现在使用医院和社区的病毒学测试数据预测流行病趋势
Tse Yang Lim1, Sanjat Kanjilal2, Shira Doron3
1Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. tseyanglim@hsph.harvard.edu.
Nature communications
|November 19, 2025
概括
来自RT-qPCR测试的病毒载荷周期值 (Ct) 值为跟踪COVID-19趋势提供了一个替代方案. 虽然使用合成数据有效,但流行病现状预测的真实准确性是适度的,但可以通过异常值修剪来改进.
科学领域:
- 流行病学 流行病学
- 病毒学 病毒学
- 公共卫生监督 公共卫生监督
背景情况:
- 传统的COVID-19监测依赖于病例数和住院情况.
- 反转录定量聚合酶连锁反应 (RT-qPCR) 周期值 (Ct) 值为监测流行趋势提供了一个潜在的替代方案.
- 对于现实世界流行病监测的Ct值的优点,局限性和统计能力仍然未被充分探索.
研究的目的:
- 为了探索SARS-CoV-2病毒载量的Ct值对于流行病现时广播的实用性.
- 量化影响基于CT的流行病监测准确性的生物和后勤因素.
- 与传统指标相比,评估Ct值的预测能力.
主要方法:
- 利用了来自医院和市政测试的SARS-CoV-2RT-qPCR数据.
- 采用了理论分析和模拟研究的组合.
- 配备了通用添加模型来预测使用Ct值分布的流行病增长率和方向.
- 通过使用RMSE和AUC等指标,评估了两周窗口的现在预测准确性.
主要成果:
- 峰值病毒载量,生长/清除率以及采样物流的变化显著影响了Ct值与生长率的关系.
- 模型在合成数据中准确预测了流行病趋势 (RMSE:0.0192,AUC:0.910).
- 与真实数据 (RMSE:0.039-0.052,AUC:0.72-0.80) 观察到适度的准确性,异常值修剪改善了性能.
结论:
- Ct值可以补充SARS-CoV-2监测的传统发病率指标.
- 基于CT的现在预测的准确性受到各种生物和后勤因素的影响.
- 虽然现实世界的表现是温和的,但Ct值为流行病动态提供了宝贵的见解.
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