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Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference

Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of...

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Detalles Bibliográficos
Autores principales: Lee, Elizabeth C., Asher, Jason M., Goldlust, Sandra, Kraemer, John D., Lawson, Andrew B., Bansal, Shweta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144899/
https://www.ncbi.nlm.nih.gov/pubmed/28830109
http://dx.doi.org/10.1093/infdis/jiw344
Descripción
Sumario:Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales.