NEWS.md

EpiEstim 2.5

• Implemented back-imputation procedure described in (Brizzi, O'Driscoll and Dorigatti)[https://doi.org/10.1093/cid/ciac138]. This is implemented through the new functions backimpute_I(), which takes a vector representing incidence and estimates the number of unobserved infections prior to the first reported case.
• estimate_R now accepts the backimputation_window parameter, which determines the number of observations used to backimpute unobserved cases. If this is set to 0 no backimputation will be performed. 0 is the default value guaranteeing compatibility with previous versions of the package.
• added vignette vignettes/EpiEstim_backimputation.Rmd and tests/testthat/test-backimpute.R.

EpiEstim 2.4

• estimate_R can now be applied to coarsely (non-daily) aggregated incidence data

MISC

• lintr is now part of EpiEstim continuous integration toolkit, alongside R CMD check. This should detect and eliminate suboptimal code pattern and potential bugs before they even make it to master (#159, @Bisaloo).

EpiEstim 2.3

• new function estimate_joint to estimate the transmission advantage of a strain or variant

EpiEstim 2.2-5

• New vignette

EpiEstim 2.2-3

• This release is also available at https://zenodo.org/record/3871387 which is the source of the DOI for this codebase; for v2.2-3 that is doi:10.5281/zenodo.3871387. Also added as a link to the top-right of the landing page. Don't forget to update in the next release!

FIXED

• Fixed bugs in draw_one_set_of_ancestries resulting from incorrect lengths and an undefined variable (issue #92) (#93, @jstockwin)
• Fixed incorrect quantiles (issue #88) (#89, @jstockwin)

EpiEstim 2.2-2

MISC

• Plotting no longer displays TableGrob output (#87, @zkamvar).

EpiEstim 2.2-1

This release contains various spelling fixes for CRAN maintenance.

EpiEstim 2.2-0

NEW FUNCTIONS

• sample_posterior_R() samples values of R from the posterior distribution of an estimate_R object (#70, @acori)

MISC

• Added a NEWS.md file to track changes to the package. (#74, @zkamvar)
• Added tests for plotting with vdiffr. (#74, @zkamvar)
• Remove un-used dependencies that were added during hackout3: plyr, grid, and plotly (#74, @zkamvar)
• Remove compare package from suggests and use test_that version. (#74, @zkamvar)
• Bump minimum required version of coarseDataTools to 0.6-4 (#71, @zkamvar)
• Incidence objects are now handled appropriately with accessors (#65, @zkamvar)

EpiEstim 2.1-0

• Changed function names to snake_case (only exception is that R remains capital letter to avoid confusion between the reproduction number R and the growth rate r) and to be more explicit; so EstimateR becomes estimate_R, OverallInfectivity becomes oberall_infectivity, WT becomes wallinga_teunis, and DiscrSI becomes discr_si. Names of arguments to these functions have also changed to snake_case. Note that compatibility functions have been added so that the old functions as written in EpiEstim 1.1-0 should still work but throw a warning pointing to the newest functions.
• Compatibility with incidence package: in the function estimate_R, the first argument, i.e. the incidence from which the reproduction number is calculated, can now be, either a vector of case counts (as in version 1.1-0) or an incidence object (see R package incidence).
• Accounting for imported cases: in the function estimate_R, the first argument, i.e. the incidence from which the reproduction number can now provide information about known imported cases: by specifying the first argument as either a dataframe with columns "local" and "imported", or an incidence object with two groups (local and imported, see R package incidence). This new feature is described in Thompson et al. Epidemics 2019 (currently in review).
• Additional methods available for function estimate_R: in addition to non_parametric_si, parametric_si and uncertain_si, which were already available in EpiEstim 1.1-0, two new methods have been added: si_from_data or si_from_sample. These allow feeding function estimate_R data on observed serial intervals (method si_from_data) or posterior samples of serial interval distributions obtained from such data (method si_from_sample). These new features are described in Thompson et al. Epidemics 2019 (currently in review).
• No more plotting option inside of estimate_R: estimate_R now generates on object of class estimate_R, which can be plotted separately by using the new estimate_R_plots function, which also now allows to plot several R estimates on a single plot.
• New argument config for estimate_R function: this is meant to minimise the number of arguments to function estimate_R; so arguments method, t_start, t_end, n1, n2, mean_si, std_si, std_mean_si, min_mean_si, max_mean_si, std_std_si, min_std_si, max_std_si, si_distr, mean_prior, std_prior, and cv_posterior are now specified as a group under this new config argument. Such a config argument must be of class estimate_R_config and can be obtained as a results of the new make_config function.
• New function make_config, which defines settings for function estimate_R, and sets defaults where arguments are missing. In particular, if argument incid is not NULL, by default config$t_start and config$t_end will be set so that, when the configuration is used inside estimate_R function, the reproduction number is estimated by default on sliding weekly windows (in EpiEstim 1.1-0 there was no default for the time window of estimation of R).
• Added a vignette to illustrate main features of the package.

NEW DATASETS:

• flu_2009_NYC_school
• mers_2014_15,
• MockRotavirus

NEW IMPORTS

• stats (to use the gamma distribution; it was already used in EpiEstim 1.1-0 but making the dependency explicit)
• coarseDataTools, fitdistrplus, coda (used for the new methods si_from_data and si_from_sample in estimate_R function to estimate the serial interval from data).
• incidence (so that estimate_R can take an incidence object as first argument)
• graphics, reshape2, ggplot2, gridExtra, scales, grDevices (to make new plots of outputs of estimate_R and wallinga_teunis functions)