hhh4contacts v0.13.1


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Age-Structured Spatio-Temporal Models for Infectious Disease Counts

Meyer and Held (2017) <doi:10.1093/biostatistics/kxw051> present an age-structured spatio-temporal model for infectious disease counts. The approach is illustrated in a case study on norovirus gastroenteritis in Berlin, 2011-2015, by age group, city district and week, using additional contact data from the POLYMOD survey. This package contains the data and code to reproduce the results from the paper, see 'demo("hhh4contacts")'.

Functions in hhh4contacts

Name Description
contactmatrix POLYMOD Contact Matrices for Germany
plotHHH4_maps_groups Plot Mean Components of a hhh4 Fit by District Averaged Over Time
stratum Extract Strata
plotHHH4_season_groups Plot Seasonality of a hhh4 Fit by Group
stationary Stationary Distribution of a Transition Matrix
pop2011 Berlin and German Population by Age Group, 2011
powerC Exponentiate a Matrix via Eigendecomposition
plotHHH4_fitted_groups Plot Mean Components of a hhh4 Fit by Group
plotC Generate an Image of a Contact Matrix
stsplothook Hook functions for stsplot_time1
subset.array Subset an Array in one Dimension
dssAggregate Compute the DSS on Aggregated Predictions and Observations
aggregateC Aggregate a Contact Matrix
addGroups2WFUN Group-Dependent Parametric Weights
fitC Estimate the Power of the Contact Matrix in a "hhh4" Model
expandC Expand the Contact Matrix over Regions
adaptP Adapt a Transition Matrix to a Specific Stationary Distribution
C2pop Adapt a Contact Matrix to Population Fractions
noroBE Create "sts" Objects from the Berlin Norovirus Data
aggregateCountsArray Aggregate an Array of Counts wrt One Dimension (Stratum)
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Date 2020-03-20
License GPL-2
LazyData yes
RoxygenNote 7.1.0
NeedsCompilation no
Packaged 2020-03-20 15:19:46 UTC; smeyer
Repository CRAN
Date/Publication 2020-03-20 16:00:03 UTC

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