Convert a Line List to Aggregate Counts (Incidence)

This function takes a line list (i.e. tabular data where each row represents a case) and aggregates to a count (new_confirm) of cases by user-specified reference_dates and report_dates. This is enables the use of enw_preprocess_data() and other epinowcast() preprocessing functions.

Usage

enw_linelist_to_incidence(
  linelist,
  reference_date = "reference_date",
  report_date = "report_date",
  by = NULL,
  max_delay,
  completion_beyond_max_report = FALSE,
  copy = TRUE
)

Arguments

linelist

An object coercible to a data.table (such as a data.frame) where each row represents a case. Must contain at least two date variables or variables that can be coerced to dates.

reference_date

A date or a variable that can be coerced to a date that represents the date of interest for the case. For example, if the reference_date is the date of symptom onset then the new_confirm will be the number of new cases reported (based on report_date) on each day that had onset on that day. The default is "reference_date".

report_date

A date or a variable that can be coerced to a date that represents the date the case was reported. The default is "report_date".

by

A character vector of variables to also aggregate by (i.e. as well as using the reference_date and report_date). If not supplied then the function will aggregate by just the reference_date and report_date.

max_delay

The maximum delay (in days) between the reference_date and the report_date. If not supplied then the function will use the maximum observed delay. Note that this function operates before timestep conversion, so max_delay is always in days here. If the max_delay is less than the maximum number of days between the reference_date and the report_date in the linelist then the function will use this value instead and inform the user.

completion_beyond_max_report

Logical, should entries be completed beyond the maximum date found in the data? Default: FALSE

copy

Should obs be copied (default) or modified in place?

Value

A data.table with the following variables: reference_date, report_date, new_confirm, confirm, delay, and any variables specified in by.

See also

Data converters enw_add_cumulative(), enw_add_incidence(), enw_aggregate_cumulative(), enw_incidence_to_linelist()

Examples

linelist <- data.frame(
  onset_date = as.Date(c("2021-01-02", "2021-01-03", "2021-01-02")),
  report_date = as.Date(c("2021-01-03", "2021-01-05", "2021-01-04"))
)
enw_linelist_to_incidence(linelist, reference_date = "onset_date")
#> Using the maximum observed delay of 4 days to complete the incidence data.
#> Key: <reference_date, report_date>
#>     report_date reference_date new_confirm confirm delay
#>          <IDat>         <IDat>       <int>   <int> <int>
#>  1:  2021-01-02           <NA>           0       0     0
#>  2:  2021-01-03           <NA>           0       0     1
#>  3:  2021-01-04           <NA>           0       0     2
#>  4:  2021-01-05           <NA>           0       0     3
#>  5:  2021-01-02     2021-01-02           0       0     0
#>  6:  2021-01-03     2021-01-02           1       1     1
#>  7:  2021-01-04     2021-01-02           1       2     2
#>  8:  2021-01-05     2021-01-02           0       2     3
#>  9:  2021-01-03     2021-01-03           0       0     0
#> 10:  2021-01-04     2021-01-03           0       0     1
#> 11:  2021-01-05     2021-01-03           1       1     2
#> 12:  2021-01-04     2021-01-04           0       0     0
#> 13:  2021-01-05     2021-01-04           0       0     1
#> 14:  2021-01-05     2021-01-05           0       0     0

# Specify a custom maximum delay and allow completion beyond the maximum
# observed delay
enw_linelist_to_incidence(
 linelist, reference_date = "onset_date", max_delay = 5,
 completion_beyond_max_report = TRUE
)
#> Key: <reference_date, report_date>
#>     report_date reference_date new_confirm confirm delay
#>          <IDat>         <IDat>       <int>   <int> <int>
#>  1:  2021-01-02           <NA>           0       0     0
#>  2:  2021-01-03           <NA>           0       0     1
#>  3:  2021-01-04           <NA>           0       0     2
#>  4:  2021-01-05           <NA>           0       0     3
#>  5:  2021-01-02     2021-01-02           0       0     0
#>  6:  2021-01-03     2021-01-02           1       1     1
#>  7:  2021-01-04     2021-01-02           1       2     2
#>  8:  2021-01-05     2021-01-02           0       2     3
#>  9:  2021-01-06     2021-01-02           0       2     4
#> 10:  2021-01-07     2021-01-02           0       2     5
#> 11:  2021-01-03     2021-01-03           0       0     0
#> 12:  2021-01-04     2021-01-03           0       0     1
#> 13:  2021-01-05     2021-01-03           1       1     2
#> 14:  2021-01-06     2021-01-03           0       1     3
#> 15:  2021-01-07     2021-01-03           0       1     4
#> 16:  2021-01-08     2021-01-03           0       1     5
#> 17:  2021-01-04     2021-01-04           0       0     0
#> 18:  2021-01-05     2021-01-04           0       0     1
#> 19:  2021-01-06     2021-01-04           0       0     2
#> 20:  2021-01-07     2021-01-04           0       0     3
#> 21:  2021-01-08     2021-01-04           0       0     4
#> 22:  2021-01-09     2021-01-04           0       0     5
#> 23:  2021-01-05     2021-01-05           0       0     0
#> 24:  2021-01-06     2021-01-05           0       0     1
#> 25:  2021-01-07     2021-01-05           0       0     2
#> 26:  2021-01-08     2021-01-05           0       0     3
#> 27:  2021-01-09     2021-01-05           0       0     4
#> 28:  2021-01-10     2021-01-05           0       0     5
#>     report_date reference_date new_confirm confirm delay