Abstract:
Background: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. Methods :A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a “band of five” outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). Results: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. Conclusions:The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.