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Online Journal of Public Health Informatics
Article . 2016 . Peer-reviewed
Data sources: Crossref
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Online Journal of Public Health Informatics
Article
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Evaluating Syndromic Surveillance Systems

Authors: Lake, Iain; Colón-González, Felipe J.; Morbey, Roger; Elliot, Alex J.; Smith, Gillian E.; Pebody, Richard;

Evaluating Syndromic Surveillance Systems

Abstract

Syndromic surveillance systems are commonly presented in the literature but few are rigorously evaluated. We present and test an evaluation framework to examine which events can and cannot be detected, the time to detection and the efficacy of different syndromic surveillance data streams. This was achieved using four national syndromic surveillance systems in England and simulating a number of possible disease events (e.g. outbreak of pandemic influenza, (Cryptosporidium) outbreak and deliberate anthrax release). This methodology can be widely adopted to provide more empirical analysis of the effectiveness of syndromic surveillance systems worldwide.

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United Kingdom
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold
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