covid_simr: Covid-19 ICU bed-occupancy simulation

In nhs-bnssg-analytics/covid-simr: easy-to-use function for modelling the effect of different mitigating scenarios on projected capacity-dependent covid19 deaths

Description

Covid-19 ICU bed-occupancy simulation

Usage

covid_simr(cases, los_median, los_95, cap, pfat, tol = 25, nreps = 100)

Arguments

cases	data.frame, hosptialisation data, one column named date (string), and one column named hospitalisations which is an integer recording new cases for that date.
los_median	positive numeric, median length of stay (in days) for admitted covid19 pateints, to be estimated by user from data or other source
los_95	positive numeric, 0.95 quantile length of stay (in days) for admitted covid19 patients, to be estimated by user from data or other source
cap	positive integer, maximum number of patients who can be concurrently admitted to the hospital/unit
pfat	numeric in range 0 (no chance of death) to 1 (certain death), probability that a patient who arrives but is rejected/cannot be admitted (because there are no beds free) dies
tol	numeric between 0 and 100, with 0 corresponding to full confidence inputs are correct, with 100 least level of confidence, subjective assessment of reliability of input hospitalisation estiamtes
nreps	positive integer, number of simulation replications to perform - larger number means better results, but longer time to compute

Value

An object of type Covidsimr, which is a list including the slots:

• data, Output results from simulation

• data_cum, Output results from simulation, in cumulative form

• tol, TRUE/FALSE based on whether a tolerance has been set in the function inputs

• cap, Maximum ICU capactiy

Of most interest to users are data and data_cum, the other elements are included for use in the plotting functions.

nhs-bnssg-analytics/covid-simr documentation built on May 12, 2020, 4:55 p.m.