Research article

Stationary distribution of an SVIB Cholera model with reaction-diffusion and Brownian motion

  • Published: 09 October 2025
  • MSC : 35Q92, 37H05, 92B05

  • In this study, we aimed to determine the stationary distribution of a Susceptible-Vaccine-Infected-Bacteria (SVIB) Cholera model that incorporates environmental noise and reaction-diffusion. First, we demonstrated the model's invariant set. Subsequently, a Lyapunov function was constructed to prove the existence and uniqueness of the solutions, and the model's finite-time stability was demonstrated. Furthermore, we derived the stationary distribution of the stochastic cholera model with reaction-diffusion. Finally, the theorem's results were verified through numerical simulation. Notably, the noise intensity could impact the model's stationary distribution. When the number of infected individuals and cholera bacteria decreases with reduced noise intensity, the system is characterized by a normal distribution. Therefore, appropriate measures should be taken to reduce the interference of external factors when a disease outbreak occurs.

    Citation: Kangkang Chang. Stationary distribution of an SVIB Cholera model with reaction-diffusion and Brownian motion[J]. AIMS Mathematics, 2025, 10(10): 22769-22790. doi: 10.3934/math.20251012

    Related Papers:

  • In this study, we aimed to determine the stationary distribution of a Susceptible-Vaccine-Infected-Bacteria (SVIB) Cholera model that incorporates environmental noise and reaction-diffusion. First, we demonstrated the model's invariant set. Subsequently, a Lyapunov function was constructed to prove the existence and uniqueness of the solutions, and the model's finite-time stability was demonstrated. Furthermore, we derived the stationary distribution of the stochastic cholera model with reaction-diffusion. Finally, the theorem's results were verified through numerical simulation. Notably, the noise intensity could impact the model's stationary distribution. When the number of infected individuals and cholera bacteria decreases with reduced noise intensity, the system is characterized by a normal distribution. Therefore, appropriate measures should be taken to reduce the interference of external factors when a disease outbreak occurs.



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    [1] B. Musundi, An immuno-epidemiological model linking between-host and within-host dynamics of cholera, Math. Biosci. Eng., 20 (2023), 16012–16030. https://doi.org/10.3934/mbe.2023714 doi: 10.3934/mbe.2023714
    [2] W. Yang, L. Gan, S. Liao, Stochastic analysis of cholera model with Lévy jumps, Int. J. Biomath., 2024, 2450067. https://doi.org/10.1142/S1793524524500670
    [3] A. Ghosh, P. Das, T. Chakraborty, P. Das, D. Ghosh, Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study, J. Theor. Biol., 605 (2025), 112097. https://doi.org/10.1016/j.jtbi.2025.112097 doi: 10.1016/j.jtbi.2025.112097
    [4] S. Edward, N. Nyerere, A mathematical model for the dynamics of cholera with control measures, Appl. Comput. Math., 4 (2015), 53–63. https://doi.org/10.11648/j.acm.20150402.14 doi: 10.11648/j.acm.20150402.14
    [5] U. T. Mustapha, Y. A. Maigoro, A. Yusuf, S. Qureshi, Mathematical modeling for the transmission dynamics of cholera with an optimal control strategy, Bull. Biomath., 2 (2024), 1–20. https://doi.org/10.59292/bulletinbiomath.2024001 doi: 10.59292/bulletinbiomath.2024001
    [6] C. E. Madubueze, S. C. Madubueze, S. Ajama, Bifurcation and stability analysis of the dynamics of cholera model with controls, Int. J. Math. Comput. Sci., 9 (2015), 645–651.
    [7] M. A. Safi, D. Y. Melesse, A. B. Gumel, Dynamics analysis of a multi-strain cholera model with an imperfect vaccine, Bull. Math. Biol., 75 (2013), 1104–1137. https://doi.org/10.1007/s11538-013-9845-2 doi: 10.1007/s11538-013-9845-2
    [8] S. Acharya, B. Mondal, R. K. Upadhyay, P. Das, Exploring noise-induced dynamics and optimal control strategy of iSIR cholera transmission model, Nonlinear Dyn., 112 (2024), 3951–3975. https://doi.org/10.1007/s11071-023-09221-z doi: 10.1007/s11071-023-09221-z
    [9] X. Cheng, Y. Wang, G. Huang, Global dynamics of a multiscale immuno-cholera transmission model with bacterial hyperinfectivity on complex networks, Math. Method. Appl. Sci., 48 (2025), 5920–5945. https://doi.org/10.1002/mma.10646 doi: 10.1002/mma.10646
    [10] S. Issam, K. Bouchaib, A. Labzai, G. Hicham, B. Mohamed, Mathematical modeling and optimal control strategy for a discrete-time cholera model, Commun. Math. Biol. Neurosci, 2023 (2023), 135. https://doi.org/10.28919/cmbn/8285 doi: 10.28919/cmbn/8285
    [11] J. Wang, Mathematical models for cholera dynamics–A review, Microorganisms, 10 (2022), 2358. https://doi.org/10.3390/microorganisms10122358 doi: 10.3390/microorganisms10122358
    [12] J. Luo, J. Wang, H. Wang, Seasonal forcing and exponential threshold incidence in cholera dynamics, Discrete Cont. Dyn. B, 22 (2017), 2261–2290. https://doi.org/10.3934/dcdsb.2017095 doi: 10.3934/dcdsb.2017095
    [13] Y. He, B. Bi, Threshold dynamics and density function of a stochastic cholera transmission model, AIMS Math., 9 (2024), 21918–21939. https://doi.org/10.3934/math.20241065 doi: 10.3934/math.20241065
    [14] Z. Hu, J. Li, L. Hu, L. Nie, Global dynamics of a nonlocal delayed reaction-diffusion Cholera model with phage-bacteria interaction, Nonlinear Dyn., 113 (2025), 17257–17288. https://doi.org/10.1007/s11071-025-10938-2 doi: 10.1007/s11071-025-10938-2
    [15] W. Wu, Q. Zhang, H. Wang, S. Liu, Cholera dynamics driven by human behavior change via a degenerate reaction-diffusion model, Z. Angew. Math. Phys., 76 (2025), 114. https://doi.org/10.1007/s00033-025-02495-w doi: 10.1007/s00033-025-02495-w
    [16] Z. Bai, L. Han, A partially degenerate reaction-diffusion cholera model with temporal and spatial heterogeneity, Appl. Anal., 102 (2023), 3167–3184. https://doi.org/10.1080/00036811.2022.2057302 doi: 10.1080/00036811.2022.2057302
    [17] X. Wang, R. Wu, X. Zhao, A reaction-advection-diffusion model of cholera epidemics with seasonality and human behavior change, J. Math. Biol., 84 (2022), 34. https://doi.org/10.1007/s00285-022-01733-3 doi: 10.1007/s00285-022-01733-3
    [18] C. Song, R. Xu, Wave propagation of a reaction-diffusion cholera model with hyperinfectious vibrios and spatio-temporal delay, J. Math. Phys., 65 (2024), 022706. https://doi.org/10.1063/5.0156896 doi: 10.1063/5.0156896
    [19] X. Wang, D. Posny, J. Wang, A reaction-convection-diffusion model for cholera spatial dynamics, Discrete Cont. Dyn. B, 21 (2016), 2785–2809. https://doi.org/10.3934/dcdsb.2016073 doi: 10.3934/dcdsb.2016073
    [20] S. Wang, L. Nie, Global stability and asymptotic profiles of a partially degenerate reaction diffusion Cholera model with asymptomatic individuals, Adv. Nonlinear Anal., 13 (2024), 20240059. https://doi.org/10.1515/anona-2024-0059 doi: 10.1515/anona-2024-0059
    [21] J. Wang, W. Wu, T. Kuniya, Analysis of a degenerated reaction-diffusion cholera model with spatial heterogeneity and stabilized total humans, Math. Comput. Simul., 198 (2022), 151–171. https://doi.org/10.1016/j.matcom.2022.02.026 doi: 10.1016/j.matcom.2022.02.026
    [22] J. Yang, P. Jia, J. Wang, Z. Jin, Rich dynamics of a bidirectionally linked immuno-epidemiological model for cholera, J. Math. Biol., 87 (2023), 71. https://doi.org/10.1007/s00285-023-02009-0 doi: 10.1007/s00285-023-02009-0
    [23] B. hou, D. Jiang, B. Han, T. Hayat, Ergodic stationary distribution and practical application of a hybrid stochastic cholera transmission model with waning vaccine-induced immunity under nonlinear regime switching, Math. Method. Appl. Sci., 45 (2022), 423–455. https://doi.org/10.1002/mma.7785 doi: 10.1002/mma.7785
    [24] M. Song, W. Zuo, D. Jiang, T. Hayat, Stationary distribution and ergodicity of a stochastic cholera model with multiple pathways of transmission, J. Franklin I., 357 (2020), 10773–10798. https://doi.org/10.1016/j.jfranklin.2020.04.061 doi: 10.1016/j.jfranklin.2020.04.061
    [25] X. Zhang, H. Peng, Stationary distribution of a stochastic cholera epidemic model with vaccination under regime switching, Appl. Math. Lett., 102 (2020), 106095. https://doi.org/10.1016/j.aml.2019.106095 doi: 10.1016/j.aml.2019.106095
    [26] X. Zhang, The stationary distribution of a stochastic heroin epidemic model with distributed delay, Int. J. Biomath., 2024, 2450077. https://doi.org/10.1142/S1793524524500773
    [27] W. Zuo, B. Liao, Ju. Ge, N. Zhao, D. Jiang, Ergodicity of a stationary distribution for a stochastic cholera model with a general functional response and higher-order perturbation, Adv. Cont. Discr. Mod., 2024 (2024), 57. https://doi.org/10.1186/s13662-024-03822-7 doi: 10.1186/s13662-024-03822-7
    [28] Q. Liu, D. Jiang, Stationary distribution of a stochastic cholera model with imperfect vaccination, Physica A, 550 (2020), 124031. https://doi.org/10.1016/j.physa.2019.124031 doi: 10.1016/j.physa.2019.124031
    [29] X. Mao, Stochastic differential equations and their applications, Elsevier, 2007.
    [30] K. Liu, Stationary distributions of second order stochastic evolution equations with memory in Hilbert spaces, Stoch. Proc. Appl., 130 (2020), 366–393. https://doi.org/10.1016/j.spa.2019.03.015 doi: 10.1016/j.spa.2019.03.015
    [31] K. Chang, Q. Zhang, H. Yuan, Stationary distribution and control strategy of a stochastic dengue model with spatial diffusion, J. Appl. Anal. Comput., 12 (2022), 153–178. https://doi.org/10.11948/20210094 doi: 10.11948/20210094
    [32] Z. Zhang, G. Liang, K. Chang, Stationary distribution of a reaction-diffusionhepatitis B virus infection model driven by the Ornstein-Uhlenbeck process, Plos one, 18 (2023), e0292073. https://doi.org/10.1371/journal.pone.0292073 doi: 10.1371/journal.pone.0292073
    [33] D. J. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev., 43 (2001), 525–546. https://doi.org/10.1137/S0036144500378302 doi: 10.1137/S0036144500378302
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