real-time outbreak and disease surveillance real-time outbreak and disease surveillance 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." 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.