SARS-CoV-2 shows an unprecedented ability to mutate and spread within the human populations. Full-genome-sequence analysis allows us to understand recent evolutionary events and adaptability mechanisms. Even though a vast amount of viral genomic data are available, there is uncertainty about the optimal computational tools needed to extract the maximum amount of knowledge at the viral population level. A reason for this is that state-of-the-art software of population genomics analysis has been obtained from studies in non-rapidly evolving organisms, such as Eukaryotes; in other words, tools adopt assumptions that, at least partially, are not valid for the study of viruses. In the mobiVirus project, we propose to study the evolution of viral genomes in human populations using realistic human mobility trajectories that will be obtained by available sources and/or they will be generated by simulations on Google and/or OpenStreet maps. Thus, mobiVirus will study the evolution of SARS-CoV-2 and dispersal patterns by extending the population genetics theory for fast evolving pathogens that may interact with their host’s genome taking into account interventions and vaccination efforts. We aim to shed light on the recombination process that may act on viral genomes since its consequences are still unknown regarding their virulence.