Research Projects

COVID-19 outbreaks are attributed to the emergence of novel variants of the SARS-CoV-2 virus, their high circulation intensity, and the vulnerability of local populations. Rapid identification of these developments through a robust surveillance system can help implement containment measures and mitigate its rapid spread and resulting mortality, morbidity, and socio-economic consequences. A surveillance system can be based on regular analysis of influent samples from waste water treatment plants draining a defined geographic area. This method bypasses logistic and feasibility issues associated with large-scale human sampling and spares the healthcare system from pressurizing an already constrained healthcare system. To establish and validate this surveillance mechanism, a study was conducted in Bhopal, mapping the entire municipality area into 10 draining zones attached to wastewater treatment plants. Fortnightly samples were collected from each treatment plant, prepared as viral concentrates, subjected to viral RNA extraction, and performed quantitative RT-PCR to evaluate and quantify SARS-CoV-2 viral titer. The positive samples were then used for whole genome sequencing using Oxford Nanopore technology, which has been reported to achieve more than 99% genome coverage at 20X depth. The raw sequences were used for base calling, de-multiplexing, generation of consensus sequences, variant calling, variant annotation, and lineage determination using Commander software. The fortnightly viral quantitative titers and variant profiles from each of the 10 wastewater plants were compared with the number of active COVID-19 cases and variant distribution reported from the draining zones. This comparison will test the efficacy of the surveillance model as a method for predicting impending COVID-19 spikes in the community and initiating prompt containment measures by public health officials.