Build model inputs from a line list — prepare_cfr

Classifies each case at an observation cut-off into an observed death (with an interval-censored onset-to-death delay), a resolved non-death, or a right-censored survivor still unresolved at the cut-off, and returns the pieces fit_cfr() passes to Stan. A case counts as resolved non-death if it has a recovery_date on or before the cut-off (or, in a retrospective fit, if it simply never died); such a case contributes the cure term rather than being censored, so recording recoveries tightens the estimate.

Usage

prepare_cfr_data(
  linelist,
  obs_time = NULL,
  covariates = character(),
  t0 = NULL,
  max_delay = 60
)

Arguments

linelist: A data frame with an onset_date column, an optional onset_lower/onset_upper onset window, a death_date column (NA for cases that have not died; use the date the death was notified, i.e. when it entered the data, so real-time censoring absorbs any reporting lag), and an optional recovery_date column (NA unless the case is a recorded non-fatal recovery). Dates may be Date or coercible.
obs_time: Real-time cut-off (Date or coercible), or NULL for a retrospective fit in which every recorded death counts and survivors are treated as fully resolved. In real time, a case with a recovery on or before obs_time is resolved; one still alive and unresolved is right-censored; and a death dated after obs_time is treated as not-yet-known (right-censored).
covariates: Character vector of linelist column names to carry through to the per-case model rows, so they can be used in a cfr ~ ... formula. The onset date is always carried as onset; for a time-varying CFR derive a time term from it (e.g. week) and pass cfr ~ s(week).
t0: Optional time origin (Date). Defaults to min(onset) - max_delay.
max_delay: Plausibility filter for data-entry errors, in days: a death record implying a negative onset-to-death delay, or one longer than max_delay, is dropped as a likely mis-keyed date. This only screens records; it does not bound or truncate the onset-to-death delay the model fits, so set it comfortably above the longest credible delay to avoid discarding genuine long-delay deaths (which would bias the delay short). It also sets the default origin, t0 = min(onset) - max_delay.

Value

A cfrnow_data list with the aggregated model inputs (n_death, death_delay, death_width, n_recovery, recovery_delay, recovery_width, n_cens, censor_time, censor_width, n_resolved, n_cases, n_deaths, n_recoveries, t0, obs_time) and a cases data frame with one row per kept case (y, outcome, pwindow, swindow, onset and any requested covariates), which as_epidist_cure_model() turns into the model frame.

Details

Onset is taken over the day-window [onset_lower, onset_upper] when those columns are present (defaulting to a one-day window at onset_date). Deaths and recoveries are recorded to the day.

Records that cannot be used are dropped with a warning: a missing onset, an inverted onset window (onset_upper < onset_lower), a death with an impossible onset-to-death delay (negative, or longer than max_delay), or a recovery dated before onset. In real time, cases whose onset falls after obs_time are not yet known and are excluded with a message.

Examples

ll <- simulate_linelist(n = 50, delay = LogNormal(2.4, 0.5))
prepare_cfr_data(ll, obs_time = as.Date("2026-02-01"))
#> 21 case(s) with onset after the cut-off excluded
#> $n_death
#> [1] 8
#> 
#> $death_delay
#> [1] 14 19 11 14 26  9  8  5
#> 
#> $death_width
#> [1] 1 1 1 1 1 1 1 1
#> 
#> $n_recovery
#> [1] 0
#> 
#> $recovery_delay
#> integer(0)
#> 
#> $recovery_width
#> numeric(0)
#> 
#> $n_cens
#> [1] 21
#> 
#> $censor_time
#>  [1] 10 21  2 29 24  9 28  8 11 26  1 27 24 11 23  1 16 11  2 32 27
#> 
#> $censor_width
#>  [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 
#> $n_resolved
#> [1] 0
#> 
#> $n_cases
#> [1] 29
#> 
#> $n_deaths
#> [1] 8
#> 
#> $n_recoveries
#> [1] 0
#> 
#> $cases
#>     y outcome pwindow swindow      onset
#> 1  10       0       1       1 2026-01-23
#> 2  21       0       1       1 2026-01-12
#> 3   2       0       1       1 2026-01-31
#> 4  29       0       1       1 2026-01-04
#> 5  24       0       1       1 2026-01-09
#> 6  14       1       1       1 2026-01-05
#> 7  19       1       1       1 2026-01-05
#> 8   9       0       1       1 2026-01-24
#> 9  11       1       1       1 2026-01-15
#> 10 14       1       1       1 2026-01-13
#> 11 26       1       1       1 2026-01-02
#> 12 28       0       1       1 2026-01-05
#> 13  9       1       1       1 2026-01-21
#> 14  8       1       1       1 2026-01-06
#> 15  5       1       1       1 2026-01-04
#> 16  8       0       1       1 2026-01-25
#> 17 11       0       1       1 2026-01-22
#> 18 26       0       1       1 2026-01-07
#> 19  1       0       1       1 2026-02-01
#> 20 27       0       1       1 2026-01-06
#> 21 24       0       1       1 2026-01-09
#> 22 11       0       1       1 2026-01-22
#> 23 23       0       1       1 2026-01-10
#> 24  1       0       1       1 2026-02-01
#> 25 16       0       1       1 2026-01-17
#> 26 11       0       1       1 2026-01-22
#> 27  2       0       1       1 2026-01-31
#> 28 32       0       1       1 2026-01-01
#> 29 27       0       1       1 2026-01-06
#> 
#> $t0
#> [1] "2025-11-02"
#> 
#> $obs_time
#> [1] "2026-02-01"
#> 
#> attr(,"class")
#> [1] "cfrnow_data"