延迟人口行为适应与疾病传播动态相结合的更新方程:多波新兴感染的机制
Xue Zhang1, Francesca Scarabel2, Kumar Murty3
1Department of Mathematics, Northeastern University, Shenyang 110819, China.
Mathematical biosciences
|September 16, 2023
概括
人口行为变化和推迟实施这些变化可能会导致传染病爆发的反复发生. 数学建模表明,延迟适应可能导致感染数量波动,有时超过最初的峰值.
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:
- 新兴传染病的反复爆发构成了重大的公共卫生挑战.
- 了解这些重复模式的驱动因素对于有效的疾病控制至关重要.
研究的目的:
- 开发一个数学模型来解释反复发生的传染病爆发.
- 调查人口行为适应和实施延迟对疫情动态的影响.
主要方法:
- 开发了一个数学传输动态模型.
- 该模型结合了人口行为适应灵活性和实施延迟.
- 用一个更新方程来建模有效的联系.
主要成果:
- 行为变化实施的关键延迟可能导致感染人数的波动.
- 振荡的幅度受到人口行为适应灵活性的影响.
- 随后的感染峰值可能会超过最初的峰值.
结论:
- 人口的行为适应和实施延迟是导致传染病爆发的关键因素.
- 这些发现为COVID-19大流行期间观察到的爆发模式提供了部分解释.
- 数学建模提供了对由人类行为驱动的疾病动态的见解.
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