Modeling the velocity of evolving lineages and predicting dispersal patterns

Area of Science:

• Evolutionary biology
• Genetics
• Epidemiology

Background:

• Estimating dispersal velocity in evolving organisms is difficult.
• Current phylogeographic models lack adequate frameworks for defining velocity.
• Popular methods modeling spatial coordinates as Brownian trajectories do not define instantaneous speed.

Purpose of the Study:

• Introduce a novel family of models, Phylogenetic Integrated Velocity (PIV) models.
• Explicitly model the velocity of evolving lineages using Gaussian processes.
• Improve accuracy of velocity estimates compared to existing approaches.

Main Methods:

• Utilize Gaussian processes to model lineage velocity.
• Develop and describe the properties of PIV models.
• Apply PIV models to analyze West Nile virus dispersal data in the U.S.A.

Main Results:

• PIV models show increased accuracy in velocity estimation.
• Analyses indicate PIV models provide sensible predictions of pathogen dispersal.
• Demonstrated feasibility of predictive phylogeography for epidemic monitoring.

Conclusions:

• PIV models offer a significant advancement in estimating evolutionary dispersal.
• Predictive phylogeography using PIV models can enhance epidemic surveillance.
• The study highlights the relevance of PIV models for real-time public health applications.