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

J Infect Dis. 2016 Dec 1;214(suppl_4):S409-S413. doi: 10.1093/infdis/jiw344.

Abstract

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.

Keywords: digital epidemiology; disease mapping; infectious diseases; spatial big data; spatial epidemiology; statistical bias.

Publication types

  • Review
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Communicable Diseases / epidemiology*
  • Epidemiological Monitoring*
  • Health Policy
  • Humans
  • Public Health Administration / ethics
  • Spatial Analysis*
  • Topography, Medical