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

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.

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

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.

Unprecedented environmental and energy impacts and challenges of COVID-19 pandemic.

The rapid transmission tendency, severity, and wide geographical spread of newly emerged novel coronavirus (SARS-CoV-2) in different environmental matrices, including water, air, and soil, has posed severe health, environmental, energy, and economic challenges worldwide. Despite the severe health effects, unprecedented improvements in air quality in many countries due to emergency measures, and public behavior changes have been reported. SARS-CoV-2 has been detected in air and sewage samples in several studies across the globe. The use of wastewater-based epidemiology (WBE) could be a valuable method to monitor the outbreak of COVID-19, which requires fast and reliable methods for virus detection in sewage. However, water treatment companies face many pressures due to potential for aerosolization, PPE shortages, and changed usage patterns. In addition, the unprecedented impact of the COVID-19 outbreak on the worldwide economy especially the energy sector, and its impact on our ecosystem required instant responses. This article discusses the recent developments and challenges faced in water, air, and energy resources, including renewables and non-renewables as the significant and interrelated components of the ecosystem. Furthermore, some recommendations have been directed, which may serve as a guideline to the scientists, legislators, and other stakeholders. A future roadmap has been proposed to overcome the tragic effects of COVID-19 and developing a sustainable environmental system to minimize the impact of such infectious outbreaks in the future.