Epidemiology in the Era of Big Data

Details

• Alternative Title:
  Epidemiology
• Personal Author:
  Mooney, Stephen J ; Westreich, Daniel J ; El-Sayed, Abdulrahman M
• Description:
  Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called "three V's": variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field's future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future.
• Subjects:
  Article Big Data Computer Programming Data Accuracy Emerging Technologies Epidemiologic Methods Epidemiologic Training Epidemiology Forecasting Humans Population Health Public Health

  More +
• Source:
  Epidemiology. 26(3):390-394.
• Pubmed ID:
  25756221
• Pubmed Central ID:
  PMC4385465
• Document Type:
  Journal Article
• Funding:
  DP2 HD084070/HD/NICHD NIH HHS/United States ; DP2HD084070/DP/NCCDPHP CDC HHS/United States ; T32 CA009529/CA/NCI NIH HHS/United States ; T32-CA09529/CA/NCI NIH HHS/United States
• Volume:
  26
• Issue:
  3
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:37a80a9aba2074ff3660fc1c68f231579761295a3cd0eadbdf989f0e291df0f7
• Download URL:
  https://stacks.cdc.gov/view/cdc/31220/cdc_31220_DS1.pdf
• File Type:
  [PDF - 1.32 MB ]