A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data.
A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data.
复制标题
一个简单的 SEIR-V 模型，可使用基于废水的监测数据来估计 COVID-19 患病率并预测 SARS-CoV-2 传播。
DOI：
10.1101/2022.07.17.22277721
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Wu,Fuqing
中科院分区：
文献类型：
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作者：
Phan,Tin;Brozak,Samantha;Pell,Bruce;Gitter,Anna;Mena,KristinaD;Kuang,Yang;Wu,Fuqing
基于废水的监测（WBS）已被广泛用作监测SARS-CoV-2传播的公共卫生工具。然而，从WBS数据得出的流行病学推断仍未得到充分研究，并限制了其应用。在本研究中，我们通过将WBS数据整合到SEIR-V模型中，建立了估算COVID-19流行率和预测SARS-CoV-2传播的定量框架。我们从概念上将个体水平的病毒脱落过程分为暴露阶段、感染阶段和恢复阶段，类似于群体水平SEIR模型中的隔室。我们证明了温度对下水道中病毒损失的影响可以直接纳入我们的框架。利用大波士顿地区第二波大流行（2020年10月2日至2021年1月25日）的WBS数据，我们发现SEIR-V模型成功地再现了废水中病毒载量的时间动态，并预测真实病例数比报告病例数更早达到峰值6-16天，高出8.3-10.2倍（R= 0.93）。本工作展示了一种简单而有效的方法，将WBS和定量流行病学模型结合起来，估计下水道中SARS-CoV-2的流行和传播，有助于将废水监测应用于传染病的流行病学推断，并为公共卫生行动提供信息。
Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020–Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6–16 days and 8.3–10.2 folds (R= 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.