Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/31049
Authors: 
Höhle, Michael
Riebler, Andrea
Year of Publication: 
2005
Series/Report no.: 
Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 422
Abstract: 
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.
Subjects: 
infectious disease
monitoring
aberrations
outbreak
time series of counts
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
526.35 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.