Speaker
Description
In 2019 SARS-CoV-2 emerged as a new human pathogen, giving rise to a pandemic that has resulted in over 700 million cases and 7 million deaths at the time of writing. Understanding the dynamics behind the generation of new variants during a pandemic event is important for improving disease control strategies and public health policies. Even though we now have an unprecedented amount of genomic and viral dynamics information available, understanding viral evolution requires considering the complex interplay between within-host dynamics and population-level transmission processes. Models that generate ground truth data can be used to study different hypotheses on the virus evolutionary pathways. We present here an agent-based SIR model that considers population-level and intra-host processes, enabling us to study (in silico) virus evolution. The model, a Stochastic Simulation of SARS-CoV-2 Spreading and Evolution accounting for within-host dynamics (SIMPLICITY), combines a population (SIR) model for disease spread, an intra-host model for individual disease progression, an evolutionary model for SARS-CoV-2 mutations, and a phenotypic model linking virus genotype to relative fitness. SIMPLICITY can be used to study in silico evolution of human pathogenic viruses, to create synthetic datasets and to benchmark existing phylogenetic pipelines and tools. Using SARS-CoV-2 as use-case scenario, we used the model to investigate the role of immunocompromised patients in the evolution of variants during a SARS-CoV-2 pandemic. Preliminary modelling results indicate that evolutionary leaps that lead to the emergence of major variants of concern (Alpha, Beta, Gamma, Omicron BA.1/2 and Pirola) are unlikely to have emerged without the inclusion of an evolutionary reservoir. Current evidence suggest that this reservoir may be individuals who remain infected for long time (long-shedders). If the preliminary results are confirmed, they would add up to the evidence that long-shedders played an important role in the evolution of SARS-CoV-2 during the pandemic.
