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10.1016_j.eti.2022.102775.pdf (647.32 kB)

Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance

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submitted on 2023-12-05, 06:45 and posted on 2023-12-05, 12:53 authored by Shimaa S. El-Malah, Jayaprakash Saththasivam, Khadeeja Abdul Jabbar, Arun K.K., Tricia A. Gomez, Ayeda A. Ahmed, Yasmin A. Mohamoud, Joel A. Malek, Laith J. Abu Raddad, Hussein A. Abu Halaweh, Roberto Bertollini, Jenny Lawler, Khaled A. Mahmoud

The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. SARS-CoV-2 variants outbreak was monitored during the circulating wave between February and August 2021. Sewage samples were collected from five major wastewater treatment plants and subsequently analyzed to determine the viral loads in the wastewater. SARS-CoV-2 was detected in all the samples where the wastewater Ct values exhibited a similar trend as the reported number of new daily positive cases in the country. The infected population number was estimated using a mathematical model that compensated for RNA decay due to wastewater temperature and sewer residence time, and which indicated that the number of positive cases circulating in the population declined from 765,729 ± 142,080 to 2,303 ± 464 during the sampling period. Genomic analyses of SARS-CoV-2 of thirty wastewater samples collected between March 2021 and April 2021 revealed that alpha (B.1.1.7) and beta (B.1.351) were among the dominant variants of concern (VOC) in Qatar. The findings of this study imply that the normalization of data allows a more realistic assessment of incidence trends within the population.

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Published in: Environmental Technology & Innovation
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Open Access funding provided by the Qatar National Library.



  • English



Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • Qatar Environment and Energy Research Institute - HBKU
  • Weill Cornell Medicine - Qatar
  • WHO Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis - WCM-Q
  • Ashghal Public Works Authority - State of Qatar
  • Ministry of Public Health - State of Qatar