Towards a characterization of behavior-disease models.

The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Nicola Perra, Duygu Balcan, Bruno Gonçalves, Alessandro Vespignani
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/186f7a0f9cdf4d7e9fcbfdb786f2bb95
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:186f7a0f9cdf4d7e9fcbfdb786f2bb95
record_format	dspace
spelling	oai:doaj.org-article:186f7a0f9cdf4d7e9fcbfdb786f2bb952021-11-18T06:48:46ZTowards a characterization of behavior-disease models.1932-620310.1371/journal.pone.0023084https://doaj.org/article/186f7a0f9cdf4d7e9fcbfdb786f2bb952011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21826228/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself. While models lacking this coupling can be extremely successful in mild epidemics, they obviously will be of limited use in situations where social disruption or behavioral alterations are induced in the population by knowledge of the disease. Here we propose a characterization of a set of prototypical mechanisms for self-initiated social distancing induced by local and non-local prevalence-based information available to individuals in the population. We characterize the effects of these mechanisms in the framework of a compartmental scheme that enlarges the basic SIR model by considering separate behavioral classes within the population. The transition of individuals in/out of behavioral classes is coupled with the spreading of the disease and provides a rich phase space with multiple epidemic peaks and tipping points. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.Nicola PerraDuygu BalcanBruno GonçalvesAlessandro VespignaniPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 8, p e23084 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nicola Perra Duygu Balcan Bruno Gonçalves Alessandro Vespignani Towards a characterization of behavior-disease models.
description	The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself. While models lacking this coupling can be extremely successful in mild epidemics, they obviously will be of limited use in situations where social disruption or behavioral alterations are induced in the population by knowledge of the disease. Here we propose a characterization of a set of prototypical mechanisms for self-initiated social distancing induced by local and non-local prevalence-based information available to individuals in the population. We characterize the effects of these mechanisms in the framework of a compartmental scheme that enlarges the basic SIR model by considering separate behavioral classes within the population. The transition of individuals in/out of behavioral classes is coupled with the spreading of the disease and provides a rich phase space with multiple epidemic peaks and tipping points. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.
format	article
author	Nicola Perra Duygu Balcan Bruno Gonçalves Alessandro Vespignani
author_facet	Nicola Perra Duygu Balcan Bruno Gonçalves Alessandro Vespignani
author_sort	Nicola Perra
title	Towards a characterization of behavior-disease models.
title_short	Towards a characterization of behavior-disease models.
title_full	Towards a characterization of behavior-disease models.
title_fullStr	Towards a characterization of behavior-disease models.
title_full_unstemmed	Towards a characterization of behavior-disease models.
title_sort	towards a characterization of behavior-disease models.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/186f7a0f9cdf4d7e9fcbfdb786f2bb95
work_keys_str_mv	AT nicolaperra towardsacharacterizationofbehaviordiseasemodels AT duygubalcan towardsacharacterizationofbehaviordiseasemodels AT brunogoncalves towardsacharacterizationofbehaviordiseasemodels AT alessandrovespignani towardsacharacterizationofbehaviordiseasemodels
_version_	1718424336485842944

Towards a characterization of behavior-disease models.

Ejemplares similares