Abstract
The aim of outbreak detection model is to obtain high detection rate but at the same time maintaining the low false alarm rate. However, because of the weakness of early outbreak signal that behaves under uncertainties, it causes imbalance result between detection rate and false alarm rate. In this study, an early review of danger theory, an approach of artificial immune system is performed to seek the possibility it can be applied in outbreak detection. To investigate that, a detection model based on danger theory is developed and the model is tested with dengue outbreak dataset. The model is then evaluated in term of detection rate, specificity, false alarm rate, and accuracy. The preliminary result indicates that the proposed model has ability to generate good detection result with a balance between detection rate and false alarm rate.
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