An Early Warning Influenza Model using Alberta Real- Time Syndromic Data (ARTSSN)

An Early Warning Influenza Model using Alberta Real- Time Syndromic Data (ARTSSN)

We developed early warning algorithms for influenza using data from the Alberta Real-Time Syndromic Surveillance Net (ARTSSN). In addition to looking for signatures of potential pandemics, the model was operationalized by using the algorithms to provide regular weekly forecasts on the influenza tren...

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Veröffentlicht in:Online journal of public health informatics 2015-02, Vol.7 (1)
Hauptverfasser: Smetanin, Paul, Biel, Rita K., Stiff, David, McNeil, Douglas, Svenson, Lawrence, Usman, Hussain R., Meurer, David P., Huang, Jane, Nardelli, Vanessa, Sikora, Christopher, Talbot, James
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ISDS 2014 Conference Abstracts
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container_title Online journal of public health informatics
container_volume 7
creator Smetanin, Paul
Biel, Rita K.
Stiff, David
McNeil, Douglas
Svenson, Lawrence
Usman, Hussain R.
Meurer, David P.
Huang, Jane
Nardelli, Vanessa
Sikora, Christopher
Talbot, James
description We developed early warning algorithms for influenza using data from the Alberta Real-Time Syndromic Surveillance Net (ARTSSN). In addition to looking for signatures of potential pandemics, the model was operationalized by using the algorithms to provide regular weekly forecasts on the influenza trends in Alberta during 2012-2014. We describe the development of the early warning model and the predicted influenza peak time and attack rate results. We report on the usefulness of this model using real-time ARTSSN data, discuss how it was used by decision makers and suggest future enhancements for this promising tool in influenza planning and preparedness.
doi_str_mv 10.5210/ojphi.v7i1.5719
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title An Early Warning Influenza Model using Alberta Real- Time Syndromic Data (ARTSSN)
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