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Ergodic stationary distribution and practical application of a hybrid stochastic cholera transmission model with waning vaccine-induced immunity under nonlinear regime switching

  • China University of Petroleum (East China)
  • King Abdulaziz University
  • Quaid-I-Azam University

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Considering the effect of stochasticity including white noise and colored noise, this paper aims to study a hybrid stochastic cholera epidemic model with waning vaccine-induced immunity and nonlinear telegraph perturbations. First, we derive a critical value (Formula presented.) related to the basic reproduction number (Formula presented.) of the deterministic model. The key aim of this paper is to generalize the θ-stochastic criterion method proposed by the recent work (Han et al. in Chaos Solit Fract 140:110238, 2020) to eliminate nonlinear telegraph perturbations. Next, via constructing several θ-stochastic Lyapunov functions and using the generalized method, we further prove that the stochastic model have a unique ergodic stationary distribution under (Formula presented.). Results show that the prevention and control of cholera epidemic depend on low transmission rate and small telegraph perturbations. Finally, the corresponding numerical simulations are performed to illustrate our analytical results and a practical application on the Somalia cholera outbreak is shown at the end of this paper.

Original languageEnglish
Pages (from-to)423-455
Number of pages33
JournalMathematical Methods in the Applied Sciences
Volume45
Issue number1
DOIs
StatePublished - 15 Jan 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Somalia cholera outbreak
  • ergodicity
  • generalized θ-stochastic criterion method
  • hybrid stochastic cholera epidemic model
  • nonlinear telegraph perturbations
  • stationary distribution

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