Future directions in analytics for infectious disease intelligence: Toward an integrated warning system for emerging pathogens

Barbara A Han; John M Drake

doi:10.15252/embr.201642534

Future directions in analytics for infectious disease intelligence: Toward an integrated warning system for emerging pathogens

EMBO Rep. 2016 Jun;17(6):785-9. doi: 10.15252/embr.201642534. Epub 2016 May 11.

Authors

Barbara A Han¹, John M Drake²

Affiliations

¹ Cary Institute of Ecosystem Studies, Millbrook, NY, USA.
² Odum School of Ecology, University of Georgia, Athens, GA, USA Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA.

Abstract

Anticipating the emergence of infectious diseases would be more effective in reducing their toll, rather than reacting to an outbreak. Machine learning and simulation tools that use environmental, epidemiological and molecular data could help manage and analyse the flow or risks, and inform appropriate actions by public health authorities.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Communicable Disease Control / methods
Communicable Disease Control / trends*
Communicable Diseases, Emerging / economics
Communicable Diseases, Emerging / prevention & control*
Decision Support Systems, Clinical*
Disease Outbreaks / prevention & control*
Earthquakes
Global Warming
Humans
Risk
Tsunamis

Grants and funding

U01 GM110744/GM/NIGMS NIH HHS/United States