Surveillance: An R package for the monitoring of infectious diseases
type: Item
instance of: scholarly article
title: Surveillance: An R package for the monitoring of infectious diseases
zbMATH Open document ID: 1186.62004
author: Michael Höhle
published in: Computational Statistics
publication date: 2010-04-22T00:00:00Z
review text: The `R package surveillance' is considered which offers an implementation of algorithms for detection of outbreaks in univariate or multivariate time series of infectious disease counts. A hidden Markov chain model for such time series is described and algorithms based on reference values are discussed. Change-point detection algorithms like CUSUM are presented. Spatial visualization of the data is also considered. An analysis of data of hepatitis A cases in Berlin is presented.
Mathematics Subject Classification ID: 62-04
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 5697310
zbMATH Keywords: outbreaks detection
zbMATH Keywords: CUSUM
zbMATH Keywords: visualization
zbMATH Keywords: hidden Markov chains
describes a project that uses: R
describes a project that uses: spc
describes a project that uses: maptools
describes a project that uses: Sweave
describes a project that uses: SurvStat@RKI
MaRDI profile type: Publication
full work available at URL: s00180-007-0074-8
OpenAlex ID: W2002243672
cites work: Stochastic epidemic models and their statistical analysis
cites work: A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease
cites work: A two-component model for counts of infectious diseases
cites work: A statistical framework for the analysis of multivariate infectious disease surveillance counts
cites work: On Sequential Detection of a Shift in the Probability of a Rare Event
cites work: Residuals in Generalized Linear Models
DOI: 10.1007/S00180-007-0074-8
description: scientific article; zbMATH DE number 5697310