baselinenowcast (version 0.2.0)

apply_delay: Apply the delay to generate a point nowcast

Description

Generate a point estimate of a completed reporting square (or rectangle) from a reporting triangle that we want to complete with a nowcast and a delay PMF. Each element is computed by taking the product of the expected number of total cases assigned to a reference time $t$ and the proportion of those cases reported on delay $d$. The formula to obtain the expected number of total cases as a function of the reporting delay and previous observations was derived elsewhere. This code was adapted from code written (under an MIT license) by the Karlsruhe Institute of Technology RESPINOW German Hospitalization Nowcasting Hub. Modified from: https://github.com/KITmetricslab/RESPINOW-Hub/blob/7cce3ae2728116e8c8cc0e4ab29074462c24650e/code/baseline/functions.R#L55 #nolint

Usage

apply_delay(reporting_triangle, delay_pmf, validate = TRUE)

Value

point_nowcast_matrix Matrix of the same number of rows and columns as the rep_mat_to_nowcast but with the missing values filled in as point estimates

Arguments

reporting_triangle

Matrix of the reporting triangle to be nowcasted, with rows representing the time points of reference and columns representing the delays

delay_pmf

Vector of delays assumed to be indexed starting at the first delay column in reporting_triangle.

validate

Logical. If TRUE (default), validates the object. Set to FALSE only when called from functions that already validated.

Examples

# Example 1: Standard usage with example dataset
delay_pmf <- estimate_delay(example_reporting_triangle)
point_nowcast_matrix <- apply_delay(
  reporting_triangle = example_reporting_triangle,
  delay_pmf = delay_pmf
)
print(point_nowcast_matrix)

# Example 2: Using delay PMF with negative entries from downward corrections
delay_pmf_negative <- c(0.7, 0.4, -0.15, 0.05)
nowcast_with_corrections <- apply_delay(
  reporting_triangle = example_downward_corr_rt,
  delay_pmf = delay_pmf_negative
)
# The nowcast includes negative predictions at delay 2,
# correctly reflecting expected downward corrections
print(nowcast_with_corrections)