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 (7,889 ± 1,421 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 people in the population on any given day using the wastewater-based epidemiology approach declined from 542,313 ± 51,159 to 31,181 ± 3,081 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 modelling approach allows for realistic assessment of incidence trend in a given population, with a more reliable estimation of the number of infected people in a population at any given point in time than can be achieved using human biomonitoring alone.

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Severe environmental conditions can have a diverse impact on marine microorganisms, including bacteria. This can have an inevitable impact on the biofouling of membrane-based desalination plants. In this work, we have utilized the indicator bacteria such as total coliform, fecal coliform, and Pseudomonas aeruginosa and 16S rRNA sequencing to investigate the impact of environmental conditions and spatial variations on the diversity of bacterial communities in the coastal waters and sediments from selected sites of Qatar over different seasons. The concentration levels of indicator bacteria were affected by increasing temperature and pH and decreasing salinity of seawater samples. Diversity indices and the molecular phylogeny demonstrated that Proteobacteria, Bacteroidetes, and Cyanobacteria were the dominant phyla in all locations. The most abundant operational taxonomic units (OTUs) at the family level were from Flavobacteriaceae (27.07%, 4.31%) and Rhodobacteraceae (22.51%, 9.86%) in seawater and sediments, respectively. Alphaproteobacteria (33.87%, 16.82%), Flavobacteria (30.68%, 5.84%), Gammaproteobacteria (20.35%, 12.45%) were abundant at the species level in both seawater and sediment, respectively, while Clostridia (13.72%) was abundant in sediment only. Results suggest that the sediments can act as a reservoir for indicators of bacteria with higher diversity and lower abundance as compared to seawater. This study helps to understand the impact of environmental conditions on the diversity and structural behavior of microbial communities specific to the marine environment of the Arabian Gulf.