Impute Cases Date of Infection

nowcast_pipeline(
  reported_cases = NULL,
  linelist = NULL,
  target_date = NULL,
  earliest_allowed_onset = NULL,
  merge_actual_onsets = FALSE,
  approx_delay = FALSE,
  max_delay = 120,
  verbose = FALSE,
  delay_defs = NULL,
  incubation_defs = NULL,
  nowcast_lag = 8,
  max_upscale = 5,
  onset_modifier = NULL
)

Arguments

reported_cases	A dataframe of reported cases
linelist	A linelist of report dates and onset dates
target_date	Character string, in the form "2020-01-01". Date to cast.
earliest_allowed_onset	A character string in the form of a date ("2020-01-01") indiciating the earliest allowed onset.
merge_actual_onsets	Logical, defaults to `TRUE`. Should linelist onset dates be used where available?
approx_delay	Logical, defaults to `FALSE`. Should delay sampling be approximated using case counts. Not appropriate when case numbers are low. Useful for high cases counts as decouples run time and resource usage from case count.
max_delay	Numeric, maximum delay to allow. Defaults to 120 days
verbose	Logical, defaults to `FALSE`. Should internal nowcasting progress messages be returned.
delay_defs	A data.table that defines the delay distributions (model, parameters and maximum delay for each model). See `get_delay_dist` for an example of the structure.
incubation_defs	A data.table that defines the incubation distributions (model, parameters and maximum delay for each model). See `get_delay_dist` for an example of the structure.
nowcast_lag	Numeric, defaults to 4. The number of days by which to lag nowcasts. Helps reduce bias due to case upscaling.
max_upscale	Numeric, maximum upscaling of cases allowed at each time point. Defaults to 100 times the observed cases.
onset_modifier	data.frame containing a `date` variable and a function `modifier` variable. This is used to modify estimated cases by onset date. `modifier` must be a function that returns a proportion when called (enables inclusion of uncertainty) and takes the following arguments: `n` (samples to return) and `status` ("local" or "import").

Value

A dataframe of nowcast cases from each step of the nowcasting process (defined by type).

Examples

## Construct example distributions
## reporting delay dist
delay_dist <- suppressWarnings(
               EpiNow::get_dist_def(rexp(25, 1 / 10), 
                                    samples = 1, bootstraps = 1))
## incubation delay dist
incubation_dist <- delay_dist

## Uses example case vector from EpiSoon
cases <- data.table::setDT(EpiSoon::example_obs_cases)
cases <- cases[, `:=`(confirm = as.integer(cases), import_status = "local")]

## Basic nowcast
nowcast <- nowcast_pipeline(reported_cases = cases, 
                            target_date = max(cases$date),
                            delay_defs = delay_dist,
                            incubation_defs = incubation_dist)
                            
nowcast
#>      sample       date cases               type import_status confidence
#>   1:      1 2020-01-15     1              onset         local  1.0000000
#>   2:      1 2020-01-16     0              onset         local  1.0000000
#>   3:      1 2020-01-17     1              onset         local  1.0000000
#>   4:      1 2020-01-18     0              onset         local  1.0000000
#>   5:      1 2020-01-19     2              onset         local  1.0000000
#>  ---                                                                    
#> 254:      1 2020-03-10   332 infection_upscaled         local  0.6480296
#> 255:      1 2020-03-11   293 infection_upscaled         local  0.5988762
#> 256:      1 2020-03-12   328 infection_upscaled         local  0.5466796
#> 257:      1 2020-03-13   367 infection_upscaled         local  0.4916264
#> 258:      1 2020-03-14   318 infection_upscaled         local  0.4340406