A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus

Marc Jornet-Sanz ^[1] ; A. Corberán-Vallet ^[1] ; F.J. Santonja ^[1] ; R.J. Villanueva ^[2]
1. [1] Universitat de València
  
  Universitat de València
  
  Valencia, España
2. [2] Universidad Politécnica de Valencia
  
  Universidad Politécnica de Valencia
  
  Valencia, España
Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 41, Nº. 1, 2017, págs. 159-176
Idioma: inglés
Enlaces
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Resumen
- Our objective in this paper is to model the dynamics of respiratory syncytial virus in the region of Valencia (Spain) and analyse the effect of vaccination strategies from a health-economic point of view. Compartmental mathematical models based on differential equations are commonly used in epidemiology to both understand the underlying mechanisms that influence disease transmission and analyse the impact of vaccination programs. However, a recently proposed Bayesian stochastic susceptible-infected-recovered-susceptible model in discrete-time provided an improved and more natural description of disease dynamics. In this work, we propose an extension of that stochastic model that allows us to simulate and assess the effect of a vaccination strategy that consists on vaccinating a proportion of newborns.