Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand.
Institut Laue-Langevin, 71 Avenue des Martyrs, 38042, Grenoble, France.
Sci Rep. 2020 Jul 9;10(1):11325. doi: 10.1038/s41598-020-68230-9.
Human mobility plays a crucial role in the temporal and spatial spreading of infectious diseases. During the past few decades, researchers have been extensively investigating how human mobility affects the propagation of diseases. However, the mechanism of human mobility shaping the spread of epidemics is still elusive. Here we examined the impact of human mobility on the infectious disease spread by developing the individual-based SEIR model that incorporates a model of human mobility. We considered the spread of human influenza in two contrasting countries, namely, Belgium and Martinique, as case studies, to assess the specific roles of human mobility on infection propagation. We found that our model can provide a geo-temporal spreading pattern of the epidemics that cannot be captured by a traditional homogenous epidemic model. The disease has a tendency to jump to high populated urban areas before spreading to more rural areas and then subsequently spread to all neighboring locations. This heterogeneous spread of the infection can be captured by the time of the first arrival of the infection [Formula: see text], which relates to the landscape of the human mobility characterized by the relative attractiveness. These findings can provide insights to better understand and forecast the disease spreading.
人类移动性在传染病的时空传播中起着至关重要的作用。在过去的几十年中，研究人员一直在广泛研究人类移动性如何影响疾病的传播。然而，人类移动性塑造传染病传播的机制仍然难以捉摸。在这里，我们通过开发个体为基础的 SEIR 模型来研究人类移动性对传染病传播的影响，该模型纳入了人类移动性模型。我们以比利时和马提尼克两个对比国家的人类流感传播为例，评估了人类移动性对感染传播的具体作用。我们发现，我们的模型可以提供传染病的地理和时间传播模式，而传统的均匀传染病模型无法捕捉到这一模式。疾病在传播到更偏远的农村地区之前，有倾向于先传播到人口稠密的城市地区，然后再传播到所有邻近的地区。这种感染的异质传播可以通过感染的首次到达时间 [Formula: see text] 来捕捉，这与以相对吸引力为特征的人类移动性景观有关。这些发现可以为更好地理解和预测疾病传播提供一些思路。
