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使用计算和数据驱动方法研究Mpox菌株动力学

Isaiah Oke Idisi¹, Kayode Oshinubi², Vigbe Benson Sewanu³

¹Department of Mathematical Sciences, Federal University of Technology, Akure PMB 704, Ondo, Nigeria.

|February 26, 2025

概括

这项研究模拟了Clade I和Clade II的Mpox (麻疹) 传播动态,发现减少接触率是控制两种病毒菌株的关键. 数学洞察力揭示了影响传播的菌株特定因素.

科学领域:

流行病学流行病学
数学生物学数学生物学
病毒学病毒学

背景情况:

马波克斯疫情涉及多种病毒株,需要细微的传播模型.
了解菌株特异性动态对于有效的公共卫生干预至关重要.

研究的目的:

开发和验证Mpox传输动态的数据驱动数学模型.
分析两种Mpox菌群 (第I类和第II类) 对传播模式的影响.
通过检查基本繁殖数 (R0) 和接触率来评估控制策略.

主要方法:

使用一个分区流行病学模型 (易受感染,暴露,传染,住院,康复) 结合了人与哺乳动物之间的传播和两个Mopox类.
使用来自西班牙,意大利,尼日利亚和刚果民主共和国 (2022-2024) 的每周世卫组织数据,通过非线性最小平方匹配和根平均平方误差 (RMSE) 验证了该模型.
执行时间序列分析,场景模拟,以及对模型属性的数学分析 (积极性,边界性,稳定性).

主要成果:

模型模拟表明,有效接触率的增加导致特定国家普遍存在的Mpox菌群占主导地位.
菌株特异性动态和感染比例显著影响基本繁殖数 (R0).
数学模型与统计模型相比显示出更好的适应性,突出显示了类特定分析的重要性.

结论:

有效控制Mpox需要针对减少有效接触率的战略,以减轻两种类型的传播.
菌株特异性建模为Mpox流行病学提供了关键的见解,并告知了有针对性的公共卫生反应.
这项研究为分析不同种群中多菌株病原体动态提供了一个强大的框架.

关键词:

马波克斯传输动态传输动态基于数据的建模.数学建模的数学建模场景模拟的场景模拟.统计学配件统计学配件菌株特定的流行病学.

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