Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2.
Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2.
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DOI：
10.1289/ehp10050
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发表时间：
2022-05
影响因子：
10.4
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中科院分区：
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有效生殖数是监测疾病动态、为区域和国家政策提供信息以及估计干预措施有效性的关键指标。它描述了随着时间的推移，由单个感染者引起的新感染的平均数量。迄今为止，估计数是基于临床数据，如观察到的病例、住院和/或死亡。当临床试验或报告策略发生变化时，这些估计值会暂时出现偏差。我们表明，污水中严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）RNA的动态可用于在接近真实的时间内进行估计，独立于临床数据，并且没有相关的偏倚。我们收集了瑞士苏黎世和美国加州圣何塞废水中SARS-CoV-2 RNA的纵向测量结果。我们将这些数据与有关甩负荷的时间动态（甩负荷分布）的信息相结合，以估计与每日COVID-19感染率成比例的时间序列。我们估计从这个事件的废水为基础。从废水中估算的方法对来自两个不同国家和两个废水矩阵的数据进行了稳健的计算。所得估计值与病例报告数据的估计值相似，因为基于观察到的病例、住院和死亡的估计值彼此相似。我们进一步提供的采样频率和脱落的负载分布的能力，推断的效果的细节。据我们所知，这是第一次从废水中估计。该方法提供了一种低成本、快速和独立的方法，为正在进行的大流行期间的SARS-CoV-2监测提供信息，并适用于未来针对其他病原体的基于废水的流行病学。https://doi.org/10.1289/EHP10050
The effective reproductive number, , is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate in near real time, independent of clinical data and without the associated biases. We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based from this incidence. The method to estimate from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the estimates from case report data as estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer . To our knowledge, this is the first time has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050