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实时测量疾病传染性,使用温度依赖的生成间隔进行实时测量
Esther Li Wen Choo1, Kris V Parag2, Jo Yi Chow1
1Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
PLoS computational biology
|January 21, 2026
概括
本研究引入了温度依赖的繁殖数 (td-Rt) 模型,以改善传染病监测. 新的td-rt框架准确估计了像登革热这样的温度敏感疾病的传播风险.
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:
- 准确的实时估计有效生殖数 (Rt) 对于传染病控制至关重要.
- 温度显著影响载体传播疾病的传播,影响代代时间.
- 现有的Rt估计方法通常假设固定的生成间隔,导致温度波动的偏差结果.
研究的目的:
- 提出和评估一种用于估计温度依赖的繁殖数 (td-Rt) 的新框架.
- 用观察到的温度数据来动态更新生成间隔分布,以更准确地估计Rt.
- 为了评估td-Rt的性能与温度独立 (ti-Rt) 和角复制数 ([公式:参见文本]) 方法相比.
主要方法:
- 开发了一个温度依赖的繁殖数 (td-Rt) 估计框架.
- 采用适应的贝叶斯递归过过程,用于实时 td-Rt 估计.
- 利用模拟和现实世界登革热病例数据对ti-Rt和[公式:见文本]进行绩效评估.
主要成果:
- td-Rt在识别流行病增长时期方面普遍优于ti-Rt和[公式:参见文本].
- 在72个模拟场景中,td-Rt在54个场景中 (37.1%-95.9%) 实现了最高的分类准确性.
- td-Rt准确度在温度变化较大的场景中最高,提高了高达20%.
结论:
- 对生成时间的温度驱动变化进行核算对于准确的实时传导性估计至关重要.
- td-Rt框架为像登革热这样的气候敏感疾病提供了更好的准确性.
- 结合温度依赖的生成间隔可以增强传染病监测和应对策略.
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