The individual movements of large numbers of people are important in many contexts, from urban planning to disease spreading. Datasets that capture human mobility are now available and many interesting features have been discovered, including the ultra-slow spatial growth of individual mobility. However, the detailed substructures and spatiotemporal flows of mobility--the sets and sequences of ...

Understanding spatio-temporal patterns of host mobility is a key factor to prevent and control animal and human diseases. This is utterly important in low-income countries, where animal disease epidemics have strong socio-economic impacts. In this article we analyzed a livestock mobility database, whose data have been collected by the Centre National d'Elevage et de Recherches Vétérinaires (CNE...

This paper reviews the effect of natural disasters on human mobility or migration. Although there is an increase of natural disasters and migration recently and more patterns to observe, the relationship remains complex. While some authors find that disasters increase migration, others show that they have only a marginal or no effect or are even negative. Human mobility appears to be an insuran...

Modeling human mobility is crucial in the analysis and simulation of opportunistic networks, where contacts are exploited as opportunities for peer-topeer message forwarding. The current approach with human mobility modeling has been based on continuously modifying models, trying to embed in them the mobility properties (e.g., visiting patterns to locations or specific distributions of inter-co...

Mobility has been measured in the form of gait analysis – a method used to assess the physical functioning of a human. Many health-related clinical and pathological gait analysis applications have been proposed in the last decades. Gait analysis research has been predominantly conducted in laboratories in a discipline-specific manner. The main measurement approach is to monitor intrinsic gait p...

The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location. Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predic...

By analyzing data reflecting human mobility, one can derive patterns and knowledge that are tightly linked to the underlying geography and therefore cannot be applied to another territory or even compared with patterns obtained for another territory. Another problem of mobility analysis is compromising personal privacy, since person identities can be determined based on the regularly visited ge...

Here we present the Global Epidemic and Mobility (GLEaM) model that integrates sociodemographic and population mobility data in a spatially structured stochastic disease approach to simulate the spread of epidemics at the worldwide scale. We discuss the flexible structure of the model that is open to the inclusion of different disease structures and local intervention policies. This makes GLEaM...

Urban areas are responsible for consuming up to 80% of the energy produced worldwide, mainly as a result of human activities. Due to the constantly increasing world population and the shift of this population into cities, over 60% of the world population is projected to reside in urban areas by 2030 and the corresponding increase in human activities will lead to a tremendous increase in energy ...

Advanced technology in GPS and sensors enables us to track moving objects, such as human beings, animals, vehicles. These mobility data as historical activity data of moving objects, in some degree can reflect some internal and external features of moving objects, how to use the massive high-precision mobile data identify potential and meaningful pattern is the current hot spots and is also a s...