Real-time outbreak and disease surveillance system (RODS) is a
syndromic surveillance system developed by the
University of Pittsburgh, Department of Biomedical
Informatics.[1] 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."[2]
RODS uses a combination of various monitoring tools.[3]
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 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.