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Long-term study on wastewater SARS-CoV-2 surveillance across United Arab Emirates.
Wadi, Vijay S; Daou, Mariane; Zayed, Noora; AlJabri, Maryam; Alsheraifi, Hamad H; Aldhaheri, Saeed S; Abuoudah, Miral; Alhammadi, Mohammad; Aldhuhoori, Malika; Lopes, Alvaro; Alalawi, Abdulrahman; Yousef, Ahmed F; Hasan, Shadi W; Alsafar, Habiba.
  • Wadi VS; Center for Membranes and Advanced Water Technology (CMAT), Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • Daou M; Department of Biology, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • Zayed N; Center for Biotechnology (BTC), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • AlJabri M; Center for Biotechnology (BTC), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • Alsheraifi HH; Center for Biotechnology (BTC), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • Aldhaheri SS; Center for Biotechnology (BTC), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • Abuoudah M; Center for Biotechnology (BTC), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • Alhammadi M; Emirates Bio-Research Center, Ministry of Interior, Abu Dhabi, United Arab Emirates.
  • Aldhuhoori M; Emirates Bio-Research Center, Ministry of Interior, Abu Dhabi, United Arab Emirates.
  • Lopes A; Emirates Bio-Research Center, Ministry of Interior, Abu Dhabi, United Arab Emirates.
  • Alalawi A; Department of Health, Safety and Environment, Department of Energy, Abu Dhabi, United Arab Emirates.
  • Yousef AF; Center for Membranes and Advanced Water Technology (CMAT), Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates; Department of Biology, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emir
  • Hasan SW; Center for Membranes and Advanced Water Technology (CMAT), Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.
  • Alsafar H; Center for Biotechnology (BTC), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates; Emirates Bio-Research Center, Ministry of Interior, Abu Dhabi, United Arab Emirates; Department of Biomedical Engineering, Khalifa University of Science and Technology, PO Bo
Sci Total Environ ; 887: 163785, 2023 Aug 20.
Artigo em Inglês | MEDLINE | ID: covidwho-2311519
ABSTRACT
Wastewater-based epidemiology (WBE) demonstrates an efficient tool to monitor and predict SARS-CoV-2 community distribution. Many countries across the world have adopted the technique, however, most of these studies were conducted for a short duration with a limited sampling size. In this study, long-term reliability and quantification of wastewater SARS-CoV-2 surveillance is reported via analyzing 16,858 samples collected from 453 different locations across the United Arab Emirates (UAE) from May 2020 to June 2022. The collected composite samples were first incubated at 60 °C followed by filtration, concentration, and then RNA extraction using commercially available kits. The extracted RNA was then analyzed by one-step RT-qPCR and RT-ddPCR, and the data was compared to the reported clinical cases. The average positivity rate in the wastewater samples was found to be 60.61 % (8.41-96.77 %), however, the positivity rate obtained from the RT-ddPCR was significantly higher than the RT-qPCR suggesting higher sensitivity of RT-ddPCR. Time-lagged correlation analysis indicated an increase in positive cases in the wastewater samples when the clinical positive cases declined suggesting that wastewater data are highly affected by the unreported asymptomatic, pre-symptomatic and recovering individuals. The weekly SARS-CoV-2 viral count in the wastewater samples are positively correlated with the diagnosed new clinical cases throughout the studied period and the studied locations. Viral count in wastewater peaked approximately one to two weeks prior to the peaks appearing in active clinical cases indicating that wastewater viral concentrations are effective in predicting clinical cases. Overall, this study further confirms the long-term sensitivity and robust approach of WBE to detect trends in SARS-CoV-2 spread and helps contribute to pandemic management.
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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Estudo prognóstico Tópicos: Covid persistente Limite: Humanos País/Região como assunto: Ásia Idioma: Inglês Revista: Sci Total Environ Ano de publicação: 2023 Tipo de documento: Artigo País de afiliação: J.scitotenv.2023.163785

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Estudo prognóstico Tópicos: Covid persistente Limite: Humanos País/Região como assunto: Ásia Idioma: Inglês Revista: Sci Total Environ Ano de publicação: 2023 Tipo de documento: Artigo País de afiliação: J.scitotenv.2023.163785