Quantifying the effect of media limitations on outbreak data in a global online web-crawling epidemic intelligence system, 2008-2011

Emerging Health Threats Journal

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Field Value
 
Title Quantifying the effect of media limitations on outbreak data in a global online web-crawling epidemic intelligence system, 2008-2011
 
Creator Scales, David; Children’s Hospital Informatics Program, Boston Children’s Hospital, Harvard Medical School, 10 Shattuck St., Boston, MA 02115, USA.
Zelenev, Alexei
Brownstein, John S.
 
Subject Epidemiology; Surveillance and Reporting; Infectious Disease
epidemic intelligence; infectious diseases; system evaluation; HealthMap; crowd out effect
RA648.5-767
 
Description Background: This is the first study quantitatively evaluating the effect that media-related limitations have on data from an automated epidemic intelligence system.Methods: We modeled time series of HealthMap’s two main data feeds, Google News and Moreover, to test for evidence of two potential limitations: first, human resources constraints, and second, high-profile outbreaks ‘‘crowding out’’ coverage of other infectious diseases.Results: Google News events declined by 58.3%, 65.9%, and 14.7% on Saturday, Sunday and Monday, respectively, relative to other weekdays. Events were reduced by 27.4% during Christmas/New Years weeks and 33.6% lower during American Thanksgiving week than during an average week for Google News. Moreover data yielded similar results with the addition of Memorial Day (US) being associated with a 36.2% reduction in events. Other holiday effects were not statistically significant. We found evidence for a crowd out phenomenon for influenza/H1N1, where a 50% increase in influenza events corresponded with a 4% decline in other disease events for Google News only. Other prominent diseases in this database - avian influenza (H5N1), cholera, or foodborne illness - were not associated with a crowd out phenomenon.Conclusions: These results provide quantitative evidence for the limited impact of editorial biases on HealthMap’s web-crawling epidemic intelligence.Keywords: epidemic intelligence; infectious diseases; system evaluation; HealthMap; crowd out effect(Published: 8 November 2013)Citation: Emerg Health Threats J 2013, 6: 21621 - http://dx.doi.org/10.3402/ehtj.v6i0.21621
 
Publisher Emerging Health Threats Journal
 
Contributor
 
Date 2013-11-08
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

System evaluation
 
Format application/pdf
text/html
application/epub+zip
text/plain
 
Identifier http://journals.co-action.net/index.php/ehtj/article/view/21621
10.3402/ehtj.v6i0.21621
 
Source Emerging Health Threats Journal; Vol 6 (2013) incl Supplements
1752-8550
1752-8550
 
Language eng
 
Relation http://journals.co-action.net/index.php/ehtj/article/view/21621/30901
http://journals.co-action.net/index.php/ehtj/article/view/21621/30902
http://journals.co-action.net/index.php/ehtj/article/view/21621/30903
http://journals.co-action.net/index.php/ehtj/article/view/21621/30904
 
Coverage Global
2008-2011

 

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