Details:

Alternative Title:
Emerg Infect Dis
Personal Author:
Olson, Sarah H. ; Benedum, Corey M. ; Mekaru, Sumiko R. ; Preston, Nicholas D. ; Mazet, Jonna A.K. ; ... More +
Olson, Sarah H. ; Benedum, Corey M. ; Mekaru, Sumiko R. ; Preston, Nicholas D. ; Mazet, Jonna A.K. ; Joly, Damien O. ; Brownstein, John S. Less -
Description:
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.
Subjects:
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Communicable Diseases, Emerging/epidemiology Communicable Diseases/epidemiology Disease Notification/methods Humans Internet Internet/trends Perspective Population Surveillance/methods
Source:
Emerg Infect Dis. 21(8):1285-1292.
Pubmed ID:
26196106
Pubmed Central ID:
PMC4517741
Document Type:
Journal Article
Collection(s):
Emerging Infectious Diseases
Main Document Checksum:
[+]
urn:sha256:d70434a868390202caf84e5ff40539b60e8b16ffee6ef38e01ed7f209ff9acef
Download URL:
https://stacks.cdc.gov/view/cdc/32649/cdc_32649_DS1.pdf
File Type:

Supporting Files

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  	14-1156-Techapp-s1.pdf	pdf
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