Document Detail


A Bayesian SIRS model for the analysis of respiratory syncytial virus in the region of Valencia, Spain.
MedLine Citation:
PMID:  25088210     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
We present a Bayesian stochastic susceptible-infected-recovered-susceptible (SIRS) model in discrete time to understand respiratory syncytial virus dynamics in the region of Valencia, Spain. A SIRS model based on ordinary differential equations has also been proposed to describe RSV dynamics in the region of Valencia. However, this continuous-time deterministic model is not suitable when the initial number of infected individuals is small. Stochastic epidemic models based on a probability of disease transmission provide a more natural description of the spread of infectious diseases. In addition, by allowing the transmission rate to vary stochastically over time, the proposed model provides an improved description of RSV dynamics. The Bayesian analysis of the model allows us to calculate both the posterior distribution of the model parameters and the posterior predictive distribution, which facilitates the computation of point forecasts and prediction intervals for future observations.
Authors:
Ana Corberán-Vallet; Francisco J Santonja
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-8-4
Journal Detail:
Title:  Biometrical journal. Biometrische Zeitschrift     Volume:  -     ISSN:  1521-4036     ISO Abbreviation:  Biom J     Publication Date:  2014 Aug 
Date Detail:
Created Date:  2014-8-4     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7708048     Medline TA:  Biom J     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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