Build an ensemble from a reporting triangle with no nowcast

Returns the counts reported so far as an ensemble with one draw. Use it for an indicator that SHOULD NOT be nowcast, and the rest of the pipeline runs unchanged.

Usage

nowcast_passthrough_to_ensemble_v1(x, max_delay_days, denominator_col = NULL)

Arguments

x

The csfmt_reporting_triangle_v3 to pass through.

max_delay_days

The delay horizon in days. The totals do not depend on it, because a report at delay max_delay_days or later is in the total too.

denominator_col

A denominator column to pass through in the same way. Its total also goes to $data as <denominator_col>_observed.

Value

A csfmt_ensemble_v3 with one draw. $data holds original, the observed total, which includes the reports at delay max_delay_days or later.

Details

The draw matrix has the name <measure>_nowcasted, as from nowcast_delay_ecdf_v1(), and holds the observed total. So every collapsed quantile equals the observed total, also for the newest weeks.

See also

vignette("pipeline", package = "csalert"), stage 2, which scores it against nowcast_delay_ecdf_v1().

Other nowcast engines: nowcast_delay_ecdf_v1()

Examples

# 40 reference weeks, each reported 3, 10 and 17 days after its Monday. The
# data stops at one as-of date, so the newest weeks are still incomplete.
monday <- as.Date("2023-01-02") + 7 * rep(0:39, each = 3)
set.seed(1)
d <- data.table::data.table(
  isoyearweek_reference = format(monday, "%G-%V"),
  reporting_date = monday + rep(c(3, 10, 17), 40),
  numerator = rpois(120, c(30, 15, 5)),
  indicator_tag = "x", location_code = "nation", age = "total", sex = "total"
)
d <- d[reporting_date <= as.Date("2023-01-02") + 7 * 39 + 6]
tri <- csfmt_reporting_triangle_v3(
  d,
  id_cols = c("indicator_tag", "location_code", "age", "sex")
)

ens <- nowcast_passthrough_to_ensemble_v1(tri, max_delay_days = 21)
ens
#> <csfmt_ensemble_v3> 40 rows | 1 series | draws: numerator_nowcasted

# one draw, so every quantile equals the observed total, also for the
# newest weeks that are still incomplete
r <- ens_collapse(ens, probs = c(0.05, 0.5, 0.95))
tail(r[, .(
  isoyearweek, original,
  lo = numerator_nowcasted_q05x0,
  med = numerator_nowcasted_q50x0,
  hi = numerator_nowcasted_q95x0
)], 3)
#>    isoyearweek original    lo   med    hi
#>         <char>    <num> <num> <num> <num>
#> 1:     2023-38       51    51    51    51
#> 2:     2023-39       44    44    44    44
#> 3:     2023-40       20    20    20    20