Figure 4.

Seasonal sensitivity trends. Average sensitivity for each month of the study period for the autoregressive (left), trimmed seasonal (center), and expectation-variance (right) models when applied to data containing a superimposed spike outbreak of 10 additional patients during one day. Data shown were collected at a mean specificity of 97%. The sensitivity of the trimmed seasonal and autoregression models is higher during the winter than during the summer. Sensitivity is higher during the summer than during the winter for the expectation-variance model. July receiver-operator (ROC) curves lie below February ROC curves for all three models (insets). Similar trends were observed for flat and linear outbreaks.

Wieland et al. BMC Medical Informatics and Decision Making 2007 7:15   doi:10.1186/1472-6947-7-15
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