Stochastic Reproduction Number and Ergodicity of a Saturated-Incidence SIHR Rumor Model with Optimal Control

This paper develops a stochastic susceptible–infected–hesitating–removed (SIHR) rumor model with Hill-type saturated incidence and compartment-specific Brownian perturbations. The model focuses on when environmental noise changes a rumor’s deterministic fate and how long-run behavior is organized as an invariant law rather than a fixed level. The hesitating class is interpreted as a post-spreading verification state: users have already engaged with the rumor but temporarily suspend further forwarding before removal. A corrected stochastic local reproduction number is derived from the logarithmic growth rate of the linearized spreader equation along the stochastic rumor-free boundary. Its Itô correction includes the second moment of the susceptible boundary process and therefore depends on the common attrition noise. Global existence and positivity are established from linear-growth and positive-invariance arguments, and the deterministic skeleton is shown to be well-posed, positive, bounded, and globally attracted to the endemic equilibrium when R0>1. Under explicit dissipativity and comparison assumptions, a Foster–Lyapunov argument with the full diffusion covariance matrix yields positive Harris recurrence, a unique invariant probability measure, and an ergodic time-average theorem. A media-debunking control problem is formulated through the stochastic maximum principle, while the implemented numerical schedule is stated as a drift-level open-loop approximation and then evaluated under the full stochastic dynamics. Numerical experiments, including 95% confidence bands, strong-saturation tests, stationary-density diagnostics, sensitivity surfaces, and control comparisons, support the revised threshold, recurrence, and intervention interpretations.

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Publication Details

Journal
Mathematics
Published
2026-09-14
DOI
https://doi.org/10.3390/math14183331
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
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article

Stochastic Reproduction Number and Ergodicity of a Saturated-Incidence SIHR Rumor Model with Optimal Control

Wenkang Zhang, Danni Yang
Mathematics
Mathematical and Theoretical Epidemiology and Ecology Models
article

Stochastic Reproduction Number and Ergodicity of a Saturated-Incidence SIHR Rumor Model with Optimal Control

Wenkang Zhang, Danni Yang
article en

Abstract

This paper develops a stochastic susceptible–infected–hesitating–removed (SIHR) rumor model with Hill-type saturated incidence and compartment-specific Brownian perturbations. The model focuses on when environmental noise changes a rumor’s deterministic fate and how long-run behavior is organized as an invariant law rather than a fixed level. The hesitating class is interpreted as a post-spreading verification state: users have already engaged with the rumor but temporarily suspend further forwarding before removal. A corrected stochastic local reproduction number is derived from the logarithmic growth rate of the linearized spreader equation along the stochastic rumor-free boundary. Its Itô correction includes the second moment of the susceptible boundary process and therefore depends on the common attrition noise. Global existence and positivity are established from linear-growth and positive-invariance arguments, and the deterministic skeleton is shown to be well-posed, positive, bounded, and globally attracted to the endemic equilibrium when R0>1. Under explicit dissipativity and comparison assumptions, a Foster–Lyapunov argument with the full diffusion covariance matrix yields positive Harris recurrence, a unique invariant probability measure, and an ergodic time-average theorem. A media-debunking control problem is formulated through the stochastic maximum principle, while the implemented numerical schedule is stated as a drift-level open-loop approximation and then evaluated under the full stochastic dynamics. Numerical experiments, including 95% confidence bands, strong-saturation tests, stationary-density diagnostics, sensitivity surfaces, and control comparisons, support the revised threshold, recurrence, and intervention interpretations.

MathematicsVol. 14(18)
The University of Sydney (AU), University of Alberta (CA), UNSW Sydney (AU)
Openalex Percentile: Top 8%
Mathematical and Theoretical Epidemiology and Ecology Models
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