A stochastic epidemic model with time delays and unreported cases based on Markovian switching

Disease dynamics are influenced by changes in the environment. In this study, unreported cases (U), environmental perturbations, and exogenous events are included in the epidemic Susceptible–Exposed–Infectious–Unreported–Removed model with time delays. We examine the process of switching from one regime to another at random. Ergodicity and stationary distribution criteria are discussed. A Lyapunov function is used to determine several conditions for disease extinction. The spread of a disease is affected when transitioning from one random regime to another via sudden external events, such as hurricanes. The model and theoretical results are validated using numerical simulations.

Authors

Publication Details

Journal
Journal of Biosafety and Biosecurity
Published
2024-09-06
DOI
https://doi.org/10.1016/j.jobb.2024.08.002
Citations
7
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
3.80
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article

A stochastic epidemic model with time delays and unreported cases based on Markovian switching

Hebatallah J. Alsakaji, A. H. Hashish, Fathalla A. Rihan, Y.A. El-Khatib
7 citations
Journal of Biosafety and Biosecurity
Mathematical and Theoretical Epidemiology and Ecology Models
3.80
article

A stochastic epidemic model with time delays and unreported cases based on Markovian switching

Hebatallah J. Alsakaji, A. H. Hashish, Fathalla A. Rihan, Y.A. El-Khatib
article en
7 citations

Abstract

Disease dynamics are influenced by changes in the environment. In this study, unreported cases (U), environmental perturbations, and exogenous events are included in the epidemic Susceptible–Exposed–Infectious–Unreported–Removed model with time delays. We examine the process of switching from one regime to another at random. Ergodicity and stationary distribution criteria are discussed. A Lyapunov function is used to determine several conditions for disease extinction. The spread of a disease is affected when transitioning from one random regime to another via sudden external events, such as hurricanes. The model and theoretical results are validated using numerical simulations.

Journal of Biosafety and BiosecurityVol. 6(4)
Good health and well-being
Openalex Percentile: Top 6%
Mathematical and Theoretical Epidemiology and Ecology Models
3.80
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