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  • 标题:Bayesian inference for an emerging arboreal epidemic in the presence of control
  • 本地全文:下载
  • 作者:Matthew Parry ; Gavin J. Gibson ; Stephen Parnell
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2014
  • 卷号:111
  • 期号:17
  • 页码:6258-6262
  • DOI:10.1073/pnas.1310997111
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:The spread of Huanglongbing through citrus groves is used as a case study for modeling an emerging epidemic in the presence of a control. Specifically, the spread of the disease is modeled as a susceptible-exposed-infectious-detected-removed epidemic, where the exposure and infectious times are not observed, detection times are censored, removal times are known, and the disease is spreading through a heterogeneous host population with trees of different age and susceptibility. We show that it is possible to characterize the disease transmission process under these conditions. Two innovations in our work are (i) accounting for control measures via time dependence of the infectious process and (ii) including seasonal and host age effects in the model of the latent period. By estimating parameters in different subregions of a large commercially cultivated orchard, we establish a temporal pattern of invasion, host age dependence of the dispersal parameters, and a close to linear relationship between primary and secondary infectious rates. The model can be used to simulate Huanglongbing epidemics to assess economic costs and potential benefits of putative control scenarios.
  • 关键词:spatiotemporal model ; dispersal kernel ; stochastic model
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