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dc.contributor.author | Corberán-Vallet, Ana | es_ES |
dc.contributor.author | Santonja, F. | es_ES |
dc.contributor.author | Jornet-Sanz, Marc | es_ES |
dc.contributor.author | Villanueva Micó, Rafael Jacinto | es_ES |
dc.date.accessioned | 2020-05-22T03:02:12Z | |
dc.date.available | 2020-05-22T03:02:12Z | |
dc.date.issued | 2018-03-20 | es_ES |
dc.identifier.issn | 1076-2787 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/144078 | |
dc.description.abstract | [EN] We present a Bayesian stochastic susceptible-exposed-infectious-recovered model in discrete time to understand chickenpox transmission in the Valencian Community, Spain. During the last decades, different strategies have been introduced in the routine immunization program in order to reduce the impact of this disease, which remains a public health's great concern. Under this scenario, a model capable of explaining closely the dynamics of chickenpox under the different vaccination strategies is of utter importance to assess their effectiveness. The proposed model takes into account both heterogeneous mixing of individuals in the population and the inherent stochasticity in the transmission of the disease. As shown in a comparative study, these assumptions are fundamental to describe properly the evolution of the disease. The Bayesian analysis of the model allows us to calculate the posterior distribution of the model parameters and the posterior predictive distribution of chickenpox incidence, which facilitates the computation of point forecasts and prediction intervals. | es_ES |
dc.description.sponsorship | This work has been supported by a research grant from the Spanish Ministry of Economy and Competitiveness (MTM2017-83850-P). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | John Wiley & Sons | es_ES |
dc.relation.ispartof | Complexity | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Modeling Chickenpox Dynamics with a Discrete Time Bayesian Stochastic Compartmental Model | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1155/2018/3060368 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-83850-P/ES/PREDICCION Y OPTIMIZACION BAJO INCERTIDUMBRE: MODELOS ESTOCASTICOS DINAMICOS Y APLICACIONES (2)/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Corberán-Vallet, A.; Santonja, F.; Jornet-Sanz, M.; Villanueva Micó, RJ. (2018). Modeling Chickenpox Dynamics with a Discrete Time Bayesian Stochastic Compartmental Model. Complexity. 1-9. https://doi.org/10.1155/2018/3060368 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1155/2018/3060368 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 9 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | S\363084 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
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