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结合废水监测和案例数据来估计时间变化的有效繁殖数量

Shihui Jin¹, Martin Tay², Lee Ching Ng³

¹Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.

The Science of the total environment

|April 15, 2024

概括

废水监测为COVID-19传播提供了有价值的见解. 将临床数据与废水监测相结合,可以准确估计有效繁殖数 (R_t),从而优化公共卫生监测.

科学领域:

流行病学流行病学
传染病建模传染病建模
公共卫生监督公共卫生监督

背景情况:

废水监测是监测COVID-19等传染病的越来越多的工具.
现有的模型主要使用临床数据来估计有效繁殖数 (R_t),对废水数据的精度的探索有限.
在流行病学建模中,废水病毒载荷的附加值仍然存在不确定性.

研究的目的:

开发和评估贝叶斯层次模型,以利用废水数据估计COVID-19传播动态.
为了比较来自各种数据源的R_t估计,包括临床数据和废水病毒载荷.
评估不同废水采样策略对估计准确性的影响.

主要方法:

开发了贝叶斯层次模型来重建感染轨迹并估计R_t.
利用多种数据流:新加坡 (2022-2023) 报告的病例,住院,死亡和废水病毒载荷.
在各种废水采样频率和大小下探索模型性能.

主要成果:

在使用不同数据流的模型中获得了一致的R_t估计.
纳入更多废水样本的模型显示不确定性增加和R_t的变化.
在病例数和确诊率的时间变化中确定了周中的一天的影响.

结论:

建议采用混合方法,将临床和废水监测相结合,以应对确定率的变化.
废水监测可能会减少采样频率或大小,而不会牺牲R_t估计的准确性.
在保持强大的传播见解的同时,在传染病监测中优化资源配置是可能的.

关键词:

在 COVID-19 疫情中,有效复制编号实际复制编号这就是SARS-CoV-2病毒.传输动态传输动态基于废水的流行病学.

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