#**************************************************************************
# project: LTBI screening
# N Green
# Oct 2016
#
# simulation specific constants
N.mc <- 5#100
cluster <- FALSE
# global fixed constants --------------------------------------------------
use_discount <- FALSE
no_students <- FALSE
force_everyone_stays <- FALSE
# rather than screen _everyone_ on entry
# screen at random 0-5 years from entry
screen_with_delay <- TRUE
MAX_SCREEN_DELAY <- 5
# time horizon for active TB progression
FUP_MAX_YEAR <- 100
screen_age_range <- 18:35
# screen_age_range <- 18:45
# year_cohort <- '2012' #most recent complete year
year_cohort <- '2009' #largest cohort, corresponds with Pareek () LTBI risk
# LIFETIME_RISK <- 0.10
# LIFETIME_RISK <- 0.163 #Choudhury (2013) 15 years
# LIFETIME_RISK <- 0.18 #NICE economic appraisal (2006)
# LIFETIME_RISK <- 0.067 #Marks (2000) 40 years
# these parameters will be modified in the
# deterministic sensitivity analysis
# but set default values
incidence_grps_screen <- c("(0,50]", "(50,150]", "(150,250]", "(250,350]", "(350,1e+05]")
min_screen_length_of_stay <- 0
ENDPOINT_cost <- "death"
ENDPOINT_QALY <- "death" #"exit uk"
interv <-
list(force_everyone_stays = force_everyone_stays,
# ENDPOINT_QALY = ENDPOINT_QALY,
# ENDPOINT_cost = ENDPOINT_cost,
# incidence_grps_screen = incidence_grps_screen,
# min_screen_length_of_stay = min_screen_length_of_stay,
screen_with_delay = screen_with_delay,
FUP_MAX_YEAR = FUP_MAX_YEAR,
screen_age_range = screen_age_range,
year_cohort = year_cohort,
N.mc = N.mc,
cluster = cluster,
no_students = no_students,
discount_rate = ifelse(use_discount, 0.035, 0))
save(interv,
file = "data/intervention_constants.RData")
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