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How much of each day has been resolved

plot_validation_status.Rd

[Experimental]

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_validation_status(x, by = NULL, proportion = TRUE)

Arguments

x

A tbl_now with a validation 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.

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_validation_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 in the palette's green (it is a real case – the epidemic process), retracted in the accent red (it was removed by the reporting process), and pending in grey (not yet known either way).

See also

diagnose_validation_delay(), validated_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,
  validation_date = result, validation_type = outcome,
  data_type = "linelist", verbose = FALSE
)

plot_validation_status(flu)