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根据污水RNA数据预测特定人群中新冠病毒感染个体

Predicting COVID-19 Infected Individuals in a Defined Population from Wastewater RNA Data.

作者信息

McMahan Christopher S, Lewis Dan, Deaver Jessica A, Dean Delphine, Rennert Lior, Kalbaugh Corey A, Shi Lu, Kriebel David, Graves Duane, Popat Sudeep C, Karanfil Tanju, Freedman David L

机构信息

School of Mathematics & Statistical Sciences, Clemson University, Clemson, SC 29634, USA.

Clemson Computing and Information Technology (CCIT), Clemson University, Clemson, SC 29634, USA.

出版信息

ACS ES T Water. 2022 Nov 11;2(11):2225-2232. doi: 10.1021/acsestwater.2c00105. Epub 2022 Jul 12.

Abstract

Wastewater surveillance of SARS-CoV-2 RNA has become an important tool for tracking the presence of the virus and serving as an early indicator for the onset of rapid transmission. Nevertheless, wastewater data are still not commonly used to predict the number of infected individuals in a sewershed. The main objective of this study was to calibrate a susceptible-exposed-infectious-recovered (SEIR) model using RNA copy rates in sewage (i.e., gene copies per liter times flow rate) and the number of SARS-CoV-2 saliva-test-positive infected individuals in a university student population that was subject to repeated weekly testing during the Spring 2021 semester. A strong correlation was observed between the RNA copy rates and the number of infected individuals. The parameter in the SEIR model that had the largest impact on calibration was the maximum shedding rate, resulting in a mean value of 7.72 log genome copies per gram of feces. Regressing the saliva-test-positive infected individuals on predictions from the SEIR model based on the RNA copy rates yielded a slope of 0.87 (SE=0.11), which is statistically consistent with a 1:1 relationship between the two. These findings demonstrate that wastewater surveillance of SARS-CoV-2 can be used to estimate the number of infected individuals in a sewershed.

摘要

对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)RNA进行废水监测已成为追踪病毒存在情况以及作为快速传播开始的早期指标的重要工具。然而,废水数据仍未普遍用于预测排水区域内感染个体的数量。本研究的主要目的是使用污水中的RNA拷贝率(即每升基因拷贝数乘以流速)以及在2021年春季学期每周接受重复检测的大学生群体中SARS-CoV-2唾液检测呈阳性的感染个体数量,来校准易感-暴露-感染-康复(SEIR)模型。观察到RNA拷贝率与感染个体数量之间存在很强的相关性。SEIR模型中对校准影响最大的参数是最大排毒率,其粪便中每克的平均值为7.72对数基因组拷贝。根据RNA拷贝率,将唾液检测呈阳性的感染个体数量与SEIR模型的预测值进行回归分析,得到斜率为0.87(标准误=0.11),这在统计学上与两者之间1:1的关系一致。这些发现表明,对SARS-CoV-2的废水监测可用于估计排水区域内感染个体的数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c59/9728558/209e6791d5a7/nihms-1823361-f0002.jpg

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