This paper is in the following e-collection/theme issue:

Presentations, Abstracts, or Demonstrations (740) Influenza and Influenza-Like-Illness (ILI) Surveillance (219)

Published on in Vol 6, No 1 (2014):

Predicting Levels of Influenza Incidence

Predicting Levels of Influenza Incidence

Predicting Levels of Influenza Incidence

Authors of this article:

Anna L. Buczak1 ;   Liane Ramac-thomas1 ;   Erhan Guven1 ;   Yevgeniy Elbert1 ;   Steven Babin1 ;   Benjamin Baugher1 ;   Sheri Lewis
The full text of this article is available as a PDF download by clicking here.
Article Authors Cited by Tweetations Metrics

    Advanced techniques in fuzzy association rule data mining and integrating evidence from multiple sources are used to predict levels of influenza incidence several weeks in advance and display results on a map in order to help public health professionals prepare mitigation measures. This approach exploits the complicated relationships between disease incidence and measurable environmental, biological, and sociological variables that were found to have associations with the disease in other studies. Predictions were compared with data not used in model development in order to avoid exaggerated values of performance. The positive and negative predictive values were 0.941 and 0.935, respectively.