Rapid genomic surveillance of SARS-CoV-2 in a dense urban community using environmental (sewage) samples
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- Rapid genomic surveillance of SARS-CoV-2 in a dense urban community using environmental (sewage) samples
Understanding disease burden and transmission dynamics in resource-limited, developing countries like Nepal is often challenging due to a lack of adequate surveillance systems. These issues are exacerbated by limited access to diagnostic and research facilities throughout the country. Nepal has one of the highest COVID-19 case rates (915 cases per 100,000 people) in South Asia, with densely-populated Kathmandu experiencing the highest number of cases. Swiftly identifying case clusters and introducing effective intervention programs is crucial to mounting an effective containment strategy.
The rapid identification of circulating SARS-CoV-2 variants can also provide important information on viral evolution and epidemiology. Genomic-based environmental surveillance can help in the early detection of outbreaks before clinical cases are recognized, and identify viral micro-diversity that can be used for designing real-time risk-based interventions. This research aimed to develop a genomic-based environmental surveillance system by detecting and characterizing SARS-CoV-2 in sewage samples of Kathmandu using portable next-generation DNA sequencing devices.
Out of 20 selected sites in the Kathmandu Valley, sewage samples from 16 (80%) sites had detectable SARS-CoV-2. A heat-map was created to visualize transmission activity in the community based on viral load intensity and corresponding geospatial data. Further, 41 mutations were observed in the SARS-CoV-2 genome. Some detected mutations (n=9, 2%) were novel and yet to be reported in the global database, with one indicating a frameshift deletion in the spike gene. We also observed more transition than transversion on detected mutations, indicating rapid viral evolution in the host.
Our study has demonstrated the feasibility of rapidly obtaining vital information on community transmission and disease dynamics of SARS-CoV-2 using genomic-based environmental surveillance.