![]() Within the social sciences, this temporally dynamic concept of incorporating an individual’s experiences is foundational to informing how social inequalities persist through mechanisms such as racial segregation, how individuals are exposed to environmental hazards, and how accessibility varies to social and health resources. Geographical context is strongly linked to the critical concept of “neighbourhood”, or the spatial context of a given individual. The health sciences have increasingly focused on human movement in recent decades, accounting for the importance of geographical context in driving health inequalities and exposure to environmental risks. Understanding human mobility and how it manifests across temporal and spatial scales is important across the health and social sciences, as mobility patterns drive important spatial processes from infrastructure and land use to infectious disease spread. While biases exist in populations with GLH data, Android phones are becoming the first and only device purchased to access the Internet and various web services in many middle and lower income settings, making these data increasingly appropriate for a wide range of scientific questions. GLH data are a greatly underutilized and novel dataset for understanding human movement. We discuss some settings where GLH data could provide novel insights, including infrastructure planning, infectious disease control, and response to catastrophic events, and discuss advantages and disadvantages of using GLH data to inform human mobility patterns. We also find GLH data avoid compliance concerns seen with GPS trackers and bias in self-reported travel, as GLH is passively collected. We find that GLH data span very long temporal periods (over a year on average in our sample), are spatially equivalent to GPS tracker data within 100 m, and capture more international movement than survey data. We validate GLH data against GPS tracker data collected from Android users in the United Kingdom to assess the feasibility of using GLH data to inform human movement. These data are passively collected by Android smartphones, which reach increasingly broad audiences, becoming the most common operating system for accessing the Internet worldwide in 2017. Here, we collect Google Location History (GLH) data and examine it as a novel source of information that could link fine scale mobility with rare, long distance and international trips, as it uniquely spans large temporal scales with high spatial granularity. While typical sources of mobility data such as travel history surveys and GPS tracker data can inform different typologies of movement, almost no source of readily obtainable data can address all types of movement at once. Detailed mobility data across spatial and temporal scales are difficult to collect, however, with movements varying from short, repeated movements to work or school, to rare migratory movements across national borders. Human mobility is fundamental to understanding global issues in the health and social sciences such as disease spread and displacements from disasters and conflicts.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |