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基于废水的监测数据,以确定人口较少社区的新冠疫情趋势。

Wastewater-based surveillance data to determine the COVID-19 trends in communities with low population.

作者信息

Pappu Aiswarya Rani, Green Ashley, Oakes Melanie, Jiang Sunny

机构信息

Department of Civil and Environmental Engineering, University of California Irvine, Irvine, USA.

Department of Biological Chemistry, University of California Irvine, Irvine, USA.

出版信息

Data Brief. 2025 Jun 7;61:111756. doi: 10.1016/j.dib.2025.111756. eCollection 2025 Aug.

Abstract

The data presented in this article show SARS-CoV-2 viral concentration and trends in wastewater among communities with different population size. Particularly, the data show that wastewater SARS-CoV-2 concentration can better predict COVID-19 transmission in communities than clinical data. The article also reports PMMoV data in wastewater and population data in each community, and their effects on the correlation between wastewater SARS-CoV-2 and clinical COVID-19 data. The wastewater and clinical data reported in this article are collected from 7 students' housing communities with population ranging between 300 and 4000 residents per community. The dataset presents SARS-CoV-2 N2 and E gene as well as PMMoV concentrations in the raw wastewater samples collected from 13 sewer manholes at these communities roughly three times per week for a period of 6-months between December 2021 and June 2022. This dataset will help to 1) improve future wastewater based epidemiological models, 2) improve understanding on PMMoV concentration ranges in wastewater at low population communities, 3) develop methods to support data interpretation, and 4) understand the effects of spatial scales on sampling frequency and infection outbreak detection.

摘要

本文所呈现的数据展示了不同人口规模社区废水中的新冠病毒浓度及趋势。具体而言,数据表明,与临床数据相比,废水中的新冠病毒浓度能更好地预测社区内的新冠疫情传播情况。文章还报告了废水中的戊型肝炎病毒(PMMoV)数据及各社区的人口数据,以及它们对废水中新冠病毒与临床新冠疫情数据之间相关性的影响。本文所报告的废水和临床数据来自7个学生居住社区,每个社区的居民人数在300至4000人之间。该数据集呈现了2021年12月至2022年6月期间,在这些社区的13个下水道检修孔每周大约三次采集的未经处理的废水样本中的新冠病毒N2和E基因以及PMMoV浓度。该数据集将有助于:1)改进未来基于废水的流行病学模型;2)增进对低人口社区废水中PMMoV浓度范围的了解;3)开发支持数据解读的方法;4)了解空间尺度对采样频率和感染爆发检测结果的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0c/12246858/3b851e264968/gr1.jpg

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引用本文的文献

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本文引用的文献

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Tracking COVID-19 trends in communities with low population by wastewater-based surveillance.
Sci Total Environ. 2025 Mar 20;970:179007. doi: 10.1016/j.scitotenv.2025.179007. Epub 2025 Mar 6.

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