#***************************************************************
# project: LTBI screening
# N Green
# May 2017
#
# calculate outcomes
# - numbers of active TB cases
# - QALYs per person for each outcome (death, avoided, cured)
n.exit_tb <-
IMPUTED_sample_year_cohort %>%
dplyr::filter(exituk_tb) %>%
dplyr::count()
n.uk_tb <-
IMPUTED_sample_year_cohort %>%
dplyr::filter(uk_tb) %>%
dplyr::count()
num_all_tb_cost <-
if (interv$ENDPOINT_cost == "exit uk") {
n.uk_tb
} else if (interv$ENDPOINT_cost == "death") {
n.uk_tb + n.exit_tb}
num_all_tb_QALY <-
if (interv$ENDPOINT_QALY == "exit uk") {
n.uk_tb
} else if (interv$ENDPOINT_QALY == "death") {
n.uk_tb + n.exit_tb}
# E_fatalities <- with(IMPUTED_sample_year_cohort,
# cfr[!is.na(cfr)])
#
# E_total_fatalities <- sum(E_fatalities)
#
# E_fatality_QALYloss <- IMPUTED_sample_year_cohort$QALY_diseasefree * E_fatalities
#
# E_total_fatality_QALYloss <- sum(E_fatality_QALYloss, na.rm = TRUE)
# adjusted_life_years type object equivalent calc
# useful for plotting...
##TODO: may need to pmax(0, .) in all_death_notif definition...
#
# QALY_diseasefree <- list()
#
# QALY_diseasefree <-
# IMPUTED_sample_year_cohort %>%
# subset(all_tb == TRUE) %$%
# map2(.x = age_all_notification,
# .y = all_death_notif,
# .f = QALY::adjusted_life_years,
# start_year = 0,
# end_year = NA,
# utility = utility$disease_free,
# discount_rate = 0.035) %>%
# map(QALY::total_QALYs)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.