Noise-induced transitions in a non-smooth SIS epidemic model with media alert

Anji Yang, Baojun Song, Sanling Yuan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We investigate a non-smooth stochastic epidemic model with consideration of the alerts from media and social network. Environmental uncertainty and political bias are the stochastic drivers in our mathematical model. We aim at the interfere measures assuming that a disease has already invaded into a population. Fundamental findings include that the media alert and social network alert are able to mitigate an infection. It is also shown that interfere measures and environmental noise can drive the stochastic trajectories frequently to switch between lower and higher level of infections. By constructing the confidence ellipse for each endemic equilibrium, we can estimate the tipping value of the noise intensity that causes the state switching.

Original languageEnglish
Pages (from-to)745-763
Number of pages19
JournalMathematical Biosciences and Engineering
Volume18
Issue number1
DOIs
StatePublished - Dec 2020

Keywords

  • Confidence domains
  • Media alert
  • Noise-induced state switching
  • SIS model
  • Stochastic sensitivity

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