contributor.author | Chavez, Mario | |
dc.contributor.author | Martinez, Johann H. [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.contributor.institution | Univ Los Andes | |
dc.contributor.institution | Grp Interdisciplinar Sistemas Complejos GISC | |
dc.contributor.institution | Ctr Biomed Technol UPM | |
dc.contributor.institution | Univ Rey Juan Carlos | |
dc.contributor.institution | Hop La Pitie Salpetriere | |
dc.date.accessioned | 2020-12-10T19:58:17Z | |
dc.date.available | 2020-12-10T19:58:17Z | |
dc.date.issued | 2020-04-29 | |
dc.description.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. | en |
dc.description.affiliation | Univ Estadual Paulista, Inst Fis Teor, ICTP South Amer Inst Fundamental Res, Sao Paulo, Brazil | |
dc.description.affiliation | Univ Los Andes, CeSiMo, Fac Ingn, Merida, Venezuela | |
dc.description.affiliation | Grp Interdisciplinar Sistemas Complejos GISC, Madrid, Spain | |
dc.description.affiliation | Ctr Biomed Technol UPM, Lab Biol Networks, Madrid, Spain | |
dc.description.affiliation | Univ Rey Juan Carlos, Complex Syst Grp, Mostoles, Spain | |
dc.description.affiliation | Hop La Pitie Salpetriere, CNRS, UMR7225, Paris, France | |
dc.description.affiliation | Univ Los Andes, Dept Biomed Engn, Bogota, Colombia | |
dc.description.affiliationUnesp | Univ Estadual Paulista, Inst Fis Teor, ICTP South Amer Inst Fundamental Res, Sao Paulo, Brazil | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorship | MINECO | |
dc.description.sponsorshipId | FAPESP: 2016/01343-7 | |
dc.description.sponsorshipId | FAPESP: 2017/05770-0 | |
dc.description.sponsorshipId | MINECO: FIS201784151-P | |
dc.format.extent | 18 | |
dc.identifier | http://dx.doi.org/10.1098/rspa.2019.0777 | |
dc.identifier.citation | Proceedings Of The Royal Society A-mathematical Physical And Engineering Sciences. London: Royal Soc, v. 476, n. 2236, 18 p., 2020. | |
dc.identifier.doi | 10.1098/rspa.2019.0777 | |
dc.identifier.issn | 1364-5021 | |
dc.identifier.uri | http://hdl.handle.net/11449/196854 | |
dc.identifier.wos | WOS:000530375100004 | |
dc.language.iso | eng | |
dc.publisher | Royal Soc | |
dc.relation.ispartof | Proceedings Of The Royal Society A-mathematical Physical And Engineering Sciences | |
dc.source | Web of Science | |
dc.subject | complex networks | |
dc.subject | ordinal patterns | |
dc.subject | entropy | |
dc.subject | time series | |
dc.subject | epidemics | |
dc.title | Using symbolic networks to analyse dynamical properties of disease outbreaks | en |
dc.type | Artigo | |
dcterms.rightsHolder | Royal Soc | |
dspace.entity.type | Publication | |
unesp.author.orcid | 0000-0002-3365-8189[4] | |
unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Física Teórica (IFT), São Paulo | pt |