Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Department of Biology and the Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.
PLoS Comput Biol. 2021 Aug 10;17(8):e1009127. doi: 10.1371/journal.pcbi.1009127. eCollection 2021 Aug.
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.
人类旅行是传染病传播的主要驱动因素之一。通常使用旅行模型，假设旅行到特定目的地的数量随着旅行成本的增加而减少，因为更多的旅行量会流向人口较多的目的地。旅行时间（在目的地停留的时间长度）也会影响旅行模式。我们调查了基于旅行时间的旅行的空间模式，发现短时间和长时间旅行之间存在明显差异。在短时间旅行网络中，与长时间旅行网络相比，旅行更倾向于城市目的地，在长时间旅行网络中，旅行在地点之间的分布更加均匀。使用引力模型来告知疾病传播模拟中的连通性模式，我们表明，具有较短世代时间的病原体在城市地点之间表现出更可预测的初始空间传播模式。此外，具有较长世代时间的病原体具有更扩散的空间传播模式，反映出更不可预测的疾病动态。
