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How much of each day has been resolved

Source: R/revision.R
plot_revision_status.Rd

[Stable]

The share of each event date's cases that are confirmed, retracted or still pending, as of the object's now.

This is the picture of the resolution front. The oldest dates are almost entirely resolved; the most recent ones are mostly pending, because the laboratory has not caught up yet. Where that front sits tells you how far back the confirmed counts can be trusted – and a day that is 80% pending is a day whose confirmed count means very little.

Usage

plot_revision_status(
  x,
  by = NULL,
  proportion = TRUE,
  palette = .tbl_now_palette()
)

Arguments

x

A tbl_now with a revision process.

by

Optional stratum column to facet by.

proportion

When TRUE (default) the bands are shares summing to 1; FALSE shows the counts instead, which keeps the epidemic curve visible.

palette

A named colour palette (see tbl_now_palette()). The plot is drawn entirely with stacked areas, so it takes no size or linewidth.

Value

A ggplot.

Reading it

The pending band widening towards the right is normal and expected – it is the same right-truncation a nowcast exists to correct, one axis over. What is not normal is a pending band that stays wide far from the now: those cases were reported and then never resolved, and they will never be. Consider censor_revision_delays_above().

A retracted share that changes over time is worth investigating: it usually means the testing criteria or the case definition changed, not that the disease did.

Colours

confirmed is drawn with the palette's epidemic role (it is a real case – the epidemic process), retracted with reporting (it was removed by the reporting process), and pending with the neutral pending role (not yet known either way). Override any of them through palette.

See also

diagnose_revision_delay(), revised_cases.

Examples

cases <- data.frame(
  onset = as.Date("2021-01-04") + rep(0:9, each = 4),
  visit = as.Date("2021-01-05") + rep(0:9, each = 4),
  result = as.Date("2021-01-07") + rep(0:9, each = 4),
  outcome = rep(c("confirmed", "confirmed", "retracted", "pending"), times = 10)
)
cases$result[cases$outcome == "pending"] <- as.Date(NA)
flu <- tbl_now(cases,
  event_date = onset, report_date = visit,
  revision_date = result, revision_type = outcome,
  data_type = "linelist", verbose = FALSE
)

plot_revision_status(flu)