surveillance v1.12.1

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by Sebastian Meyer

Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena. The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of H�hle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available monitoring procedures is given by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>. For the retrospective analysis of epidemic spread, the package provides three endemic-epidemic modeling frameworks with tools for visualization, likelihood inference, and simulation. 'hhh4' estimates models for (multivariate) count time series following Paul and Held (2011) <doi:10.1002/sim.4177> and Meyer and Held (2014) <doi:10.1214/14-AOAS743>. 'twinSIR' models the susceptible-infectious-recovered (SIR) event history of a fixed population, e.g, epidemics across farms or networks, as a multivariate point process as proposed by H�hle (2009) <doi:10.1002/bimj.200900050>. 'twinstim' estimates self-exciting point process models for a spatio-temporal point pattern of infective events, e.g., time-stamped geo-referenced surveillance data, as proposed by Meyer et al. (2012) <doi:10.1111/j.1541-0420.2011.01684.x>. A recent overview of the implemented space-time modeling frameworks for epidemic phenomena is given by Meyer et al. (2015) <http://arxiv.org/abs/1411.0416>.

Functions in surveillance

Name Description
imdepi Occurrence of Invasive Meningococcal Disease in Germany
plot.disProg Plot Generation of the Observed and the defined Outbreak States of a (multivariate) time series
stK Diggle et al (1995) K-function test for space-time clustering
epidataCS_update Update method for "epidataCS"
sts-class Class "sts" -- surveillance time series
R0 Computes reproduction numbers from fitted models
LRCUSUM.runlength Run length computation of a CUSUM detector
abattoir Abattoir Data
algo.call Query Transmission to Specified Surveillance Algorithm
algo.hmm Hidden Markov Model (HMM) method
anscombe.residuals Compute Anscombe Residuals
untie Randomly Break Ties in Data
aggregate.disProg Aggregate the observed counts
epidata Continuous-Time SIR Event History of a Fixed Population
formatPval Pretty p-Value Formatting
twinstim_step Stepwise Model Selection by AIC
calibrationTest Calibration Test for Poisson or Negative Binomial Predictions
algo.farrington Surveillance for a count data time series using the Farrington method.
animate Generic animation of spatio-temporal objects
estimateGLRNbHook Hook function for in-control mean estimation
compMatrix.writeTable Latex Table Generation
boda Surveillance for an univariate count data time series using the Bayesian Outbreak Detection Algorithm (BODA) described in Manitz and H�hle{Hoehle} (2013)
nowcast Adjust a univariate time series of counts for observed but-not-yet-reported events
deleval Surgical failures data
shadar Salmonella Hadar cases in Germany 2001-2006
hhh4_methods Print, Summary and other Standard Methods for "hhh4" Objects
coeflist List Coefficients by Model Component
readData Reading of Disease Data
epidataCS_animate Spatio-Temporal Animation of a Continuous-Time Continuous-Space Epidemic
checkResidualProcess Check the residual process of a fitted twinSIR or twinstim
meanResponse Calculate mean response needed in algo.hhh
pit Non-Randomized Version of the PIT Histogram (for Count Data)
enlargeData Data Enlargement
correct53to52 Data Correction from 53 to 52 weeks
epidata_summary Summarizing an Epidemic
knox Knox Test for Space-Time Interaction
multiplicity.Spatial Count Number of Instances of Points
algo.rki The system used at the RKI
twinSIR_profile Profile Likelihood Computation and Confidence Intervals
arlCusum Calculation of Average Run Length for discrete CUSUM schemes
twinSIR_cox Identify Endemic Components in an Intensity Model
backprojNP Non-parametric back-projection of incidence cases to exposure cases using a known incubation time as in Becker et al (1991).
hagelloch 1861 Measles Epidemic in the City of Hagelloch, Germany
marks Import from package spatstat
multiplicity Import from package spatstat
momo Danish 1994-2008 all cause mortality data for six age groups
sts_animate Animated Maps and Time Series of Disease Incidence
m1 RKI SurvStat Data
salmNewport Salmonella Newport cases in Germany 2004-2013
stsplot Plot-Methods for Surveillance Time-Series Objects
unionSpatialPolygons Compute the Unary Union of "SpatialPolygons"
algo.quality Computation of Quality Values for a Surveillance System Result
twinSIR_intensityplot Plotting Paths of Infection Intensities for twinSIR Models
hhh4 Fitting HHH Models with Random Effects and Neighbourhood Structure
twinSIR Fit an Additive-Multiplicative Intensity Model for SIR Data
magic.dim Returns a suitable k1 x k2 for plotting the disProgObj
rotaBB Rotavirus cases in Brandenburg, Germany, during 2002-2013 stratified by 5 age categories
stsBP-class Class "stsBP" -- a class inheriting from class sts which allows the user to store the results of back-projecting or nowcasting surveillance time series
plot.hhh4 Plots for Fitted hhh4-models
wrap.algo Multivariate Surveillance through independent univariate algorithms
hhh4_predict Predictions from a hhh4 Model
linelist2sts Convert individual case information based on dates into an aggregated time series of counts
measles.weser Measles in the Weser-Ems region of Lower Saxony, Germany, 2001-2002
twinstim_update update-method for "twinstim"
twinstim_iafplot Plot the Spatial or Temporal Interaction Function of a twimstim
polyAtBorder Indicate Polygons at the Border
simHHH Simulates data based on the model proposed by Held et. al (2005)
test Print xtable for several diseases and the summary
twinstim_epitest Permutation Test for Space-Time Interaction in "twinstim"
twinstim_siaf Spatial Interaction Function Objects
algo.cdc The CDC Algorithm
discpoly Polygonal Approximation of a Disc/Circle
inside.gpc.poly Test Whether Points are Inside a "gpc.poly" Polygon
stcd Spatio-temporal cluster detection
algo.bayes The Bayes System
algo.farrington.assign.weights Assign weights to base counts
hepatitisA Hepatitis A in Germany
twinstim_intensity Plotting Intensities of Infection over Time or Space
glm_epidataCS Fit an Endemic-Only twinstim as a Poisson-glm
findH Find decision interval for given in-control ARL and reference value
hhh4_W Power-Law and Nonparametric Neighbourhood Weights for hhh4-Models
findK Find reference value
algo.farrington.threshold Compute prediction interval for a new observation
algo.farrington.fitGLM Fit the Poisson GLM of the Farrington procedure for a single time point
create.grid Create a Matrix of Initial Values for algo.hhh.grid
epidataCS_aggregate Conversion (aggregation) of "epidataCS" to "epidata" or "sts"
husO104Hosp Hospitalization date for HUS cases of the STEC outbreak in Germany, 2011
isoWeekYear Find ISO week and ISO year of a vector of Date objects on Windows
hhh4_simulate_plot Summarize Simulations from "hhh4" Models
makePlot Plot Generation
nbOrder Determine Neighbourhood Order Matrix from Binary Adjacency Matrix
runifdisc Sample Points Uniformly on a Disc
isScalar Checks if the Argument is Scalar
hhh4_update update a fitted "hhh4" model
print.algoQV Print quality value object
scale.gpc.poly Centering and Scaling a "gpc.poly" Polygon
algo.outbreakP Semiparametric surveillance of outbreaks
sim.seasonalNoise Generation of Background Noise for Simulated Timeseries
create.disProg Creating an object of class disProg
epidata_animate Spatio-Temporal Animation of an Epidemic
epidataCS Continuous Space-Time Marked Point Patterns with Grid-Based Covariates
meningo.age Meningococcal infections in France 1985-1995
farringtonFlexible Surveillance for an univariate count data time series using the improved Farrington method described in Noufaily et al. (2012).
fluBYBW Influenza in Southern Germany
ks.plot.unif Plot the ECDF of a uniform sample with Kolmogorov-Smirnov bounds
plot.atwins Plot results of a twins model fit
refvalIdxByDate Compute indices of reference value using Date class
plot.survRes Plot a survRes object
residuals.ah Residuals from a HHH model
surveillance-package [stage=build]{(meta
stsplot_spacetime Map of Disease Incidence
toLatex.sts toLatex-Method for "sts" Objects
salmAllOnset Salmonella cases in Germany 2001-2014 by data of symptoms onset
stsNewport Salmonella Newport cases in Germany 2004-2013
algo.cusum CUSUM method
algo.hhh Fit a Classical HHH Model (DEPRECATED)
campyDE Cases of Campylobacteriosis and Absolute Humidity in Germany 2002-2011
epidata_plot Plotting the Evolution of an Epidemic
addFormattedXAxis Formatted Time Axis for "sts" Objects
ha Hepatitis A in Berlin
algo.twins Model fit based on a two-component epidemic model
earsC Surveillance for a count data time series using the EARS C1, C2 or C3 method.
sts_observation Function for creating a sts-object with a given observation date
epidataCS_plot Plotting the Events of an Epidemic over Time and Space
hhh4_formula Specify Formulae in a Random Effects HHH Model
zetaweights Power-Law Weights According to Neighbourhood Order
hhh4_simulate Simulate "hhh4" Count Time Series
hhh4_validation Predictive Model Assessment for hhh4 Models
intersectPolyCircle Intersection of a Polygonal and a Circular Domain
[,sts-methods Extraction and Subsetting of "sts" Objects
stsplot_time Time-Series Plots for "sts" Objects
sim.pointSource Simulate Point-Source Epidemics
stsplot_space Map of Disease Incidence During a Given Period
epidataCS_permute Randomly Permute Time Points or Locations of "epidataCS"
influMen Influenza and meningococcal infections in Germany, 2001-2006
primeFactors Prime number factorization
qlomax Quantile Function of the Lomax Distribution
loglikelihood Calculation of the loglikelihood needed in algo.hhh
stsSlot-generics Generic functions to access "sts" slots
sts_creation Function for simulating a time series
twinSIR_simulation Simulation of Epidemic Data
residualsCT Extract Cox-Snell-like Residuals of a Fitted Point Process
twinstim_simulation Simulation of a Self-Exciting Spatio-Temporal Point Process
MMRcoverageDE MMR coverage levels in the 16 states of Germany
algo.hhh.grid Fit a Classical HHH Model (DEPRECATED) with Varying Start Values
algo.rogerson Modified CUSUM method as proposed by Rogerson and Yamada (2004)
layout.labels Layout Items for spplot
categoricalCUSUM CUSUM detector for time-varying categorical time series
disProg2sts Convert disProg object to sts and vice versa
hhh4_calibration Test Calibration of a hhh4 Model
predict.ah Predictions from a HHH model
measlesDE Measles in the 16 states of Germany
salmHospitalized Hospitalized Salmonella cases in Germany 2004-2014
find.kh Determine the k and h values in a standard normal setting
plapply Verbose and Parallel lapply
toFileDisProg Writing of Disease Data
siaf.simulatePC Simulation from an Isotropic Spatial Kernel via Polar Coordinates
addSeason2formula Function that adds a sine-/cosine formula to an existing formula.
algo.compare Comparison of Specified Surveillance Systems using Quality Values
algo.glrnb Count Data Regression Charts
bodaDelay Bayesian Outbreak Detection in the Presence of Reporting Delays
algo.summary Summary Table Generation for Several Disease Chains
epidata_intersperse Impute Blocks for Extra Stops in "epidata" Objects
poly2adjmat Derive Adjacency Structure of "SpatialPolygons"
twinSIR_exData Toy Data for twinSIR
twinstim_plot Plot methods for fitted twinstim's
twinstim_tiaf Temporal Interaction Function Objects
all.equal Test if Two Model Fits are (Nearly) Equal
permutationTest Monte Carlo Permutation Test for Paired Individual Scores
xtable.algoQV Xtable quality value object
intensityplot Plot Paths of Point Process Intensities
pairedbinCUSUM Paired binary CUSUM and its run-length computation
make.design Create the design matrices
salmonella.agona Salmonella Agona cases in the UK 1990-1995
bestCombination Partition of a number into two factors
ranef Import from package nlme
twinSIR_methods Print, Summary and Extraction Methods for "twinSIR" Objects
aggregate-methods Aggregate an "sts" Object Over Time or Across Units
stsNC-class Class "stsNC" -- a class inheriting from class sts which allows the user to store the results of back-projecting surveillance time series
twinstim_methods Print, Summary and Extraction Methods for "twinstim" Objects
twinstim_iaf Temporal and Spatial Interaction Functions for twinstim
twinstim_profile Profile Likelihood Computation and Confidence Intervals for twinstim objects
sumNeighbours Calculates the sum of counts of adjacent areas
testSim Print xtable for a Simulated Disease and the Summary
twinstim Fit a Two-Component Spatio-Temporal Point Process Model
surveillance.options Options of the surveillance Package
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