对呼吸道同胞病毒动态的随机延迟模型进行数学分析
Ali Raza1,2, Marek Lampart3, Umar Shafique3
1IT4Innovations, VSB-Technical University of Ostrava, 17 Listopadu 2172/15, Ostrava, Czech Republic. ali.raza@vsb.cz.
Scientific reports
|February 19, 2026
概括
一个新的随机模型增强了对呼吸道同胞病毒 (RSV) 传播动态的理解. 一种新的数值方法确保了这种常见的呼吸道感染的稳定性和准确性.
科学领域:
- 流行病学 流行病学
- 数学生物学 数学生物学
- 计算科学 计算科学
背景情况:
- 呼吸道同胞病毒 (RSV) 在全球范围内引起重大呼吸道感染.
- 了解RSV传播动态对于有效的控制策略至关重要.
- 现有的随机模型在保持动态特征方面面临着挑战.
研究的目的:
- 提出和分析生物启发的RSV传播的随机延迟模型.
- 开发一种稳定,准确的数值方法来模拟拟拟议的模型.
- 通过先进的计算建模,增强对RSV动态的理解.
主要方法:
- 为RSV开发一个生物启发的随机延迟微分方程模型.
- 对模型属性的严格数学分析:积极性,边界性,平衡性和基本复制数.
- 应用和比较传统的数值方案 (欧勒-马鲁雅马) 与一个新的随机非标准有限差异 (NSFD) 计划与延迟.
主要成果:
- 提出的随机延迟模型对其定性属性进行了严格分析.
- 传统的数值方法在保存模型动态方面存在局限性.
- 开发的随机NSFD方案证明了非负面性,局限性,一致性和无条件的趋同.
- 对比模拟证实了NSFD方法在复制准确模型动态方面的可靠性.
结论:
- 随机NSFD方案为分析延迟随机模型提供了一个稳定而准确的计算工具.
- 这一框架促进了对RSV传输动态的理解.
- 这种方法为模拟流行病学和神经生物学中的其他复杂的非线性随机过程提供了潜力.
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