Abstract
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 (T_{fi} ), 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.
Highlights
Human mobility plays a crucial role in the temporal and spatial spreading of infectious diseases
We found that at the early time of the epidemic, the disease is likely to reach urban areas with high population densities and after an intermediate time, it spreads to rural areas with lower population densities
To deeply understand the impact of human mobility on the epidemics, we exploited a classical SEIR individual-based model that integrates with a model of individual human mobility as proposed by Yan et al.[37] where human mobility is described, both at the individual and population level, with transition probabilities between localities governed by both a gravity-like part and a memory part
Summary
Human mobility plays a crucial role in the temporal and spatial spreading of infectious diseases. Traditional homogenous epidemic models, e.g., a compartmental epidemic model, have long been helpful in understanding the foundation of transmission dynamics of infectious diseases. These homogenous epidemic models assume all human individuals to be well-mixed and ignore heterogeneity that may be resulted from, for example, ages, locations, and contact patterns of human individuals. These homogeneous models are useful in certain situations, in order to gain more accurate modelling results, incorporating factors describing spatiotemporal heterogeneity in disease transmission dynamics into the epidemic models may be necessary. Integrating an epidemic model with an individual human mobility model is necessary for investigating how an individual infectious person geotemporally spread the disease
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