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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.

作者:Elizabeth C, Lee;Jason M, Asher;Sandra, Goldlust;John D, Kraemer;Andrew B, Lawson;Shweta, Bansal

来源:The Journal of infectious diseases 2016 年 214卷 suppl_4期

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作者:
Elizabeth C, Lee;Jason M, Asher;Sandra, Goldlust;John D, Kraemer;Andrew B, Lawson;Shweta, Bansal
来源:
The Journal of infectious diseases 2016 年 214卷 suppl_4期
标签:
digital epidemiology disease mapping infectious diseases spatial big data spatial epidemiology statistical bias
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.