Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena
Formatted Time Axis for "sts" Objects
Add Harmonics to an Existing Formula
Aggregate a disProg Object
The Bayes System
Query Transmission to Specified Surveillance Algorithm
The CDC Algorithm
Comparison of Specified Surveillance Systems using Quality Values
CUSUM method
Assign weights to base counts
Fit Poisson GLM of the Farrington procedure for a single time point
Surveillance for Count Time Series Using the Classic Farrington Method
Compute prediction interval for a new observation
Count Data Regression Charts
Hidden Markov Model (HMM) method
Semiparametric surveillance of outbreaks
Computation of Quality Values for a Surveillance System Result
The system used at the RKI
Modified CUSUM method as proposed by Rogerson and Yamada (2004)
Summary Table Generation for Several Disease Chains
Test if Two Model Fits are (Nearly) Equal
Generic animation of spatio-temporal objects
Compute Anscombe Residuals
Calculation of Average Run Length for discrete CUSUM schemes
Non-parametric back-projection of incidence cases to exposure cases us...
Partition of a number into two factors
Bayesian Outbreak Detection Algorithm (BODA)
Bayesian Outbreak Detection in the Presence of Reporting Delays
Calibration Tests for Poisson or Negative Binomial Predictions
CUSUM detector for time-varying categorical time series
Check the residual process of a fitted twinSIR or twinstim
Conditional lapply
List Coefficients by Model Component
Creating an object of class disProg (DEPRECATED)
Polygonal Approximation of a Disc/Circle
Convert disProg object to sts and vice versa
Surveillance for a count data time series using the EARS C1, C2 or C3 ...
Spatio-Temporal Animation of an Epidemic
Impute Blocks for Extra Stops in "epidata" Objects
Plotting the Evolution of an Epidemic
Summarizing an Epidemic
Continuous-Time SIR Event History of a Fixed Population
Conversion (aggregation) of "epidataCS" to "epidata" or "sts"
Spatio-Temporal Animation of a Continuous-Time Continuous-Space Epidem...
Randomly Permute Time Points or Locations of "epidataCS"
Plotting the Events of an Epidemic over Time and Space
Update method for "epidataCS"
Continuous Space-Time Marked Point Patterns with Grid-Based Covariates
Hook function for in-control mean estimation
Fan Plot of Forecast Distributions
Surveillance for Univariate Count Time Series Using an Improved Farrin...
Determine the k and h values in a standard normal setting
Find decision interval for given in-control ARL and reference value
Find Reference Value
Convert Dates to Character (Including Quarter Strings)
Pretty p-Value Formatting
Fit an Endemic-Only twinstim as a Poisson-glm
HCL-based Heat Colors from the colorspace Package
Specify Formulae in a Random Effects HHH Model
Internal Functions Dealing with hhh4 Models
Print, Summary and other Standard Methods for "hhh4" Objects
Plots for Fitted hhh4-models
Predictions from a hhh4 Model
Plot Simulations from "hhh4" Models
Proper Scoring Rules for Simulations from hhh4 Models
Simulate "hhh4" Count Time Series
update a fitted "hhh4" model
Predictive Model Assessment for hhh4 Models
Extract Neighbourhood Weights from a Fitted hhh4 Model
Power-Law and Nonparametric Neighbourhood Weights for hhh4-Models
Fitting HHH Models with Random Effects and Neighbourhood Structure
Plot Paths of Point Process Intensities
Intersection of a Polygonal and a Circular Domain
Find ISO Week and Year of Date Objects
Knox Test for Space-Time Interaction
Plot the ECDF of a uniform sample with Kolmogorov-Smirnov bounds
Layout Items for spplot
Convert Dates of Individual Case Reports into a Time Series of Counts
Run length computation of a CUSUM detector
Compute Suitable k1 x k2 Layout for Plotting
Generate control Settings for an hhh4 Model
Import from package spatstat.geom
Import from package spatstat.geom
Count Number of Instances of Points
Determine Neighbourhood Order Matrix from Binary Adjacency Matrix
Adjust a univariate time series of counts for observed but-not-yet-rep...
Paired binary CUSUM and its run-length computation
Monte Carlo Permutation Test for Paired Individual Scores
Non-Randomized Version of the PIT Histogram (for Count Data)
Verbose and Parallel lapply
Plot Observed Counts and Defined Outbreak States of a (Multivariate) T...
Plot a survRes object
Derive Adjacency Structure of "SpatialPolygons"
Indicate Polygons at the Border
Prime Number Factorization
Print Quality Value Object
Computes reproduction numbers from fitted models
Import from package nlme
Compute indices of reference value using Date class
Extract Cox-Snell-like Residuals of a Fitted Point Process
Sample Points Uniformly on a Disc
Proper Scoring Rules for Poisson or Negative Binomial Predictions
Simulate Point-Source Epidemics
Generation of Background Noise for Simulated Timeseries
Spatio-temporal cluster detection
Diggle et al (1995) K-function test for space-time clustering
Animated Maps and Time Series of Disease Counts or Incidence
Simulate Count Time Series with Outbreaks
Time-Series Plots for "sts" Objects Using ggplot2
Create an sts object with a given observation date
Convert an "sts" Object to a Data Frame in Long (Tidy) Format
Class "sts" -- surveillance time series
Aggregate an "sts" Object Over Time or Across Units
Class "stsBP" -- a class inheriting from class sts which allows the ...
Class "stsNC" -- a class inheriting from class sts which allows the ...
Animate a Sequence of Nowcasts
Map of Disease Counts/Incidence accumulated over a Given Period
Animated Map of Disease Incidence (DEPRECATED)
Time-Series Plots for "sts" Objects
Plot Methods for Surveillance Time-Series Objects
Generic Functions to Access "sts" Slots
Subsetting "sts" Objects
Defunct Functions in Package surveillance
surveillance: tools:::Rd_package_title("surveillance")
Options of the surveillance Package
toLatex-Method for "sts" Objects
Identify Endemic Components in an Intensity Model
Toy Data for twinSIR
Plotting Paths of Infection Intensities for twinSIR Models
Print, Summary and Extraction Methods for "twinSIR" Objects
Profile Likelihood Computation and Confidence Intervals
Simulation of Epidemic Data
Fit an Additive-Multiplicative Intensity Model for SIR Data
Permutation Test for Space-Time Interaction in "twinstim"
Temporal and Spatial Interaction Functions for twinstim
Plot the Spatial or Temporal Interaction Function of a twimstim
Plotting Intensities of Infection over Time or Space
Print, Summary and Extraction Methods for "twinstim" Objects
Plot methods for fitted twinstim's
Profile Likelihood Computation and Confidence Intervals for twinstim...
Simulation from an Isotropic Spatial Kernel via Polar Coordinates
Spatial Interaction Function Objects
Quick Simulation from an Endemic-Only twinstim
Simulation of a Self-Exciting Spatio-Temporal Point Process
Stepwise Model Selection by AIC
Temporal Interaction Function Objects
update-method for "twinstim"
Fit a Two-Component Spatio-Temporal Point Process Model
Compute the Unary Union of "SpatialPolygons"
Randomly Break Ties in Data
Multivariate Surveillance through independent univariate algorithms
Power-Law Weights According to Neighbourhood Order
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 Hoehle 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 Hoehle (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. (2017) <doi:10.18637/jss.v077.i11>.