Although the presence of SARS-CoV-2 fragments in raw sewage water are not much concerning, since it is a new pathogen and its fate in the environment is poorly understood; therefore efforts are needed for their effective removal. In under-developed countries with poor sewersheds and sanitation practices, the raw sewage water might come in contact with rivers and other water bodies and is generally used by the population for various purposes including drinking water. Hence it is important to properly treat sewage water to reduce public health risks, if any. Our study evaluated various advanced oxidation processes (AOPs) for disinfection of SARS-CoV-2 from sewage water collected from the academic institutional residential campus. The present study is the first report showing hydrodynamic cavitation (HC) used to reduce the SARS-CoV-2 viral load from sewage water. Additionally, we have also evaluated hybrid techniques like HC/O3, HC/O3/H2O2, HC/H2O2, O3/UV, UV/H2O2, UV/H2O2/O3, and O3/H2O2 for the minimization of the SARS-CoV-2 viral load from sewage water. The sewage water treatment techniques were evaluated based on its viral concentration-reducing efficiency by comparing it with the same raw sewage water sample. However, ozone alone and its combination with other disinfecting techniques (like HC, UV, and H2O2) showed >95% SARS-CoV-2 specific RNA-reducing efficiency (also known as viral load). The AOPs treated sewage water was subjected to total nucleic acid isolation followed by RT-qPCR for viral load estimation. Interestingly, all sewage water treatment techniques used in this study significantly reduces both the SARS-CoV-2 viral load as well as PMMoV (faecal indicator) load.

No abstract

The wastewater-based epidemiology (WBE) of SARS-CoV-2 is a quick and cost-effective method of tracking virus transmission. However, few studies reported on campus or in academic or residential settings worldwide. In this study, we demonstrated the WBE approach to detect, monitor, and evaluate genomic variants of SARS-CoV-2 fragments in a sewage treatment plant (STP) located on the campus of CSIR National Chemical Laboratory, Pune, India. Herein we describe the early warning capability of WBE, with viral load rise in campus sewage water up to 14 days before its clinical detection. This was supported further by a significant correlation between SARS-CoV-2 RNA concentration and clinically reported COVID-19 cases on campus. Additionally, we comprehended the probable targets missed by the quantitative qRT-PCR using amplicon-based sequencing due to low viral load. The analysis revealed the presence of signature mutations of the Omicron (S:N679K, S:N764K, S:D796Y, N:P13L, ORF1a:T3255I, ORF1a:K856R, ORF1a:P3395H, and N:S413R) before the lineage was first detected globally. Further, we used Lineage decomposition (LCS) tool to detect the Variant of Concern (VOC)/Variant of Interest (VOI) signals upto a month earlier in sewage water samples. The analysis also indicated the transition of lineage from Delta to Omicron in late Decemeber,2021. This is the first study in India highlighting the use of on-campus STP to evaluate the local spread of SARS-CoV-2, which could aid in preventing COVID-19 in academic institutes/universities. This study proves the usefulness of WBE as an early warning system for detecting, tracking and tracing VOCs using the sequencing approach. The current study could aid in taking critical decisions to tackle the pandemic scenario on campus.HighlightsThe first study on campus sewage water for SARS-CoV-2 surveillance in IndiaEarly detection of Omicron VOC signals during early November 2021Sequencing revealed the presence of Omicron VOC fragments prior to clinical cases reported on campusGenomic analysis indicated transition of Delta to Omicron lineage in late December 2021 and potentially led to the third waveCombining qRT-PCR and sequencing could be useful for on-campus tracking of variants using wastewater surveillance

The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods in early detection and monitoring of the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool to analyze and enumerate the prevalence of infectious pathogens in a population ahead of time. In the present study, real time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing was performed to determine the SARS-CoV-2 load trend and dynamics of variants over a longitudinal scale in 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) of Pune city, India, during November 2021 to April-2022. In total 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2 were identified. The SARS-CoV-2 Omicron variant fragments were detected in WW samples prior to its detection in clinical cases. Moreover, highly contagious sub-lineages of Omicron, such as BA.2.12 (0.8-0.25%), BA.2.38 (0.8-1.0%), BA.2.75 (0.01-0.02%), BA.3 (0.09-6.3%), BA.4 (0.24-0.29%), and XBB (0.01-13.7%) fragments were significantly detected. The longitudinal analysis also suggested the presence of the BA.5 lineage in November 2021, which was not reported in the clinical settings throughout the duration of this study, indicative of silent variant persistence. Overall, the present study demonstrated the practicality of WBE in early detection of SARS CoV-2 variants, which could be useful in tracking future outbreaks of SARS-CoV-2. Such approaches could be implicated in the monitoring of the infectious agents before they appear in clinical cases.