Cell Phones ≠ Self and Other Problems With Big Data Detection and Containment During Epidemics

Med Anthropol Q. 2018 Sep;32(3):315-339. doi: 10.1111/maq.12440. Epub 2018 Apr 22.

Abstract

Evidence from Sierra Leone reveals the significant limitations of big data in disease detection and containment efforts. Early in the 2014-2016 Ebola epidemic in West Africa, media heralded HealthMap's ability to detect the outbreak from newsfeeds. Later, big data-specifically, call detail record data collected from millions of cell phones-was hyped as useful for stopping the disease by tracking contagious people. It did not work. In this article, I trace the causes of big data's containment failures. During epidemics, big data experiments can have opportunity costs: namely, forestalling urgent response. Finally, what counts as data during epidemics must include that coming from anthropological technologies because they are so useful for detection and containment.

Keywords: Ebola; big data; cell phones; digital humanitarianism; global health; technology.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Altruism
  • Anthropology, Medical
  • Big Data*
  • Cell Phone*
  • Epidemics / prevention & control*
  • Global Health*
  • Hemorrhagic Fever, Ebola
  • Humans
  • Information Dissemination*
  • Sierra Leone