Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 422
This document gives an introduction to the R-Package 'surveillance' containing tools for outbreak detection in routinely collected surveillance data. The package contains an implementation of the procedures described by Stroup et al. (1989), Farrington et al. (1996) and the system used at the Robert Koch Institute, Germany. For evaluation purposes, the package contains example data sets and functionality to generate surveillance data by simulation. To compare the algorithms, benchmark numbers like sensitivity, specificity, and detection delay can be computed for a set of time series. Being an open-source package it should be easy to integrate new algorithms; as an example of this process, a simple Bayesian surveillance algorithm is described, implemented and evaluated.
infectious disease monitoring aberrations outbreak time series of counts