Document Type
Conference Proceeding
Publication Date
2008
Abstract
To predict the spread of Avian Influenza we propose a synchronous Susceptible-Infected-Recovered-Susceptible (SIRS) Boolean network of poultry farms, using probabilistic Boolean rules. Gravity models from transportation theory are used for the probability of infection of a node in one time step, taking into account farm sizes, distances be- tween farms, and mean distance travelled by birds. Basic reproduction numbers are computed analytically and numerically. The dynamics of the network are analyzed and various statistics considered such as number of infected nodes or time until eradication of the epidemic. We conclude that mostly when large farms (eventually) become infected the epidemic is more encompassing, but for a farm that does not have a very large poultry population, the epidemic could be contained.
Recommended Citation
Kasyanov, Alexander; Kirkland, Leona; and Matache, Mihaela Teodora, "A Spatial SIRS Boolean Network Model for the Spread of H5N1 Avian Influenza Virus among Poultry Farms" (2008). Mathematics Faculty Proceedings & Presentations. 2.
https://digitalcommons.unomaha.edu/mathfacproc/2
Included in
Epidemiology Commons, Mathematics Commons, Other Public Health Commons, Poultry or Avian Science Commons
Comments
Proceedings of the Fifth International Workshop on Computational Systems Biology, WCSB 2008, p. 73-76.