Drivers of emerging infectious disease events as a framework for digital detection

Sarah H. Olson, Corey M. Benedum, Sumiko R. Mekaru, Nicholas D. Preston, Jonna A Mazet, Damien O. Joly, John S. Brownstein

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data.

Original languageEnglish (US)
Pages (from-to)1285-1292
Number of pages8
JournalEmerging Infectious Diseases
Issue number8
StatePublished - Jul 23 2015

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases
  • Epidemiology


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