通过经典和分数RK4方案,对巴西的联合感染莱什曼病-查加斯病的控制政策进行建模和数值模拟
Balal Aalam1, Daniyal Ur-Rehman2, Maryam Ghaffar3
1Department of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
Computational biology and chemistry
|March 12, 2026
概括
这项研究模拟了巴西莱什曼病和查加斯病的同时感染情况,确定政策5是控制最有效的. 数学建模和数据分析为针对这些被忽视的热带疾病的公共卫生战略提供了洞察力.
科学领域:
- 流行病学 流行病学
- 数学生物学 数学生物学
- 公共卫生 公共卫生
背景情况:
- 载体传播疾病,包括莱什曼病和查加斯病,是巴西重要的公共卫生问题.
- 这些被忽视的热带疾病导致大量的人类死亡,需要有效的控制策略.
研究的目的:
- 开发和分析莱什曼病和查加斯病单一和联合感染动态的确定性数学模型.
- 评估四种不同的疾病控制干预政策的有效性.
- 探索分数顺序模型的应用,以捕捉疾病传播中的记忆效应.
主要方法:
- 对动态模型进行严格的数学分析,包括计算基本复制数 (R0LC) 和灵敏度指数.
- 使用可靠的巴西数据集和适合现实数据的模型进行参数估计.
- 整数顺序和分数顺序模型的数值模拟,以评估疾病动态和干预影响.
主要成果:
- 分析了基本繁殖数 (R0LC) 和平衡状态,以了解疾病的传播.
- 模型预测显示与实际的巴西数据有很强的一致性,验证了模型的准确性.
- 政策5被确定为减少疾病负担的最有效干预措施,得到了受控生殖数量分析的支持.
- 分数顺序模型模拟表明其适用于模拟疾病传播中的记忆效应.
结论:
- 开发的数学模型准确地代表了巴西莱什曼病和查加斯病的动态.
- 建议采取干预政策5作为控制这些被忽视的热带疾病的最有效策略.
- 分数顺序模型为理解具有记忆效应的复杂疾病传播模式提供了有价值的框架.
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