具有空间扩散和非局部延迟的随机禽流感模型的指数稳定性和固定时间控制
1School of Mathematics and Statistics, Ningxia University, Yinchuan 750021, People's Republic of China.
Chaos (Woodbury, N.Y.)
|September 23, 2024
概括
本研究介绍了一种具有空间扩散和延迟的随机禽流感模型,分析其稳定性并提出疫情管理的控制策略.
科学领域:
- 流行病学 流行病学
- 数学生物学 数学生物学
- 控制理论 控制理论
背景情况:
- 禽流感疫情受到空间因素,环境随机性和疾病潜伏期的影响.
- 了解疾病动态对于有效的控制策略至关重要.
研究的目的:
- 开发和分析具有空间扩散和非局部延迟的随机敏感-传染性-敏感-感染-恢复 (SI-SIR) 禽流感模型.
- 调查模型解决方案的存在,独特性和稳定性.
- 为制禽流感疫情提出一个固定时间控制战略.
主要方法:
- 巴纳赫定点定理,截断方法和半组方法用于解决方案分析.
- 博雷尔-坎特利定理用于分析平均平方和几乎确定的指数稳定性.
- 设计固定时间控制策略的利亚普诺夫理论.
主要成果:
- 确立了温和解决方案的存在和独特性.
- 分析了模型的平均平方指数稳定性和几乎确定的指数稳定性.
- 提出了一种新的固定时间控制策略,并通过数值模拟进行验证.
结论:
- 开发的随机SI-SIR模型为考虑空间和时间因素的禽流感动态提供了洞察力.
- 稳定性分析证实了模型的稳定性.
- 拟议的控制策略为及时干预禽流感疫情提供了一个有希望的方法.
相关概念视频
Steps in Outbreak Investigation
108
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
108
Viral Mutations
32.2K
A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
32.2K
Viral Recombination
23.3K
Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
23.3K
Linear Approximation in Time Domain
70
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
70


