What is it about?
People travel between cities and countries every day, and these movements influence the spread infectious diseases. However, it is often unclear whether outbreaks in a new location are brought by infected visitors who infect local residents while traveling, or by local residents who become infected while abroad and bring the disease home. In this study, we developed a novel phylogenetic model that captures how diseases spread through short-term travel. The model uses a time-calibrated phylogenetic tree from sampled individuals together with travel patterns to estimate how diseases move between populations. We also derived mathematical results showing when our approximation model provides an accurate representation of the full underlying disease dynamics. We applied the model to empirical data from the early spread of SARS-CoV-2 in Europe. Our results suggest that, during the early stages of the pandemic, new outbreaks were more often caused by infected residents returning home after traveling than by infected visitors transmitting the virus abroad. We also found that models assuming people migrate permanently or for very long periods may underestimate the impact of short-term travelers on disease spread. These findings highlight the importance of accurately representing human travel patterns when studying how infectious diseases spread and the role of short-term visitors in shaping outbreaks.
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Why is it important?
We designed a phylogenetic model of infectious disease transmission among spatially structured populations during the early phase of an outbreak with realistic host movement dynamics. By accounting for “short trips,” our findings show that models lacking this feature can produce biased estimates of key epidemiological parameters, such as the contribution of travelers to introducing disease into new countries. Models with realistic host movement, such as ours, may help inform travel-related strategies for containing emergent outbreaks.
Perspectives
As a mathematician with a deep interest in biology, I have always been fascinated by using mathematics to understand complex biological systems. This project provided a novel insight in combining mathematical theory, epidemiological modeling, and phylogenetic methods to investigate how infectious diseases spread through human travel. One of the most rewarding aspects of this work was showing that incorporating realistic short-term host movement can substantially change our understanding of disease spread. Our findings suggest that models that overlook these movement patterns can produce biased estimates of key epidemiological parameters and underestimate the role of short-term visitors in shaping outbreak dynamics.
Albert Soewongsono
Washington University in Saint Louis
Read the Original
This page is a summary of: Inferring epidemiological parameters under an infectious phylogeography model with visitor dynamics, Proceedings of the National Academy of Sciences, July 2026, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2535042123.
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