Hospital Census Forecasts from Hubverse Admission Forecasts • censcast

Hospital census forecasts from hubverse admission forecasts.

censcast convolves hubverse format admission quantile forecasts with a length of stay (LOS) distribution to produce hubverse format census quantile forecasts. Same schema in, same schema out.

census(t) = Σ_{d ≥ 0} admissions(t − d) · P(LOS > d)

where d is the lag in time steps since admission, and P(LOS > d) is the probability a patient is still in hospital d steps after they arrived.

Example

library(censcast)

los <- spec_los("negbin", mu = 2, k = 1.7, max_stay = 8)
census_fcast <- fcast_census(admission_forecast, los, admission_history)

plot_fan(census_fcast)

admission_forecast and admission_history are toy datasets shipped with the package. In real use, swap them for outputs from hubData::connect_hub() and hubData::connect_target_timeseries(). See the vignette.

API

Function	Role
`spec_los()`	LOS survival vector from literature priors.
`fit_los()`	Fit LOS survival from observed `(admissions, census)`.
`fcast_census()`	Convolve hubverse admissions × LOS → hubverse census.
`plot_fan()`	Quantile fan chart, returns a `ggplot`.
`score_census()`	Optional WIS via `scoringutils`.