Dynamics properties and density function of a stochastic HBV transmission model with information dissemination and two logarithmic Ornstein–Uhlenbeck processes

Tao Chen, Xiaolin Ding, Zhiming Li and Mingzhu Yin

Mathematics and Computers in Simulation (MATCOM), 2026, vol. 248, issue C, 166-189

Abstract: This study formulates a stochastic HBV transmission model that incorporates information dissemination and logarithmic Ornstein–Uhlenbeck noise to jointly capture environmental and informational randomness. Threshold conditions for disease persistence and extinction are derived, and explicit expressions for the stationary distribution near the quasi-endemic equilibrium are obtained. Numerical simulations corroborate the theoretical results and demonstrate that stronger information dissemination effectively suppresses HBV, while randomness in information flow alters fluctuation patterns and influences the mean first-passage time to equilibrium. The results highlight the significant impact of stochastic information dynamics on HBV spread and provide quantitative and qualitative insights for intervention strategies under uncertainty.

Keywords: HBV; Information intervention; Stochastic dynamics; Ornstein–Uhlenbeck noise; Threshold analysis; Stationary distribution (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:248:y:2026:i:c:p:166-189

DOI: 10.1016/j.matcom.2026.04.009

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