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. 2021 Apr 10:764:142929.
doi: 10.1016/j.scitotenv.2020.142929. Epub 2020 Oct 19.

Detection and quantification of SARS-CoV-2 RNA in wastewater and treated effluents: Surveillance of COVID-19 epidemic in the United Arab Emirates

Shadi W Hasan  1 , Yazan Ibrahim  2 , Marianne Daou  3 , Hussein Kannout  4 , Nila Jan  3 , Alvaro Lopes  5 , Habiba Alsafar  6 , Ahmed F Yousef  7
Affiliations

Detection and quantification of SARS-CoV-2 RNA in wastewater and treated effluents: Surveillance of COVID-19 epidemic in the United Arab Emirates

Shadi W Hasan et al. Sci Total Environ. .

Abstract

Testing SARS-CoV-2 viral loads in wastewater has recently emerged as a method of tracking the prevalence of the virus and an early-warning tool for predicting outbreaks in the future. This study reports SARS-CoV-2 viral load in wastewater influents and treated effluents of 11 wastewater treatment plants (WWTPs), as well as untreated wastewater from 38 various locations, in the United Arab Emirates (UAE) in May and June 2020. Composite samples collected over twenty-four hours were thermally deactivated for safety, followed by viral concentration using ultrafiltration, RNA extraction using commercially available kits, and viral quantification using RT-qPCR. Furthermore, estimates of the prevalence of SARS-CoV-2 infection in different regions were simulated using Monte Carlo. Results showed that the viral load in wastewater influents from these WWTPs ranged from 7.50E+02 to over 3.40E+04 viral gene copies/L with some plants having no detectable viral RNA by RT-qPCR. The virus was also detected in 85% of untreated wastewater samples taken from different locations across the country, with viral loads in positive samples ranging between 2.86E+02 and over 2.90E+04 gene copies/L. It was also observed that the precautionary measures implemented by the UAE government correlated with a drop in the measured viral load in wastewater samples, which were in line with the reduction of COVID-19 cases reported in the population. Importantly, none of the 11 WWTPs' effluents tested positive during the entire sampling period, indicating that the treatment technologies used in the UAE are efficient in degrading SARS-CoV-2, and confirming the safety of treated re-used water in the country. SARS-CoV-2 wastewater testing has the potential to aid in monitoring or predicting an outbreak location and can shed light on the extent viral spread at the community level.

Keywords: Detection; Quantification; SARS-CoV-2; Surveillance; UAE; Wastewater.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Unlabelled Image
Graphical abstract
Fig. 1
Fig. 1
Schematic representation of the sample collection, virus deactivation, and RNA concentration and extraction (WWTPs: Wastewater treatment plants, WW: Wastewater) (a) viral concentration using ultrafiltration columns and (b) Viral concentration using PEG-mediated precipitation.
Fig. 2
Fig. 2
Viral load (average of triplicate measurements ± SD) in six SARS-CoV-2 positive wastewater samples determined by the two compared methods. ND – indicates a sample where no value could be determined because it is below the detection limit.
Fig. 3
Fig. 3
Concentration profile of SARS-CoV-2 viral load in 11 WWTPs' influents in the UAE. X-axis: mm/dd/yy, y-axis: viral concentration (gene copies/L). ND – indicates a sample where no value could be determined because it is below the detection limit.
Fig. 4
Fig. 4
Number of SARS-CoV-2 (COVID-19) diagnosed patients (grey bars) and infected individuals that recovered in the UAE (green line) (U. National Emergency Crisis and Disaster Management Authority, 2020). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 5
Fig. 5
Viral load in wastewater in four different locations across the UAE during May and June 2020. ND – indicates a sample where no value could be determined because it is below the detection limit.
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