Understanding how quickly viruses spread among host populations is essential for managing disease outbreaks effectively. A recent study published on December 3 in PLOS Biology by Simon Dellicour and his team from the University of Brussels (ULB), Belgium, assesses the effectiveness of statistical measures that track virus movement in infected populations over time and space.
By using genomic sequencing, epidemiologists can investigate the evolutionary background of disease outbreaks and monitor their geographic spread. However, the intensity of sampling genomic data can affect the reliability of insights regarding how viruses disperse. To explore how sampling size influences these insights, the researchers modeled the spread of different pathogens and assessed three metrics derived from viral genome analysis: lineage dispersal velocity (how quickly lineages advance), diffusion coefficient (the rate of invasion into new areas), and isolation-by-distance signal (the degree to which genomic sequences of a population lose similarity as distance increases).
The findings revealed that the diffusion coefficient and isolation-by-distance signal metrics were the least affected by sampling size and intensity. When these metrics were applied to compare how various viruses dispersed within animal populations, it became clear that the speed and distance of viral spread are connected to the dispersal ability of the infected host animals, although human activities like animal trade can also have an impact. However, the study has its limitations; notably, the simulation framework did not include the generation of actual genomic sequences due to constraints in time and resources.
The authors state, “In summary, our research offers important suggestions for utilizing lineage dispersal metrics in future investigations and demonstrates their effectiveness in comparing virus spread across different contexts.”
They further explain, “This research evaluates various metrics from evolutionary trees to quantify how viruses disperse in natural settings. By applying the most effective metrics, we can compare the dispersal patterns of different viruses in animal populations, highlighting a wide range of diffusion rates that generally reflect the dispersal capabilities of the primary infected host species, while also indicating cases of significant and/or long-distance dispersal associated with human activities like animal trade.”
