def report_CEA(simOutputs_NONE, simOutputs_ANTICOAG):
""" performs cost-effectiveness analysis
:param simOutputs_mono: output of a cohort simulated under mono therapy
:param simOutputs_combo: output of a cohort simulated under combination therapy
"""
# define two strategies
no_therapy_strategy = Econ.Strategy(
name='Mono Therapy',
cost_obs=simOutputs_NONE.get_costs(),
effect_obs=simOutputs_NONE.get_utilities()
)
anticoag_therapy_strategy = Econ.Strategy(
name='Combination Therapy',
cost_obs=simOutputs_ANTICOAG.get_costs(),
effect_obs=simOutputs_ANTICOAG.get_utilities()
)
# do CEA
if Settings.PSA_ON:
CEA = Econ.CEA(
strategies=[no_therapy_strategy, anticoag_therapy_strategy],
if_paired=True
)
else:
CEA = Econ.CEA(
strategies=[no_therapy_strategy, anticoag_therapy_strategy],
if_paired=False
)
# show the CE plane
CEA.show_CE_plane(
title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=8,
transparency=0.3
)
# report the CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=Settings.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2,
)
def report_CEA():
""" performs cost-effectiveness and cost-benefit analyses
:param simOutputs_mono: output of a cohort simulated under mono therapy
:param simOutputs_combo: output of a cohort simulated under combination therapy
"""
# define two strategies
without_therapy = EconCls.Strategy(
name='Without Therapy',
cost_obs=cohort_ONE.get_total_cost(),
effect_obs=cohort_ONE.get_total_utility())
with_therapy = EconCls.Strategy(name='With Therapy',
cost_obs=cohort_TWO.get_total_cost(),
effect_obs=cohort_TWO.get_total_utility())
# do CEA
CEA = EconCls.CEA(strategies=[without_therapy, with_therapy],
if_paired=False)
# show the CE plane
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3)
# report the CE table
CEA.build_CE_table(
interval=EconCls.Interval.CONFIDENCE,
alpha=0.05,
cost_digits=0,
effect_digits=2,
icer_digits=2,
)
def report_CEA_CBA(simOutputs_US, simOutputs_CT):
# strategies
strategy_US = Econ.Strategy(name='Ultrasound',
cost_obs=simOutputs_US.get_costs(),
effect_obs=simOutputs_US.get_utilities())
strategy_CT = Econ.Strategy(name='Computed Tomography',
cost_obs=simOutputs_CT.get_costs(),
effect_obs=simOutputs_CT.get_utilities())
# CEA
CEA = Econ.CEA(strategies=[strategy_US, strategy_CT], if_paired=False)
# report CE table
CEA.build_CE_table(interval=Econ.Interval.CONFIDENCE,
alpha=Data.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CE plane
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label="Additional Discounted Utility",
y_label='Additional Discounted Cost',
show_names=True,
show_legend=True,
show_clouds=True,
figure_size=6,
transparency=0.3)
def report_CEA_CBA(simOutputs_nodrug, simOutputs_drugtx):
""" performs cost-effectiveness and cost-benefit analysis"""
# strategies
strategy_no_drug = Econ.Strategy(
name='No drug',
cost_obs=simOutputs_nodrug.get_costs(),
effect_obs=simOutputs_nodrug.get_utilities()
)
strategy_drug = Econ.Strategy(
name='Drug Treatment',
cost_obs=simOutputs_drugtx.get_costs(),
effect_obs=simOutputs_drugtx.get_utilities()
)
# CEA
CEA = Econ.CEA(
strategies=[strategy_no_drug, strategy_drug],
if_paired=False
)
# CE plane
CEA.show_CE_plane(
title='Cost Effectiveness Analysis',
x_label='Additional Discounted Utility',
y_label='Additional Discounted Cost',
show_names=True,
show_legend=True,
show_clouds=True,
figure_size=6,
transparency=0.3
)
# report CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=Settings.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2
)
# CBA
NBA = Econ.CBA(
strategies=[strategy_no_drug,strategy_drug],
if_paired=False
)
# net monetary benefit figure
NBA.graph_deltaNMB_lines(
min_wtp=0,
max_wtp=100000,
title='Cost Benefit Analysis',
x_label='WTP for one addn QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval=Econ.Interval.CONFIDENCE,
show_legend=True,
figure_size=6
)
def report_CEA_CBA(simOutputs_none, simOutputs_anticoag):
""" performs cost-effectiveness analysis
:param simOutputs_none: output of a cohort simulated under mono therapy
:param simOutputs_anticoag: output of a cohort simulated under combination therapy
"""
# define two strategies
no_therapy_strategy = Econ.Strategy(
name='No Therapy',
cost_obs=simOutputs_none.get_costs(),
effect_obs=simOutputs_none.get_utilities()
)
anticoag_therapy_strategy = Econ.Strategy(
name='Combination Therapy',
cost_obs=simOutputs_anticoag.get_costs(),
effect_obs=simOutputs_anticoag.get_utilities()
)
# CEA
CEA = Econ.CEA(
strategies=[no_therapy_strategy, anticoag_therapy_strategy],
if_paired=False
)
# show the CE plane
CEA.show_CE_plane(
title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3
)
# report the CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=Settings.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2,
)
# CBA
NBA = Econ.CBA(
strategies=[no_therapy_strategy, anticoag_therapy_strategy],
if_paired=False
)
# show the net monetary benefit figure
NBA.graph_deltaNMB_lines(
min_wtp=0,
max_wtp=50000,
title='Cost-Benefit Analysis',
x_label='Willingness-to-pay for one additional QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval=Econ.Interval.CONFIDENCE,
show_legend=True,
figure_size=6
)
def report_CEA_CBA(simOutputs_standard, simOutputs_population):
""" performs cost-effectiveness analysis
:param simOutputs_standard: output of a cohort simulated under standard testing
:param simOutputs_population: output of a cohort simulated under population testing
"""
# define two strategies
standard_testing_strategy = Econ.Strategy(
name='Standard Testing',
cost_obs=simOutputs_standard.get_costs(),
effect_obs=simOutputs_standard.get_utilities())
population_testing_strategy = Econ.Strategy(
name='Population Testing',
cost_obs=simOutputs_population.get_costs(),
effect_obs=simOutputs_population.get_utilities())
# CEA
CEA = Econ.CEA(
strategies=[standard_testing_strategy, population_testing_strategy],
if_paired=False)
# show the CE plane
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3)
# report the CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=0,
)
# CBA
NBA = Econ.CBA(
strategies=[standard_testing_strategy, population_testing_strategy],
if_paired=False)
# show the net monetary benefit figure
NBA.graph_deltaNMB_lines(
min_wtp=0,
max_wtp=150000,
title='Cost-Benefit Analysis',
x_label='Willingness-to-pay for one additional QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval=Econ.Interval.CONFIDENCE,
show_legend=True,
figure_size=6)
def report_CEA_CBA(simOutputs_warfarin, simOutputs_dabigatran_110,
simOutputs_dabigatran_150):
warfarin_strategy = Econ.Strategy(
name="Warfarin",
cost_obs=simOutputs_warfarin.get_costs(),
effect_obs=simOutputs_warfarin.get_utilities())
dabigatran_110_strategy = Econ.Strategy(
name="Dabigatran 110mg",
cost_obs=simOutputs_dabigatran_110.get_costs(),
effect_obs=simOutputs_dabigatran_110.get_utilities())
dabigatran_150_strategy = Econ.Strategy(
name="Dabigatran 150mg",
cost_obs=simOutputs_dabigatran_150.get_costs(),
effect_obs=simOutputs_dabigatran_150.get_utilities())
listofStrategies = [
warfarin_strategy, dabigatran_110_strategy, dabigatran_150_strategy
]
CEA = Econ.CEA(listofStrategies, if_paired=False)
# create cost effectiveness analysis plane
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3)
# report the CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=Settings.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=3,
)
CBA = Econ.CBA(listofStrategies, if_paired=False)
# Create Cost benefit analysis figure
CBA.graph_deltaNMB_lines(
min_wtp=0,
max_wtp=50000,
x_label="Willingness-to-pay for one additional QALY ($)",
y_label="Incremental Net Monetary Benefit ($)",
interval=Econ.Interval.CONFIDENCE,
transparency=0.4,
show_legend=True,
figure_size=6,
title='Cost Benefit Analysis')
def report_CEA_CBA(simOutputs_none, simOutputs2, simOutputs3, simOutputs4):
no_change = Econ.Strategy(name="No change",
cost_obs=simOutputs_none.get_costs(),
effect_obs=simOutputs_none.get_utilities())
supplies = Econ.Strategy(name="Additional Supplies",
cost_obs=simOutputs2.get_costs(),
effect_obs=simOutputs2.get_utilities())
training = Econ.Strategy(name="Additional Training",
cost_obs=simOutputs3.get_costs(),
effect_obs=simOutputs3.get_utilities())
supplies_and_training = Econ.Strategy(
name="Adding Supplies and Training",
cost_obs=simOutputs4.get_costs(),
effect_obs=simOutputs4.get_utilities())
listofStrategies = [no_change, supplies, training, supplies_and_training]
CEA = Econ.CEA(listofStrategies, if_paired=False)
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3)
# report the CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=Settings.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2,
)
CBA = Econ.CBA(listofStrategies, if_paired=False)
CBA.graph_deltaNMB_lines(
min_wtp=0,
max_wtp=50000,
x_label="Willingness-to-pay for one additional QALY ($)",
y_label="Incremental Net Monetary Benefit ($)",
interval=Econ.Interval.CONFIDENCE,
transparency=0.4,
show_legend=True,
figure_size=6,
title='cost benefit analysis')
def report_CEA_CBA(simOutputs_ANNUAL, simOutputs_SEMI):
annual_MDA = Econ.Strategy(name="Annual MDA",
cost_obs=simOutputs_ANNUAL.get_costs(),
effect_obs=simOutputs_ANNUAL.get_utilities())
semiannual_MDA = Econ.Strategy(name="Semi-Annual MDA",
cost_obs=simOutputs_SEMI.get_costs(),
effect_obs=simOutputs_SEMI.get_utilities())
listofStrategies = [annual_MDA, semiannual_MDA]
CEA = Econ.CEA(listofStrategies, if_paired=False)
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3)
# report the CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=Settings.ALPHA,
cost_digits=2,
effect_digits=2,
icer_digits=2,
)
CBA = Econ.CBA(listofStrategies, if_paired=False)
NBA = Econ.CBA(strategies=[annual_MDA, semiannual_MDA], if_paired=False)
NBA.graph_deltaNMB_lines(
min_wtp=0,
max_wtp=900,
x_label="Willingness-to-pay for one unit reduction in DALY ($)",
y_label="Incremental Net Monetary Benefit ($)",
interval=Econ.Interval.CONFIDENCE,
transparency=0.4,
show_legend=True,
figure_size=6,
title='Cost Benefit Analysis')
def report_CEA_CBA(simOutputs_none, simOutputs_anticoag):
no_therapy_strategy = EconCls.Strategy(
name="without vaccination",
cost_obs=simOutputs_none.get_total_cost(),
effect_obs=simOutputs_none.get_total_utility())
anticoag_therapy_strategy = EconCls.Strategy(
name="With vaccination",
cost_obs=simOutputs_anticoag.get_total_cost(),
effect_obs=simOutputs_anticoag.get_total_utility())
listofStrategies = [no_therapy_strategy, anticoag_therapy_strategy]
CEA = EconCls.CEA(listofStrategies, if_paired=False)
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3)
# report the CE table
CEA.build_CE_table(
interval=EconCls.Interval.CONFIDENCE,
alpha=0.05,
cost_digits=0,
effect_digits=2,
icer_digits=2,
)
CBA = EconCls.CBA(listofStrategies, if_paired=False)
CBA.graph_deltaNMB_lines(
min_wtp=0,
max_wtp=50000,
x_label="Willingness-to-pay for one additional QALY ($)",
y_label="Incremental Net Monetary Benefit ($)",
interval=EconCls.Interval.CONFIDENCE,
transparency=0.4,
show_legend=True,
figure_size=6,
title='cost benefit analysis')
def report_CEA(simOutputs_mono, simOutputs_combo):
""" performs cost-effectiveness analysis
:param simOutputs_mono: output of a cohort simulated under mono therapy
:param simOutputs_combo: output of a cohort simulated under combination therapy
"""
# define two strategies
mono_therapy_strategy = Econ.Strategy(
name='WITHOUT anticoagulation',
cost_obs=simOutputs_mono.get_costs(),
effect_obs=simOutputs_mono.get_utilities()
)
combo_therapy_strategy = Econ.Strategy(
name='WITH anticoagulation',
cost_obs=simOutputs_combo.get_costs(),
effect_obs=simOutputs_combo.get_utilities()
)
# CEA
CEA = Econ.CEA(
strategies=[mono_therapy_strategy, combo_therapy_strategy],
if_paired=False
)
# show the CE plane
CEA.show_CE_plane(
title='Problem 4: Cost-Effectiveness Analysis',
x_label='Additional discounted utility',
y_label='Additional discounted cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3
)
# report the CE table
CEA.build_CE_table(
interval=Econ.Interval.CONFIDENCE,
alpha=ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2,
)
def report_CEA_CBA_single(cohort_no_treat, cohort_acu, cohort_cran, cohort_abx,
cohort_estro):
no_treatment_strategy = Econ.Strategy(
name="No treatment",
cost_obs=cohort_no_treat.get_ave_total_cost(),
effect_obs=cohort_no_treat.get_ave_number_utis())
acu_strategy = Econ.Strategy(name="Acupunture",
cost_obs=cohort_acu.get_ave_total_cost(),
effect_obs=cohort_acu.get_ave_number_utis())
cran_strategy = Econ.Strategy(name="Cranberry",
cost_obs=cohort_cran.get_ave_total_cost(),
effect_obs=cohort_cran.get_ave_number_utis())
abx_strategy = Econ.Strategy(name="Antibiotics",
cost_obs=cohort_abx.get_ave_total_cost(),
effect_obs=cohort_abx.get_ave_number_utis())
estro_strategy = Econ.Strategy(
name="Estrogen",
cost_obs=cohort_estro.get_ave_total_cost(),
effect_obs=cohort_estro.get_ave_number_utis())
CEA = Econ.CEA(strategies=[
no_treatment_strategy, acu_strategy, cran_strategy, abx_strategy,
estro_strategy
],
if_paired=False)
CEA.show_CE_plane(title='Cost-Effectiveness Analysis',
x_label='Difference in total number of UTIs',
y_label='Difference in total cost',
show_names=True,
show_clouds=True,
show_legend=True,
figure_size=6,
transparency=0.3)
SA2_baseline_strat = Econ.Strategy(name="4% Baseline",
cost_obs=[137.54],
effect_obs=[.986])
SA2_training_strat = Econ.Strategy(name="4% Training Only",
cost_obs=[144.33],
effect_obs=[.9872])
SA2_supplies_strat = Econ.Strategy(name="4% Supplies Only",
cost_obs=[136.29],
effect_obs=[.9874])
SA2_both_strat = Econ.Strategy(name="4% Both Training and Supplies",
cost_obs=[144.11],
effect_obs=[.989])
econ_eval = Econ.CEA(
strategies=[baseline_strat, training_strat, supplies_strat, both_strat],
if_paired=False)
Econ.CEA.show_CE_plane(econ_eval, title='Cost Effectiveness Analysis with 10% Hypertension',\
y_label='Cost',\
x_label='Utility',\
show_names=True,\
figure_size=6)
SA1_econ_eval = Econ.CEA(strategies=[
SA1_baseline_strat, SA1_training_strat, SA1_supplies_strat, SA1_both_strat
],
if_paired=False)
Econ.CEA.show_CE_plane(SA1_econ_eval, title='Cost Effectiveness Analysis with 18% Hypertension',\
y_label='Cost',\
x_label='Utility',\
show_names=True,\
import scr.EconEvalClasses as Econ
import Decision_Tree as Inputs
import RunTree as run
baseline_strat = Econ.Strategy(name="Baseline", cost_obs=1.44, effect_obs=.966)
training_strat = Econ.Strategy("Training Only", cost_obs=8.81, effect_obs=.9661)
supplies_strat = Econ.Strategy("Supplies Only", cost_obs=1.17, effect_obs=.968)
both_strat = Econ.Strategy("Both Training and Supplies", cost_obs=12.432, effect_obs=.915)
econ_eval=Econ.CEA(strategies=[baseline_strat, training_strat, supplies_strat, both_strat], if_paired=False)
Econ.CEA.show_CE_plane(econ_eval, title='Cost Effectiveness Analysis',\
y_label='Cost',\
x_label='Utility')
s_center[3, 1] + np.random.normal(0, 0.5, 10))
s4 = ce.Strategy("s5", s_center[4, 0] + np.random.normal(0, 0.5, 10),
s_center[4, 1] + np.random.normal(0, 0.5, 10))
s5 = ce.Strategy("s6", s_center[5, 0] + np.random.normal(0, 0.5, 10),
s_center[5, 1] + np.random.normal(0, 0.5, 10))
s6 = ce.Strategy("s7", s_center[6, 0] + np.random.normal(0, 0.5, 10),
s_center[6, 1] + np.random.normal(0, 0.5, 10))
s7 = ce.Strategy("s8", s_center[7, 0] + np.random.normal(0, 0.5, 10),
s_center[7, 1] + np.random.normal(0, 0.5, 10))
s8 = ce.Strategy("s9", s_center[8, 0] + np.random.normal(0, 0.5, 10),
s_center[8, 1] + np.random.normal(0, 0.5, 10))
s9 = ce.Strategy("s10", s_center[9, 0] + np.random.normal(0, 0.5, 10),
s_center[9, 1] + np.random.normal(0, 0.5, 10))
# create a CEA object -- unpaired
myCEA = ce.CEA([s0, s1, s2, s3, s4, s5, s6, s7, s8, s9], if_paired=True)
# plot with label and sample cloud
myCEA.show_CE_plane('CE plane with unpaired observations and showing labels',
'E[Effect]',
'E[Cost]',
show_names=True,
show_clouds=True,
figure_size=6)
# plot with sample cloud and legend
myCEA.show_CE_plane('CE Plane with unpaired observations and showing legend',
'E[Effect]',
'E[Cost]',
show_legend=True,
show_clouds=True,
