Multiple sources and routes of information transmission: Implications for epidemic dynamics

Vasilis Hatzopoulos, Michael Taylor, Péter L. Simon, Istvan Z. Kiss

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

In a recent paper [20], we proposed and analyzed a compartmental ODE-based model describing the dynamics of an infectious disease where the presence of the pathogen also triggers the diffusion of information about the disease. In this paper, we extend this previous work by presenting results based on pairwise and simulation models that are better suited for capturing the population contact structure at a local level. We use the pairwise model to examine the potential of different information generating mechanisms and routes of information transmission to stop disease spread or to minimize the impact of an epidemic. The individual-based simulation is used to better differentiate between the networks of disease and information transmission and to investigate the impact of different basic network topologies and network overlap on epidemic dynamics. The paper concludes with an individual-based semi-analytic calculation of R0 at the non-trivial disease free equilibrium.

Original languageEnglish
Pages (from-to)197-209
Number of pages13
JournalMathematical Biosciences
Volume231
Issue number2
DOIs
Publication statusPublished - Jun 1 2011

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Keywords

  • Epidemic
  • Information transmission
  • Network overlap
  • Pairwise models
  • Simulation

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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