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. 2021 Jun 20:774:145608.
doi: 10.1016/j.scitotenv.2021.145608. Epub 2021 Feb 9.

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

Jayaprakash Saththasivam  1 , Shimaa S El-Malah  1 , Tricia A Gomez  1 , Khadeeja A Jabbar  1 , Reshma Remanan  1 , Arun K Krishnankutty  1 , Oluwaseun Ogunbiyi  1 , Kashif Rasool  1 , Sahel Ashhab  1 , Sergey Rashkeev  1 , Meryem Bensaad  2 , Ayeda A Ahmed  2 , Yasmin A Mohamoud  2 , Joel A Malek  2 , Laith J Abu Raddad  3 , Andrew Jeremijenko  4 , Hussein A Abu Halaweh  5 , Jenny Lawler  6 , Khaled A Mahmoud  7
Affiliations

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

Jayaprakash Saththasivam et al. Sci Total Environ. .

Abstract

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.

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

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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
A) Effects of heat treatment at 56 °C at 30 min and 60 min on the SARS-CoV-2 RNA integrity; B) Detection of SARS-CoV-2 RNA in wastewater samples (19th July 2020). Standard deviations shown in this figure were based on duplicate measurements.
Fig. 2
Fig. 2
SARS-CoV-2 RNA concentration in the influent of five major WWTPs in Qatar. Standard deviations shown in the bar charts were based on duplicate measurements.
Fig. 3
Fig. 3
Daily and Cumulative SARS-CoV-2 positive cases as reported in Qatar from late March to August 2020. S1–9 represents the sampling days conducted between 21st June to 30th August 2020.
Fig. 4
Fig. 4
Estimated infected population against the corrected 22 days of cumulative positive cases.
See this image and copyright information in PMC

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