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 wastewater 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 N1 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 N1 Ct values in the wastewater samples. The estimated number of infected population on any given day using the wastewater-based epidemiology approach declined from 542,313 ± 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.
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•First study that reports the detection of SARS-CoV-2 RNA fragments in wastewater in Qatar.•SARS-CoV-2 RNA was detected in all the influent wastewater samples (7,889 ± 1,421 copy/L – 542,056 ± 25,775) copy/L).•WBE modeling gives good estimation of infected population numbers supported by clinical seroprevalence data•WBE model shows that the number of infected people dropped from 542,313 ± 51,159 to 31,181± 3,081 over the sampling period
Wastewater-based epidemiology (WBE) has been proven effective for the monitoring of infectious disease outbreaks during mass gathering events and for timely public health interventions. As part of ...Qatar's efforts to monitor and combat the spread of infectious diseases during the FIFA World Cup Qatar 2022™ (FWC’22), wastewater surveillance was used to monitor the spread of SARS-CoV-2, human enterovirus, and poliovirus. The screening covered five major wastewater treatment plants servicing the event locations between October 2022 and January 2023. Viruses were concentrated from the wastewater samples by PEG precipitation, followed by qRT-PCR to measure the viral load in the wastewater. As expected, SARS-CoV-2 and enterovirus RNA were detected in all samples, while poliovirus was not detected. The concentration of SARS-CoV-2 was correlated with population density, such as areas surrounding the World Cup venues, and with the number of reported clinical cases. Additionally, we observed temporal fluctuations in viral RNA concentrations, with peak levels coinciding with the group stage matches of the FWC’22. This study has been useful in providing public health authorities with an efficient and cost-effective surveillance system for potential infectious disease outbreaks during mega-events.
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•Wastewater surveillance was utilized to monitor SARS-CoV-2, enterovirus, and poliovirus during the FIFA World Cup Qatar 2022.•SARS-CoV-2 and enterovirus RNA were detected in all samples, while poliovirus was not detected.•Sequencing revealed that Omicron XBB.1 was the predominant subvariant during the games period.•Wastewater-based epidemiology offers an efficient, economical way to detect disease outbreaks during major events.
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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•The Ct values were normalized against the human reference gene RNase P.•Data normalization allows for a logical assessment of incidence trends within the population.•Normalized SARS-CoV-2 viral loads in wastewater correlate well with the clinical cases in Qatar.•Sequencing in wastewater samples helps the identification of circulating variants.
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