Abstract
Human travel is one of the primary drivers of infectious disease spread. Models of travel are often used that assume the amount of travel to a specific destination decreases as cost of travel increases with higher travel volumes to more populated destinations. Trip duration, the length of time spent in a destination, can also impact travel patterns. We investigated the spatial patterns of travel conditioned on trip duration and find distinct differences between short and long duration trips. In short-trip duration travel networks, trips are skewed towards urban destinations, compared with long-trip duration networks where travel is more evenly spread among locations. Using gravity models to inform connectivity patterns in simulations of disease transmission, we show that pathogens with shorter generation times exhibit initial patterns of spatial propagation that are more predictable among urban locations. Further, pathogens with a longer generation time have more diffusive patterns of spatial spread reflecting more unpredictable disease dynamics.
Highlights
During an infectious disease outbreak, anticipating where a pathogen will spread is an important part of planning an effective response [1,2]
We analyzed travel data and found specific spatial patterns in trip duration, where short-duration trips are more common between urban destinations and long-duration trips are evenly spread out among locations
To show how this spatial pattern impacts the spread of infectious diseases, we used data-driven models and simulations to show that pathogens with shorter generation times have patterns of spatial spread that are more predictable among urban locations
Summary
During an infectious disease outbreak, anticipating where a pathogen will spread is an important part of planning an effective response [1,2]. The initial stages of an outbreak are typically characterized by spatial dynamics through the population from an introduction event, such as the 2014 Ebola outbreak in West Africa [3] and the COVID-19 pandemic [4] which started at the end of 2019. These outbreaks provide clear examples of how quickly a pathogen can spread through a highly susceptible population. Recent methods have relied more heavily on detailed information about human mobility patterns [23,24,25] to inform the spatial dynamics of disease spread
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