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Inferring epidemiological parameters under an infectious phylogeography model with visitor dynamics.

Albert C Soewongsono¹, Ammon Thompson², Michael J Landis¹

¹Department of Biology, Washington University in St. Louis, Rebstock Hall, St. Louis, Missouri, 63130, USA.

Medrxiv : the Preprint Server for Health Sciences

|December 25, 2025

Summary

Infectious disease spread is complex. Our model shows returning travelers, not foreign visitors, were the primary drivers of early SARS-CoV-2 spread in Europe, highlighting the importance of host movement dynamics.

Keywords:

Bayesian inference epidemiology host movement infectious diseases phylogeography

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Area of Science:

Epidemiology
Phylogeography
Mathematical Modeling

Background:

Infectious diseases spread through host movement, complicating outbreak dynamics.
Distinguishing between pathogen transmission by visitors versus returning travelers is challenging.

Purpose of the Study:

To develop a phylogeographic model incorporating visitor dynamics for pathogen spread.
To analyze the role of host movement in disease transmission during outbreaks.

Main Methods:

Developed a phylogeographic model based on an epidemiological compartment model with visitor dynamics.
Used stationary properties for a statistically accurate and computationally tractable approximation.
Applied the model to European SARS-CoV-2 infection and travel data.

Main Results:

SARS-CoV-2 was primarily introduced into new countries by returning travelers early in the European outbreak.
Visitor dynamics models may underestimate outbreak magnitudes compared to models with indefinite travel.
Host movement patterns significantly influence disease transmission dynamics.

Conclusions:

Host movement, specifically returning travelers, plays a crucial role in the early spread of infectious diseases.
Accurate modeling of host movement dynamics is essential for understanding and controlling pandemics.
Phylogeographic models incorporating visitor dynamics offer valuable insights into pathogen transmission.