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  • 标题:A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
  • 本地全文:下载
  • 作者:Marc Jornet-Sanz ; Ana Corberán-Vallet ; Francisco Santonja
  • 期刊名称:SORT-Statistics and Operations Research Transactions
  • 印刷版ISSN:2013-8830
  • 出版年度:2017
  • 卷号:1
  • 期号:1
  • 页码:159-176
  • 语种:English
  • 出版社:SORT- Statistics and Operations Research Transactions
  • 摘要: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.
  • 其他摘要: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.
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