Welcome to surveillance project!

The R-package 'surveillance' is a framework for the development and the evaluation of outbreak detection algorithms in univariate and multivariate routine collected public health surveillance data. It is hosted on CRAN.

• The intention of the R-package surveillance is to provide open source software for the visualization and monitoring of count data time series in public health surveillance. Potential users are epidemiologists and others working in applied infectious disease epidemiology.
• Furthermore, surveillance also provides a data structure and framework for methodological developments of surveillance algorithms.
• Among others the package contains an implementation of the following procedures:
• Stroup et al. (1989)
• Farrington et al. (1996)
• The system used at the Robert Koch Institute (RKI), Germany.
• A Bayesian predictive posterior approach documented in Höhle (2007)
  
• An online version of the Hidden Markov Model approach by Le Strat and Carrat (1999)
• Surveillance for time varying Poisson means as documented in Rogerson and Yamada (2004).
  This approach has been extended to cover time varying proportions in a binomial setting.
• An approximate CUSUM method for time varying Poisson means as documented in Rossi et al (1999)
• Generalized likelihood ratio detectors for time varying Poisson and negative binomial means documented in Höhle and Paul (2008)
  
• Furthermore the package contains estimation and prediction routines for the models described in
  • Held et al. (2005)
  • Held et al. (2006)
• For evaluation purposes, the package contains example datasets drawn from the SurvStat@RKI Database maintained the RKI, Germany. More comprehensive comparisons using simulation studies are possible by methods for simulating point source outbreak data using a hidden Markov model. To compare the algorithms, benchmark numbers like sensitivity, specificity and detection delay can be computed for entire sets of surveillance time series.
• The package comes with ABSOLUTELY NO WARRANTY; for details see http://www.gnu.org/copyleft/gpl.html (GPL). This is free software, and and you are welcome to redistribute it under the GPL conditions.

The surveillance package (version 1.0-2) is available for download from CRAN.
Current package development, help-forum and bugtracking is hosted through R-Forge:

https://r-forge.r-project.org/projects/surveillance/

From this page snapshots of the current development version 1.0-3 are available.

New features:

• (>0.9-10) See NEWS file in the current distribution

• A good introduction to the package is provided in the paper surveillance: An R package for the surveillance of infectious diseases, Computational Statistics (2007), 22(4), pp. 571-582. [preprint]
• An overview of statistical methods and implementational usage is given the course notes of the short course on Statistical surveillance of infectious diseases held at the Department of Statistics, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil, Nov 27-28, 2008.
• Invited talk held at the ESCAIDE satellite workshop on Computer supported outbreak detection and signal management (R-File, Data from SurvStat@RKI)
• Use of the package in veterinary public health surveillance can be found in Statistical approaches to the surveillance of infectious diseases for veterinary public health
• Read the package vignette
• Sometimes one picture says more than 1000 words:

• Michael Höhle, Department of Statistics, University of Munich, Germany (Project Admin)
• Michaela Paul, Institute of Social and Preventive Medicine, University of Zurich, Switzerland
• Former student programmers: C. Lang, Andrea Riebler, Valentin Wimmer
• Contributions by: T. Correa, M. Hofmann

The development of models and algorithms implemented in surveillance was financially supported by :

• Munich Center of Health Sciences (MC-Health, since 2007)
• Swiss National Science Foundation (SNF, since 2007)
• German Science Foundation (DFG, 2003-2006)