传染病传播的双菌株模型,具有不对称的临时免疫期和部分交叉免疫
Matthew D Johnston1, Bruce Pell1, David A Rubel1
1Department of Mathematics + Computer Science, Lawrence Technological University, 21000 W 10 Mile Rd, Southfield, MI 48075, USA.
Mathematical biosciences and engineering : MBE
|November 3, 2023
概括
病原体菌株之间的临时免疫和交叉免疫差异显著影响了它们之间的竞争. 这种数学模型解释了不同的免疫期如何导致菌株共存或排除,就像COVID-19变种所看到的那样.
科学领域:
- 流行病学和数学建模 流行病学和数学建模
- 传染病的动态传染病的动态.
背景情况:
- 了解病原体菌株竞争对于预测疾病爆发至关重要.
- 以前的模型往往简化了免疫力学,限制了它们对复杂病原体进化的预测能力.
研究的目的:
- 开发和分析一种具有不对称的临时免疫和部分交叉免疫的传染病动态的数学模型.
- 确定竞争性排斥与病原体菌株共存的条件.
- 用现实世界COVID-19变种发病率数据验证模型.
主要方法:
- 开发了一种两株数学模型,包括差异性的临时免疫期和交叉免疫.
- 采用分叉分析来确定菌株排除和共存的条件.
- 利用准稳定状态的减少模型,并使用线性稳定性,相平面分析和本迪克森-杜拉克标准分析了其动态.
- 根据Delta,Omicron和Kraken变种的COVID-19发病率数据验证的模型预测.
主要成果:
- 根据生殖数量,免疫期和交叉免疫,得出了竞争性排斥和共存的明确条件.
- 临时免疫期和交叉免疫的差异被证明可以赋予显著的竞争优势.
- 模型与COVID-19数据的验证表明,最近的变种 (例如,Omicron,Kraken) 与早期的菌株 (例如,Delta) 相比,具有更大的共存能力.
结论:
- 临时免疫持续时间和交叉免疫是控制传染病菌株竞争动态的关键因素.
- 开发的模型准确地捕捉了从早期COVID-19变种中的统治/灭绝动态向后期变种中的共存的转变.
- 这一框架为预测不断演变的病原体的流行病学轨迹提供了有价值的见解.
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