感染后死亡率的流行病学影响
Chadi M Saad-Roy1,2, Simon A Levin3, Bryan T Grenfell3,4
1Miller Institute for Basic Research in Science, University of California, Berkeley, CA, USA.
Proceedings. Biological sciences
|July 12, 2023
概括
感染后死亡率 (PIM) 可以导致传染病流行病循环,与感染期间的死亡率不同. 了解PIM和免疫力对于准确的流行病预测至关重要,特别是对于COVID-19等疾病.
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:
- 传染病可能会导致长期损伤和恢复后的死亡,这种现象被称为感染后死亡率 (PIM).
- PIM对传染病流行病的动态的影响在很大程度上是未知的.
- 长期COVID是潜在的长期健康后果和感染后死亡率的最新例子.
研究的目的:
- 使用流行病学模型调查感染后死亡率 (PIM) 对流行病动态的影响.
- 确定PIM如何影响疾病循环和稳定性,与急性感染阶段的死亡率相比.
- 评估宿主免疫强度在调节PIM对流行病影响中的作用.
主要方法:
- 开发和分析一个流行病学模型,明确纳入感染后死亡率 (PIM).
- 数学建模以检查PIM可以诱导流行病循环的条件.
- 分析PIM,宿主易感性和免疫强度之间的相互作用.
主要成果:
- 感染后的死亡率 (PIM),与感染期间的死亡率不同,可以诱导流行病循环.
- 流行病循环是由易受感染池中高死亡率和再感染动态之间的相互作用驱动的.
- 强大的免疫力降低了循环的可能性,而弱的PIM可以在与疾病引起的死亡率相互作用时产生周期性.
结论:
- 感染后死亡率 (PIM) 是一个重要的,经常被忽视的因素,可以破坏流行病的动态.
- 在宿主易感性中表征异质性,包括PIM和免疫强度,对于准确的流行病学预测至关重要.
- 对于像SARS-CoV-2这样缺乏强大的免疫力的疾病,PIM可能会驱动复杂的流行病模式,特别是在季节性影响下.
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