Bayesian inference for an emerging arboreal epidemic in the presence of control

Matthew Parry, Gavin Jarvis Gibson, Stephen Parnell, Tim R. Gottwald, Michael S. Irey, Timothy C. Gast, Christopher A. Gilligan

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)6258-6262
Number of pages5
JournalProceedings of the National Academy of Sciences
Volume111
Issue number17
DOIs
Publication statusPublished - 29 Apr 2014

Keywords

  • spatiotemporal model
  • dispersal kernel
  • stochastic model
  • SPATIOTEMPORAL STOCHASTIC-MODELS
  • INFECTIOUS-DISEASES
  • PLANT EPIDEMIOLOGY
  • POPULATIONS
  • CITRUS
  • TRANSMISSION
  • SPREAD
  • RATES

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