Genomics-based approach for detection and characterization of SARS-CoV-2 co-infections and diverse viral populations

We aim to implement an innovative approach to monitor and study the diversity of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) within the human population, particularly during periods of emergence and circulation of VOCs. This approach focused on detecting highly diverse viral samples and co-infection cases, which are known to facilitate viral diversity through recombination and can potentially lead to the emergence of new recombinant lineages with novel characteristics. Monitoring and characterizing co-infection cases during an outbreak is a key strategy for better understanding viral evolution, especially during epidemic periods. However, detecting co-infection cases is challenging, and their prevalence is often highly underestimated. In this study, we developed a strategy to identify highly diverse viral samples that can be implemented in surveillance programs and applied to large datasets. We aim to implement an innovative approach to monitor and study the diversity of SARS-CoV-2 within the human population, particularly during periods of emergence and circulation of Variants of Concern. This approach focused on detecting highly diverse viral samples and co-infection cases, which are known to facilitate viral diversity through recombination and can potentially lead to the emergence of new recombinant lineages with novel characteristics.