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

被引:40
作者
Lee, Elizabeth C. [1 ]
Asher, Jason M. [3 ]
Goldlust, Sandra [1 ]
Kraemer, John D. [2 ]
Lawson, Andrew B. [4 ]
Bansal, Shweta [1 ,5 ]
机构
[1] Georgetown Univ, Dept Biol, 408 Reiss Sci Bldg, Washington, DC 20057 USA
[2] Georgetown Univ, Dept Hlth Syst Adm, Washington, DC USA
[3] Leidos, Washington, DC USA
[4] Med Univ South Carolina, Dept Publ Hlth Sci, Charleston, SC USA
[5] NIH, Fogarty Int Ctr, Bldg 10, Bethesda, MD 20892 USA
基金
美国国家卫生研究院;
关键词
spatial big data; spatial epidemiology; disease mapping; infectious diseases; digital epidemiology; statistical bias;
D O I
10.1093/infdis/jiw344
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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.
引用
收藏
页码:S409 / S413
页数:5
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