Dynamics of the impact of Twitter with time delay on the spread of infectious diseases

Maoxing liu, Yuting Chang, Haiyan Wang, Benxing Li

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this paper, a mathematical model to study the impact of Twitter in controlling infectious disease is proposed. The model includes the dynamics of “tweets” which may enhance awareness of the disease and cause behavioral changes among the public, thus reducing the transmission of the disease. Furthermore, the model is improved by introducing a time delay between the outbreak of disease and the release of Twitter messages. The basic reproduction number and the conditions for the stability of the equilibria are derived. It is shown that the system undergoes Hopf bifurcation when time delay is increased. Finally, numerical simulations are given to verify the analytical results.

Original languageEnglish (US)
JournalInternational Journal of Biomathematics
DOIs
StateAccepted/In press - Jun 1 2018

Fingerprint

Infectious Diseases
Time Delay
Time delay
Basic Reproduction number
Hopf Bifurcation
Hopf bifurcation
Mathematical Model
Verify
Numerical Simulation
Mathematical models
Model
Computer simulation

Keywords

  • epidemic
  • Hopf bifurcation
  • time delay
  • Twitter

ASJC Scopus subject areas

  • Modeling and Simulation
  • Applied Mathematics

Cite this

Dynamics of the impact of Twitter with time delay on the spread of infectious diseases. / liu, Maoxing; Chang, Yuting; Wang, Haiyan; Li, Benxing.

In: International Journal of Biomathematics, 01.06.2018.

Research output: Contribution to journalArticle

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