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Spatio-temporal point process models for the spread of avian influenza virus (H5N1)

  • Author(s): Kim, Harry
  • Advisor(s): Yu, Bin
  • Kaufman, Cari
  • et al.
Abstract

An outbreak of the devastating avian influenza virus (H5N1) was first observed in China in 1996. The explosive re-emergence of the virus after 7 years of its debut is estimated to be responsible for 14 million poultry deaths globally. Our research aims to identify the key factors (such as promixities to cities and roads and temperature) that are associated with the spread of H5N1 in Turkey and quantify their relationships to the virus dispersal. Our statistical model, the EAI (Epidemic Avian Influenza) model, is based on self-exciting

point processes inspired by Hawkes and Ogata. A self-exciting point process can incorporate spatial and temporal dependencies of H5N1 outbreaks by specifying a branching structure among the outbreaks. In addition to quantifying the relationship between the virus spread and the key factors, the estimation result of the EAI model is used to predict future flu occurences.

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