simulate_incidence_stats {prevtoinc}

Calculate theoretical values like x.los, x.loi and other characteristics of the patient population

Description

Calculate theoretical values like x.los, x.loi and other characteristics of the patient population

Usage

simulate_incidence_stats(hospital, steps = 365 * 10000,
  n.sim.pat = 5000)

Arguments

hospital

type of hospital as a list-object (see vignette for details)

steps

number of steps to evolve process

n.sim.pat

size of simulations to estimate individual characteristics of patients

Value

list with following components

• x.los - average length of stay x_los

• x.loi - average length of infection x_loi

• x.los.noso.only - average length of stay for patients with HAI

• x.los.wo.noso - average length of stay for patients discounting time with HAI

• I - theoretical incidence rate per patient day

• I.pp - list of theoretical incidences for patient types

• patient.stats - list with 'x.los' and 'x.loi' for different patient types

• patient.risk.times - list of patient days at risk for different patient types

Examples

pat.1 <- list(dist.X.los = create_dist_vec(
                               function(x) dpois(x-1, lambda = 12), 70),
I.p = 0.008,
dist.X.loi = create_dist_vec(function(x) dpois(x-1, lambda = 10), 70))

pat.2 <- list(dist.X.los = 
                create_dist_vec(function(x) dpois(x-1, lambda = 10), 70),
              I.p = 0.02,
              dist.X.loi = 
                create_dist_vec(function(x) dpois(x-1, lambda = 7), 70))

patient.list <- list(pat.1, pat.2)


# define distribution of patients
pat.1.prob <- 0.4; pat.2.prob <- 0.6
pat.dist.hosp <- c(pat.1.prob, pat.2.prob)
hospital.1 <- list(inc.factor = 1,
                   pat.dist = pat.dist.hosp,
                   patient.list = patient.list)
data.pps <- simulate_pps_data(n.sample=1000, steps=200, hospital=hospital.1) 
data.inc.theo <- simulate_incidence_stats(hospital.1, 365 * 1000)
# gives incidence rate I
data.inc.theo$I
# gives incidence proportion per admission
data.inc.theo$I.pp