基于卡普托衍生物的分数模型用于结核病传播,使用肯尼亚的真实数据
Bhamini Bhatia1, Sanjay Bhatter1, S D Purohit2
1Department of Mathematics, Malaviya National Institute of Technology Jaipur, Jaipur, India.
Scientific reports
|December 10, 2025
概括
本研究介绍了肯尼亚的分数顺序结核病 (TB) 模型,找到0.85.85的最佳分数顺序. 该模型准确地反映了现实世界结核病传播动态,并为干预策略提供了信息.
科学领域:
- 数学建模的数学建模
- 流行病学 流行病学
- 传染病的动态传染病的动态
背景情况:
- 结核病 (TB) 是全球主要的传染病杀手,不成比例地影响弱势群体.
- 现有的TB模型往往缺乏强度,无法完全捕捉复杂的传输动态.
- 需要先进的建模来指导有效的结核病控制政策.
研究的目的:
- 开发和分析一种新的结核病传播在肯尼亚的分数顺序数学模型.
- 严格调查拟议模型的基本数学属性.
- 估计模型参数并确定结核病传播的关键驱动因素.
主要方法:
- 将卡普托分数导数纳入一个分区结核病模型.
- 模型属性的分析:积极性,局限性,独特性和存在性.
- 参数估计,使用基本复制号的灵敏度分析,以及使用亚当斯-巴什福斯预测校正器方案进行数值模拟.
- 数据拟合以验证模型性能与现实世界结核病数据对比.
主要成果:
- 为了实现最佳数据对齐,确定了大约0.85的最佳分数顺序.
- 敏感性分析揭示了关键参数,这些参数显著影响了结核病传播动态.
- 分数顺序模型在匹配现实世界结核病数据方面表现出高准确性.
- 数字模拟突出了记忆效应对疾病动态的影响.
结论:
- 分数顺序结核病模型提供了更现实的疾病传播表征,并结合了记忆效应.
- 该模型的发现为优化肯尼亚的结核病控制干预和政策提供了可操作的见解.
- 通过先进的建模,及时和有针对性的干预措施对于加强结核病控制工作至关重要.
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