# 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) No Results!