The interplay between migration and selection on the dynamics of pathogen variants

Area of Science:

• Epidemiology
• Evolutionary Biology
• Mathematical Modeling

Background:

• Estimating pathogen variant fitness typically assumes a well-mixed population, where frequency changes reflect selection.
• Spatial structure and host metapopulations can influence variant dynamics, challenging traditional estimation methods.

Purpose of the Study:

• To model the frequency changes of a new pathogen variant in a two-patch metapopulation over time and space.
• To investigate how migration rates affect selection and bias fitness estimations.
• To analyze the spread of SARS-CoV-2 Alpha and Delta variants in England.

Main Methods:

• Developed a mathematical model for pathogen variant frequency dynamics in a two-patch metapopulation.
• Simulated variant spread considering both selection and migration.
• Applied the model to real-world data of SARS-CoV-2 variant evolution in England.

Main Results:

• Demonstrated that even low migration rates can interfere with selection processes.
• Showed that spatial structure and migration can bias the estimation of pathogen variant fitness.
• Observed heterogeneity in fitness estimates across space, potentially explained by migration.

Conclusions:

• Spatial structure and migration are critical factors in pathogen variant evolution that must be considered.
• Current methods for estimating variant fitness may be unreliable in spatially structured populations.
• A comprehensive theoretical framework integrating selection and migration is needed for accurate pathogen evolution studies.