A cellular automata to model epidemics

Autores
López, L; Burguener, G.; Giovanini, Leonardo L.; Baldomenico, P.
Año de publicación
2013
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Compartmental models are very popular in epidemiology, they provide excellent results when the populations satisfy certain hypotheses as large population size or population homogeneity, the complexity of this models is low making their analysis intuitive. In the other hand, they ignore important factors inherent to the problem, such as the nature of contacts between individuals and population heterogeneity. Cellular automata models are adequate to describe natural systems consisting of a massive collection of simple objects. They represent the global system behavior as a colection of simpler objects or cells. In this paper we propouse a cellular automata model to study the time evolution of a heterogeneous population through the various stages of disease resulting from the individuals interactions (epidemic). We validate the model with real data of flu that hit Geneva (Switzerland) in 1918 and then we will test the model under different assumptions discussing the result that each has on the disease dynamics.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Cellular automata
Modell
Epidemics
Heterogeneity
Individual based model
Public health
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/93778
Acceder
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network_name_str SEDICI (UNLP)
spelling A cellular automata to model epidemicsLópez, LBurguener, G.Giovanini, Leonardo L.Baldomenico, P.Ciencias InformáticasCellular automataModellEpidemicsHeterogeneityIndividual based modelPublic healthCompartmental models are very popular in epidemiology, they provide excellent results when the populations satisfy certain hypotheses as large population size or population homogeneity, the complexity of this models is low making their analysis intuitive. In the other hand, they ignore important factors inherent to the problem, such as the nature of contacts between individuals and population heterogeneity. Cellular automata models are adequate to describe natural systems consisting of a massive collection of simple objects. They represent the global system behavior as a colection of simpler objects or cells. In this paper we propouse a cellular automata model to study the time evolution of a heterogeneous population through the various stages of disease resulting from the individuals interactions (epidemic). We validate the model with real data of flu that hit Geneva (Switzerland) in 1918 and then we will test the model under different assumptions discussing the result that each has on the disease dynamics.Sociedad Argentina de Informática e Investigación Operativa2013-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf150-161http://sedici.unlp.edu.ar/handle/10915/93778enginfo:eu-repo/semantics/altIdentifier/issn/1853-1881info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:19:31Zoai:sedici.unlp.edu.ar:10915/93778Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:19:31.916SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A cellular automata to model epidemics
title A cellular automata to model epidemics
spellingShingle A cellular automata to model epidemics
López, L
Ciencias Informáticas
Cellular automata
Modell
Epidemics
Heterogeneity
Individual based model
Public health
title_short A cellular automata to model epidemics
title_full A cellular automata to model epidemics
title_fullStr A cellular automata to model epidemics
title_full_unstemmed A cellular automata to model epidemics
title_sort A cellular automata to model epidemics
dc.creator.none.fl_str_mv López, L
Burguener, G.
Giovanini, Leonardo L.
Baldomenico, P.
author López, L
author_facet López, L
Burguener, G.
Giovanini, Leonardo L.
Baldomenico, P.
author_role author
author2 Burguener, G.
Giovanini, Leonardo L.
Baldomenico, P.
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Cellular automata
Modell
Epidemics
Heterogeneity
Individual based model
Public health
topic Ciencias Informáticas
Cellular automata
Modell
Epidemics
Heterogeneity
Individual based model
Public health
dc.description.none.fl_txt_mv Compartmental models are very popular in epidemiology, they provide excellent results when the populations satisfy certain hypotheses as large population size or population homogeneity, the complexity of this models is low making their analysis intuitive. In the other hand, they ignore important factors inherent to the problem, such as the nature of contacts between individuals and population heterogeneity. Cellular automata models are adequate to describe natural systems consisting of a massive collection of simple objects. They represent the global system behavior as a colection of simpler objects or cells. In this paper we propouse a cellular automata model to study the time evolution of a heterogeneous population through the various stages of disease resulting from the individuals interactions (epidemic). We validate the model with real data of flu that hit Geneva (Switzerland) in 1918 and then we will test the model under different assumptions discussing the result that each has on the disease dynamics.
Sociedad Argentina de Informática e Investigación Operativa
description Compartmental models are very popular in epidemiology, they provide excellent results when the populations satisfy certain hypotheses as large population size or population homogeneity, the complexity of this models is low making their analysis intuitive. In the other hand, they ignore important factors inherent to the problem, such as the nature of contacts between individuals and population heterogeneity. Cellular automata models are adequate to describe natural systems consisting of a massive collection of simple objects. They represent the global system behavior as a colection of simpler objects or cells. In this paper we propouse a cellular automata model to study the time evolution of a heterogeneous population through the various stages of disease resulting from the individuals interactions (epidemic). We validate the model with real data of flu that hit Geneva (Switzerland) in 1918 and then we will test the model under different assumptions discussing the result that each has on the disease dynamics.
publishDate 2013
dc.date.none.fl_str_mv 2013-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/93778
url http://sedici.unlp.edu.ar/handle/10915/93778
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1853-1881
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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150-161
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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