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Real-time outbreak and disease surveillance system (RODS) is a syndromic surveillance system developed by the University of Pittsburgh, Department of Biomedical Informatics.〔 It is "prototype developed at the University of Pittsburgh where real-time clinical data from emergency departments within a geographic region can be integrated to provide an instantaneous picture of symptom patterns and early detection of epidemic events."〔''Public Health-Related Activities'' at the (US HHS government website ). Accessed December 2, 2010.〕 RODS uses a combination of various monitoring tools.〔 # The first tool is a moving average with a 120-day sliding phase-I-window. # The second tool is a nonstandard combination of CUSUM and EWMA, where an EWMA is used to predict next-day counts, and a CuSum monitors the residuals from these predictions. # The third monitoring tool in RODS is a recursive least squares (RLS) algorithm, which fits an autoregressive model to the counts and updates estimates continuously by minimizing prediction error. A Shewhart I-chart is then applied to the residuals, using a threshold of 4 standard deviations. # The fourth tool in RODS implements a wavelet approach, which decomposes the time series using Haar wavelets, and uses the lowest resolution to remove long-term trends from the raw series. The residuals are then monitored using an ordinary Shewhart I-chart with a threshold of 4 standard deviations. == References == 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Real-time outbreak and disease surveillance」の詳細全文を読む スポンサード リンク
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