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<p>Considering the critical role of pine trees as forest carbon sink components in addressing climate change and achieving carbon peak and carbon neutrality goals, against the backdrop of intensifying global warming, this paper establishes a stochastic pine wilt disease transmission model incorporating logarithmic Ornstein-Uhlenbeck processes and general incidence rates. First, the global dynamics of the deterministic model are proven. Second, the existence and uniqueness of the global positive solution of the stochastic model are proved, and a sufficient criterion for disease extinction is obtained. Furthermore, we establish sufficient conditions for the existence of a stationary distribution and derive an analytical expression for the probability density function in the vicinity of the quasi-endemic equilibrium. In the numerical simulation section, the research model effectively fitted the actual data of pine wilt disease in China, estimated the basic reproduction number, and proposed new disease control strategies.</p>

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Stochastic mathematical modeling and data fitting for pine wilt disease prevention and control: a case study in China

  • 期刊论文

  • 发表日期：

    2026年1月28日

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  • Xiaohu Liu,
  • Linfei Nie

摘要

Considering the critical role of pine trees as forest carbon sink components in addressing climate change and achieving carbon peak and carbon neutrality goals, against the backdrop of intensifying global warming, this paper establishes a stochastic pine wilt disease transmission model incorporating logarithmic Ornstein-Uhlenbeck processes and general incidence rates. First, the global dynamics of the deterministic model are proven. Second, the existence and uniqueness of the global positive solution of the stochastic model are proved, and a sufficient criterion for disease extinction is obtained. Furthermore, we establish sufficient conditions for the existence of a stationary distribution and derive an analytical expression for the probability density function in the vicinity of the quasi-endemic equilibrium. In the numerical simulation section, the research model effectively fitted the actual data of pine wilt disease in China, estimated the basic reproduction number, and proposed new disease control strategies.