hhh4contacts 0.13.4 (2024-10-07)

• The source code is now hosted in a public Git repository at https://codeberg.org/EE-hub/hhh4contacts.

hhh4contacts 0.13.3 (2023-11-06)

• The package now formally depends on sp (S4 class used by map data), not only implicitly via surveillance.

hhh4contacts 0.13.2 (2023-10-23)

• Minor documentation improvements and updates.

hhh4contacts 0.13.1 (2020-03-20)

• Maintenance for new S3 method lookup in R 4.0.0. NextMethod("confint") in confint.fitC() wouldn’t find a method if confint.fitC() was called directly from summary.fitC().

hhh4contacts 0.13.0 (2017-06-29)

This is the first version published on CRAN. It requires surveillance >= 1.14.0. The main change is in the documentation, which became more comprehensive, especially for the included datasets.

Other changes include:

• Changed the default agegroups parameter in noroBE() (and grouping parameter in contactmatrix()) such that it corresponds to the six age groups used by Meyer and Held (2017).

• The aggregateC() function is now exported.

hhh4contacts 0.12.6 (2017-01-23)

This version has been used for the publication

Held L, Meyer S and Bracher J (2017). “Probabilistic forecasting in infectious disease epidemiology: The 13th Armitage lecture.” Statistics in Medicine, doi: 10.1002/sim.7363.

New features

• An additional year of norovirus surveillance counts has been added, such that noroBE() can now extract data from the time range 2011-w01 to 2016-w30.

• noroBE(by = "none") extracts the overall univariate time series.

• update() method for "fitC" objects, which enables modification of the "hhh4" model with automatic refitting of the power parameter of the contact matrix.

• plotHHH4_season_groups() gained an option to disable confidence intervals.

Bug fixes

• A typical drop=FALSE bug prevented aggregateC() from aggregating a contact matrix to only two groups.

hhh4contacts 0.12.1 (2016-07-28)

This is the original version published as supplementary data of

Meyer S and Held L (2017). “Incorporating social contact data in spatio-temporal models for infectious disease spread.” Biostatistics, 18(2), pp. 338-351, doi: 10.1093/biostatistics/kxw051.