School of Mathematics and Statistics, Northwestern Polytechnical University, Shannxi 710072 Xi'an, People's Republic of China.
Department of Mathematics, Faculty of Science, Sana'a University, Sana'a, Yemen.
Chaos. 2024 Sep 1;34(9). doi: 10.1063/5.0175352.
The emergence of multi-disease epidemics presents an escalating threat to global health. In response to this serious challenge, we present an innovative stochastic susceptible-vaccinated-infected-recovered epidemic model that addresses the dynamics of two diseases alongside intricate vaccination strategies. Our novel model undergoes a comprehensive exploration through both theoretical and numerical analyses. The stopping time concept, along with appropriate Lyapunov functions, allows us to explore the possibility of a globally positive solution. Through the derivation of reproduction numbers associated with the stochastic model, we establish criteria for the potential extinction of the diseases. The conditions under which one or both diseases may persist are explained. In the numerical aspect, we derive a computational scheme based on the Milstein method. The scheme will not only substantiate the theoretical results but also facilitate the examination of the impact of parameters on disease dynamics. Through examples and simulations, we have a crucial impact of varying parameters on the system's behavior.
多疾病疫情的出现对全球健康构成了日益严重的威胁。针对这一严峻挑战,我们提出了一种创新的随机易感-接种-感染-恢复传染病模型,该模型针对两种疾病的动态以及复杂的接种策略进行了探讨。我们的新型模型通过理论和数值分析进行了全面的探索。停止时间概念以及适当的李雅普诺夫函数使我们能够探索全局正解的可能性。通过与随机模型相关的繁殖数的推导,我们建立了疾病可能灭绝的准则。解释了一种或两种疾病可能持续存在的条件。在数值方面,我们基于米尔斯坦方法推导出一个计算方案。该方案不仅将证实理论结果,还便于研究参数对疾病动态的影响。通过示例和模拟,我们研究了参数变化对系统行为的重要影响。