scripts/create--single_migrant_cohort_Excel_test_cases.R
In n8thangreen/LTBIscreeningproject: LTBI screening cost-effectiveness analysis
# create--single_migrant_cohort_Excel_test_cases.R
# matched with model runs in
# C:\Users\ngreen1\Google Drive\LTBI-screening-cost-effectiveness\spreadsheet model
# scenario 1 --------------------------------------------------------------
# tb in EWNI
# have LTBI, complete treatment, case averted
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 2 --------------------------------------------------------------
# remain EWNI
# No LTBI, but tested, no treatment
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 0 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 3 --------------------------------------------------------------
# remain EWNI
# LTBI, no case averted, but complete treatment
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 1 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 4 --------------------------------------------------------------
# tb exit EWNI
# LTBI, case averted, complete treatment, exit
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = "0" ,
all_tb = "1" ,
LTBI = 1 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2011-01-01" ,
date_exit_uk1_issdt = 2 ,
notif_issdt.years = NA ,
all_tb_issdt = 3 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 5 --------------------------------------------------------------
# no LTBI - exit EWNI
# LTBI, no case averted, complete treatment, exit
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 1 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2011-01-01" ,
date_exit_uk1_issdt = 2 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 6 --------------------------------------------------------------
# No LTBI, but false positive, so complete treatment, no exit
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 0 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 7 --------------------------------------------------------------
# LTBI, progress to TB 100%, don't complete treatment, EWNI
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 8 --------------------------------------------------------------
# LTBI, progress to TB 100%, don't complete treatment, EWNI
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
exituk_tb = 0 ,
all_tb = 0 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 9 --------------------------------------------------------------
# LTBI, progression risk 100%, doesn't accept testing
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 10 --------------------------------------------------------------
# LTBI, progression 100%, accepts testing, doesn't start treatment
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 11 --------------------------------------------------------------
# no LTBI, screened, treated, exit
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 0 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2011-01-01" ,
date_exit_uk1_issdt = 2 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
n8thangreen/LTBIscreeningproject documentation built on May 23, 2019, 12:01 p.m.
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# create--single_migrant_cohort_Excel_test_cases.R
# matched with model runs in
# C:\Users\ngreen1\Google Drive\LTBI-screening-cost-effectiveness\spreadsheet model
# scenario 1 --------------------------------------------------------------
# tb in EWNI
# have LTBI, complete treatment, case averted
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 2 --------------------------------------------------------------
# remain EWNI
# No LTBI, but tested, no treatment
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 0 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 3 --------------------------------------------------------------
# remain EWNI
# LTBI, no case averted, but complete treatment
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 1 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 4 --------------------------------------------------------------
# tb exit EWNI
# LTBI, case averted, complete treatment, exit
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = "0" ,
all_tb = "1" ,
LTBI = 1 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2011-01-01" ,
date_exit_uk1_issdt = 2 ,
notif_issdt.years = NA ,
all_tb_issdt = 3 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 5 --------------------------------------------------------------
# no LTBI - exit EWNI
# LTBI, no case averted, complete treatment, exit
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 1 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2011-01-01" ,
date_exit_uk1_issdt = 2 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 6 --------------------------------------------------------------
# No LTBI, but false positive, so complete treatment, no exit
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 0 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
# scenario 7 --------------------------------------------------------------
# LTBI, progress to TB 100%, don't complete treatment, EWNI
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 8 --------------------------------------------------------------
# LTBI, progress to TB 100%, don't complete treatment, EWNI
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
exituk_tb = 0 ,
all_tb = 0 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 9 --------------------------------------------------------------
# LTBI, progression risk 100%, doesn't accept testing
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 10 --------------------------------------------------------------
# LTBI, progression 100%, accepts testing, doesn't start treatment
cohort <-
data.frame(
age_at_entry = "18" ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 1 ,
exituk_tb = 0 ,
all_tb = 1 ,
LTBI = "1" ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2050-01-01" ,
date_exit_uk1_issdt = 41 ,
notif_issdt.years = 2 ,
all_tb_issdt = 2 ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = 1 ,
num_2nd_inf = 0
)
# scenario 11 --------------------------------------------------------------
# no LTBI, screened, treated, exit
cohort <-
data.frame(
age_at_entry = 18 ,
who_inc_Pareek2011 = "(150,250]" ,
issdt = "2009-01-01" ,
uk_tb = 0 ,
all_tb = 0 ,
LTBI = 0 ,
screen_year = 1 ,
date_death1 = "2040-01-01" ,
date_death1_issdt = 31 ,
date_exit_uk1 = "2011-01-01" ,
date_exit_uk1_issdt = 2 ,
notif_issdt.years = NA ,
all_tb_issdt = NA ,
cfr = 0 ,
tb_fatality = NA ,
QALY_statusquo = 11 ,
QALY_diseasefree = 13 ,
QALY_cured = 1 ,
QALY_fatality = 0 ,
uk_notif_discounts = 1 ,
all_notif_discounts = 1 ,
uk_secondary_inf_discounts = 1 ,
all_secondary_inf_discounts = 1 ,
id_avoided_tb = NA ,
num_2nd_inf = 0
)
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