Evaluating the speed at which viruses spread and transmit across host populations is critical to mitigating disease outbreaks. A study published December 3rd in PLOS Biology by Simon Dellicour at the University of Brussels (ULB), Belgium, and colleagues evaluate the performance of statistics measuring how viruses move across space and time in infected populations.
Genomic sequencing allows epidemiologists to examine the evolutionary history of pathogenic outbreaks and track the spatial movement of an outbreak. However, the sampling intensity of genomic sequences can potentially impact the accuracy of dispersal insights gained through these evolutionary approaches. In order to assess the impact of the sampling size, researchers simulated the spread of several pathogens to evaluate three dispersal metrics estimated from the analysis of viral genomes: a lineage dispersal velocity (the speed at which lineages spread), a diffusion coefficient (how fast lineages invade space), and an isolation-by-distance signal (how genomic sequences of a population become less similar over geographic distance) metric.
The researchers found that diffusion coefficient and isolation-by-distance signal metrics were least impacted by sample size/intensity. After using these metrics to compare the dispersal pattern and capacity of various viruses spreading in animal populations, they also discovered the extent to which the speed and distance of viral spread reflects the dispersal capacity of the infected host animal, but may also be influenced by human interference, such as the animal trade. The study does have limitations; for example, the simulation framework did not involve the generation of actual genomic sequences due to limited time and resources.
According to the authors, "Overall, our study provides key recommendations for the use of lineage dispersal metrics to consider in future studies and illustrates their application to compare the spread of viruses in various settings."
The authors add, "In this study, we evaluate the performance of various metrics estimated from evolutionary trees to quantify the dispersal capacity of viruses in the wild. We then use the most performant metrics to compare the dispersal pattern of various viruses spreading in animal populations, which reveals a broad range of diffusion velocities mostly reflecting the dispersal capacity of the main infected host species but also, in some cases, the likely signature of rapid and/or long-distance dispersal events driven by human-mediated movements through animal trade."
