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COVID-19 (SARS-CoV-2) outbreak monitoring using wastewater-based epidemiology in Qatar

机译:Covid-19(SARS-COV-2)使用卡塔尔的废水流行病学爆发监测

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摘要

Raw municipal wastewater from five wastewater treatment plants representing the vast majority of the Qatar population was sampled between the third week of June 2020 and the end of August 2020, during the period of declining cases after the peak of the first wave of infection in May 2020. The N1 region of the SARS-CoV-2 genome was used to quantify the viral load in the wastewater using RT-qPCR. The trend in Ct values in the waste-water samples mirrored the number of new daily positive cases officially reported for the country, confirmed by RT-qPCR testing of naso-pharyngeal swabs. SARS-CoV-2 RNA was detected in 100% of the influent wastewater samples (7889 ± 1421 copy/L - 542,056 ± 25,775 copy/L, based on the Nl assay). A mathematical model for wastewater-based epidemiology was developed and used to estimate the number of people in the population infected with COVID-19 from the Nl Ct values in the wastewater samples. The estimated number of infected population on any given day using the wastewater-based epidemiology approach declined from 542313 ± 51,159 to 31,181 ± 3081 over the course of the sampling period, which was significantly higher than the officially reported numbers. However, seroprevalence data from Qatar indicates that diagnosed infections represented only about 10% of actual cases. The model estimates were lower than the corrected numbers based on application of a static diagnosis ratio of 10% to the RT-qPCR identified cases, which is assumed to be due to the difficulty in quantifying RNA losses as a model term. However, these results indicate that the presented WBE modeling approach allows for a realistic assessment of incidence trend in a given population, with a more reliable estimation of the number of infected people at any given point in time than can be achieved using human biomonitoring alone.
机译:来自五个废水处理厂的未加工的城市废水,代表绝大多数卡塔尔人口在2020年6月的第三周和2020年8月底,在5月2020年5月在第一波感染峰值后的衰退期间进行了取样。SARS-COV-2基因组的N1区域用于使用RT-QPCR量化废水中的病毒载量。废水样品中CT值的趋势反映了该国正式报告的新日常阳性案件的数量,通过鼻咽拭子的RT-QPCR测试证实。在100%的流动性废水样品中检测到SARS-COV-2 RNA(基于NL测定,在100%的进水废水样品中检测到100%的流动废水样品(7889±1421拷贝/ L - 542,056±25,775拷贝/ L)。开发了一种基于废水的流行病学的数学模型,并用于从废水样品中的NL CT值中估计患有Covid-19感染的人口数量。使用废水的流行病学方法的任何给定日的受感染群的估计数量在采样期的过程中从542313±51,159到31,181±3081减少,这显着高于正式报告的数字。然而,来自卡塔尔的Seroprengalences数据表明,诊断的感染仅占实际情况的约10%。模型估计基于施用静态诊断率为10%的静态诊断率为RT-QPCR所识别的病例的校正数量低于校正数,这被认为是由于难以定量RNA损失作为模型术语。然而,这些结果表明,所呈现的WBE建模方法允许对特定人群的发生率趋势进行逼真的评估,更可靠地估计任何特定时间点的受感染者的数量,而不是单独使用人类生物监测。

著录项

  • 来源
    《Science of the total environment》 |2021年第20期|145608.1-145608.9|共9页
  • 作者单位

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Cenomics Laboratory Weill Cornell Medicine-Qatar (WCM-Q). Cornell University Doha Qatar;

    Cenomics Laboratory Weill Cornell Medicine-Qatar (WCM-Q). Cornell University Doha Qatar;

    Cenomics Laboratory Weill Cornell Medicine-Qatar (WCM-Q). Cornell University Doha Qatar;

    Cenomics Laboratory Weill Cornell Medicine-Qatar (WCM-Q). Cornell University Doha Qatar;

    Infectious Disease Epidemiology Croup Weill Cornell Medicine-Qatar Cornell University Doha Qatar;

    Hamad Medical Corporation Doha Qatar;

    Drainage Network Operation & Maintenance Department Public Works Authority Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

    Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation P.O. Box 34110 Doha Qatar;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    SARS-CoV-2; COVID-19; Wastewater-based epidemiology (WBE); Outbreaks; Community; Health risks;

    机译:SARS-CoV-2;新冠肺炎;基于废水的流行病学(WBE);爆发;社区;健康风险;

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