Incorporating seasonality and other long-term trends improves surveillance for acute respiratory infections


As the electronic medical record (EMR) market matures, long-term time series of EMR-based surveillance data are becoming available. In this work, we hypothesized that statistical aberrancy-detection methods that incorporate seasonality and other long-term data trends reduce the time required to discover an influenza outbreak compared with methods that only consider the most recent past.

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December, 2010

June 18, 2019

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