Publicação: EPIGUI: Graphical User Interface for Simulating Epidemics on Networks
dc.contributor.author | Pinto, E. R. [UNESP] | |
dc.contributor.author | Nepomuceno, E. G. | |
dc.contributor.author | Kusak, J. | |
dc.contributor.author | Campanharo, A. S. L. O. [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.contributor.institution | Maynooth University | |
dc.contributor.institution | AGH University of Science and Technology | |
dc.date.accessioned | 2023-07-29T11:14:59Z | |
dc.date.available | 2023-07-29T11:14:59Z | |
dc.date.issued | 2023-03-27 | |
dc.description.abstract | This paper presents a graphical interface called EPIGUI, which allows the study of the dynamics of an infectious disease spread using compartmental models in combination with complex networks. This interface aims at considering stochastic factors that govern the evolution of an infection in a network. Moreover, it provides simple tools to create networks of agents and to define the epidemiological parameters of outbreaks. There are six common infectious disease models (SI, SIS, SIR, SIRS, SEIR, and SEIRS) or a user can provide another model, combining compartments. Moreover, in the simulations the user can either include a synthetic network generated according to a network model (random, small-world, scalefree, modular, or hierarchical) or a real network. This approach can help understand the paths followed by outbreaks in a given community and design new strategies to prevent and to control them. | en |
dc.description.affiliation | São Paulo State University, Institute of Biosciences | |
dc.description.affiliation | Maynooth University, Centre for Ocean Energy Research and Department of Electronic Engineering | |
dc.description.affiliation | AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications | |
dc.description.affiliationUnesp | São Paulo State University, Institute of Biosciences | |
dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorshipId | CAPES: 1770124 | |
dc.description.sponsorshipId | FAPESP: 2018/25358-9 | |
dc.format.extent | 91-120 | |
dc.identifier | http://dx.doi.org/10.5540/tcam.2022.024.01.00091 | |
dc.identifier.citation | Trends in Computational and Applied Mathematics. Sociedade Brasileira de Matemática Aplicada e Computacional - SBMAC, v. 24, n. 1, p. 91-120, 2023. | |
dc.identifier.doi | 10.5540/tcam.2022.024.01.00091 | |
dc.identifier.file | S2676-00292023000100091.pdf | |
dc.identifier.issn | 2676-0029 | |
dc.identifier.scielo | S2676-00292023000100091 | |
dc.identifier.uri | http://hdl.handle.net/11449/244895 | |
dc.language.iso | eng | |
dc.publisher | Sociedade Brasileira de Matemática Aplicada e Computacional - SBMAC | |
dc.relation.ispartof | Trends in Computational and Applied Mathematics | |
dc.rights.accessRights | Acesso aberto | |
dc.source | SciELO | |
dc.subject | agent-based model | en |
dc.subject | complex networks | en |
dc.subject | infectious diseases | en |
dc.subject | computational graphical interface | en |
dc.title | EPIGUI: Graphical User Interface for Simulating Epidemics on Networks | en |
dc.type | Artigo | |
dspace.entity.type | Publication | |
unesp.author.orcid | 0000-0001-5057-6911[1] | |
unesp.author.orcid | 0000-0002-5841-2193[2] | |
unesp.author.orcid | 0000-0002-0501-5303[4] |
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