Experiment to test diagnostic noncompliance propagation

crcsim/experiment/README.md

@@ -1,10 +1,10 @@
 # Experiment: Test exp-diagnostic-and-screening-compliance-interaction with 100% and 80% Diagnostic Compliance for FQHCs
 
-This branch tests 80% and 100% compliance for FQHCs 1-8 with differing screening uptake and low and extra low costs for Stage III and Stage IV inital treatment and a new parameter propagate_diagnostic_noncompliance set to true.The branch was created from the branch diagnostic-and-screening-compliance-interaction (#435d041) to test the newly merged propagate_diagnostic_noncompliance parameter.
+This branch tests 80% and 100% compliance for FQHCs 1-8 with differing screening uptakes and a new parameter propagate_diagnostic_noncompliance toggled on and off.The branch was created from the branch diagnostic-and-screening-compliance-interaction (#435d041) to test the newly merged propagate_diagnostic_noncompliance parameter.
 
 ## Results
 
-The results show a small difference between a previous 100% and 80% compliance for FQHCs. Results are included in the summary folder.
+The results show expected changes when propagation is toggled on and off for these FQHC experiments.
 
 ## Experiment Workflow
 
@@ -70,7 +70,7 @@ The subdirectories and files in `scenarios/` must be uploaded to AWS S3 for the
 
 To upload the files to S3, run
 ```
-aws s3 cp ./scenarios s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-interaction/scenarios --recursive
+aws s3 cp ./scenarios s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-together/scenarios --recursive
 ```
 *(Another note: this manual step is necessary because `boto3` does not include functionality to upload a directory to S3 recursively. Future experiments could improve this workflow by writing a function to upload the directory recursively in `prepare.py`. Or submit a patch to resolve https://github.com/boto/boto3/issues/358)*
 

crcsim/experiment/prepare.py

@@ -1,6 +1,6 @@
 import json
 import random
-from copy import deepcopy
+from enum import Enum, unique
 from pathlib import Path
 from typing import Callable, Dict, List, Optional
 
@@ -10,6 +10,18 @@
 NUM_ITERATIONS: int = 100
 
 
+@unique
+class Test(Enum):
+    FIT = "FIT"
+    COLONOSCOPY = "Colonoscopy"
+
+
+@unique
+class ConditionalComplianceParam(Enum):
+    PREV_COMPLIANT = "compliance_rate_given_prev_compliant"
+    NOT_PREV_COMPLIANT = "compliance_rate_given_not_prev_compliant"
+
+
 class Scenario:
     def __init__(self, name: str, params: Dict):
         self.name = name
@@ -87,6 +99,13 @@ def transform(params):
     return transform
 
 
+def transform_propagate_diagnostic_noncompliance(noncompliance: bool) -> Callable:
+    def transform(params):
+        params["propagate_diagnostic_noncompliance"] = noncompliance
+
+    return transform
+
+
 def transform_diagnostic_compliance(rate: float) -> Callable:
     def transform(params):
         params["diagnostic_compliance_rate"] = rate
@@ -108,6 +127,75 @@ def transform(params):
     return transform
 
 
+def transform_fit_only() -> Callable:
+    """Transform parameters to use FIT tests only."""
+
+    def transform(params):
+        # Set FIT as the only test
+        params["routine_testing_year"] = list(range(45, 76))  # Ages 45-75
+        params["variable_routine_test"] = ["FIT"] * 31  # FIT for all years
+
+        # Disable other tests by setting their routine ages outside valid range
+        for test_name in params["tests"]:
+            if test_name != "FIT":
+                params["tests"][test_name]["routine_start"] = -1
+                params["tests"][test_name]["routine_end"] = -1
+            else:
+                params["tests"]["FIT"]["routine_start"] = 45
+                params["tests"]["FIT"]["routine_end"] = 75
+
+    return transform
+
+
+def transform_colonoscopy_only() -> Callable:
+    """Transform parameters to use Colonoscopy tests only."""
+
+    def transform(params):
+        # Set FIT as the only test
+        params["routine_testing_year"] = list(range(45, 76))  # Ages 45-75
+        params["variable_routine_test"] = ["Colonoscopy"] * 31  # FIT for all years
+
+        # Disable other tests by setting their routine ages outside valid range
+        for test_name in params["tests"]:
+            if test_name != "Colonoscopy":
+                params["tests"][test_name]["routine_start"] = -1
+                params["tests"][test_name]["routine_end"] = -1
+            else:
+                params["tests"]["Colonoscopy"]["routine_start"] = 45
+                params["tests"]["Colonoscopy"]["routine_end"] = 75
+
+    return transform
+
+
+def transform_conditional_compliance_rates(
+    param: ConditionalComplianceParam, rates: List[float]
+) -> Callable:
+    """
+    Replaces a conditional compliance parameter with a new set of rates.
+    """
+
+    def transform(params):
+        for test in params["tests"]:
+            params["tests"][test][param.value] = rates
+
+    return transform
+
+
+def transform_routine_ages(test: Test, start_age: int, end_age: int) -> Callable:
+    def transform(params):
+        params["tests"][test.value]["routine_start"] = start_age
+        params["tests"][test.value]["routine_end"] = end_age
+
+    return transform
+
+
+def transform_routine_proportion(test: Test, proportion: float) -> Callable:
+    def transform(params):
+        params["tests"][test.value]["proportion"] = proportion
+
+    return transform
+
+
 def create_scenarios() -> List:
     # For each health center, define the initial compliance rate in the baseline
     # scenario and the implementation scenario and vary diagnostic compliance.
@@ -121,99 +209,113 @@ def create_scenarios() -> List:
         "fqhc7": (0.257, 0.354),
         "fqhc8": (0.190, 0.390),
     }
-    low_initial_stage_3_treatment_cost = 67_300
-    low_initial_stage_4_treatment_cost = 97_931
-    extra_low_initial_stage_3_treatment_cost = 50_000
-    extra_low_initial_stage_4_treatment_cost = 80_000
 
     diagnostic_compliance_rates = {
         "100Compliance": 1.0,
         "80Compliance": 0.8,
     }
+
+    propagate_diagnostic_noncompliance = {
+        "Propagation_on": True,
+        "Propagation_off": False,
+    }
     scenarios = []
 
     for fqhc, sreening_rates in initial_compliance.items():
         for compliance, diagnostic_rate in diagnostic_compliance_rates.items():
-            baseline = (
-                Scenario(
-                    name=f"{fqhc}_{compliance}_baseline", params=get_default_params()
+            for (
+                propogation_name,
+                propagation_value,
+            ) in propagate_diagnostic_noncompliance.items():
+                baseline = (
+                    Scenario(
+                        name=f"{propogation_name}_{fqhc}_{compliance}_baseline",
+                        params=get_default_params(),
+                    )
+                    .transform(transform_initial_compliance(sreening_rates[0]))
+                    .transform(transform_diagnostic_compliance(diagnostic_rate))
+                    .transform(
+                        transform_propagate_diagnostic_noncompliance(propagation_value)
+                    )
                 )
-                .transform(transform_initial_compliance(sreening_rates[0]))
-                .transform(transform_diagnostic_compliance(diagnostic_rate))
-            )
-            scenarios.append(baseline)
-
-            implementation = (
-                Scenario(
-                    name=f"{fqhc}_{compliance}_implementation",
-                    params=get_default_params(),
+                scenarios.append(baseline)
+
+                implementation = (
+                    Scenario(
+                        name=f"{propogation_name}_{fqhc}_{compliance}_implementation",
+                        params=get_default_params(),
+                    )
+                    .transform(transform_initial_compliance(sreening_rates[1]))
+                    .transform(transform_diagnostic_compliance(diagnostic_rate))
+                    .transform(
+                        transform_propagate_diagnostic_noncompliance(propagation_value)
+                    )
                 )
-                .transform(transform_initial_compliance(sreening_rates[1]))
-                .transform(transform_diagnostic_compliance(diagnostic_rate))
+                scenarios.append(implementation)
+
+    for (
+        propogation_name,
+        propagation_value,
+    ) in propagate_diagnostic_noncompliance.items():
+        # No screening baseline scenario
+        no_screening = (
+            Scenario(
+                name=f"{propogation_name}_no_screening", params=get_default_params()
             )
-            scenarios.append(implementation)
-
-            # Sensitivity analysis 2. Lower cost for stage III and stage IV initial phase
-            baseline_low_cost = deepcopy(baseline)
-            baseline_low_cost.transform(
-                transform_treatment_cost(
-                    "3", "initial", low_initial_stage_3_treatment_cost
-                )
-            ).transform(
-                transform_treatment_cost(
-                    "4", "initial", low_initial_stage_4_treatment_cost
-                )
+            .transform(transform_fit_only())
+            .transform(transform_routine_proportion(Test.FIT, 1.0))
+            .transform(transform_routine_ages(Test.FIT, -1, -1))
+            .transform(transform_propagate_diagnostic_noncompliance(propagation_value))
+        )
+        scenarios.append(no_screening)
+
+        # Full FIT compliance baseline
+        full_FIT_compliance = (
+            Scenario(
+                name=f"{propogation_name}_full_FIT_compliance",
+                params=get_default_params(),
             )
-            baseline_low_cost.name = (
-                f"{fqhc}_{compliance}_baseline_low_initial_treat_cost"
-            )
-            scenarios.append(baseline_low_cost)
-
-            implementation_low_cost = deepcopy(implementation)
-            implementation_low_cost.transform(
-                transform_treatment_cost(
-                    "3", "initial", low_initial_stage_3_treatment_cost
-                )
-            ).transform(
-                transform_treatment_cost(
-                    "4", "initial", low_initial_stage_4_treatment_cost
+            .transform(transform_fit_only())
+            .transform(transform_routine_proportion(Test.FIT, 1.0))
+            .transform(transform_routine_proportion(Test.COLONOSCOPY, 0.0))
+            .transform(transform_initial_compliance(1.0))
+            .transform(
+                transform_conditional_compliance_rates(
+                    ConditionalComplianceParam.PREV_COMPLIANT, [float(1.0)] * 31
                 )
             )
-            implementation_low_cost.name = (
-                f"{fqhc}_{compliance}_implementation_low_initial_treat_cost"
-            )
-            scenarios.append(implementation_low_cost)
-
-            # Sensitivity analysis 2a. Extra low cost for stage III and stage IV initial phase
-            baseline_extra_low_cost = deepcopy(baseline)
-            baseline_extra_low_cost.transform(
-                transform_treatment_cost(
-                    "3", "initial", extra_low_initial_stage_3_treatment_cost
-                )
-            ).transform(
-                transform_treatment_cost(
-                    "4", "initial", extra_low_initial_stage_4_treatment_cost
+            .transform(
+                transform_conditional_compliance_rates(
+                    ConditionalComplianceParam.NOT_PREV_COMPLIANT, [float(1.0)] * 31
                 )
             )
-            baseline_extra_low_cost.name = (
-                f"{fqhc}_{compliance}_baseline_extra_low_initial_treat_cost"
+            .transform(transform_propagate_diagnostic_noncompliance(propagation_value))
+        )
+        scenarios.append(full_FIT_compliance)
+
+        # Full Colonoscopy compliance baseline
+        full_Colonoscopy_compliance = (
+            Scenario(
+                name=f"{propogation_name}_full_Colonoscopy_compliance",
+                params=get_default_params(),
             )
-            scenarios.append(baseline_extra_low_cost)
-
-            implementation_extra_low_cost = deepcopy(implementation)
-            implementation_extra_low_cost.transform(
-                transform_treatment_cost(
-                    "3", "initial", extra_low_initial_stage_3_treatment_cost
-                )
-            ).transform(
-                transform_treatment_cost(
-                    "4", "initial", extra_low_initial_stage_4_treatment_cost
+            .transform(transform_colonoscopy_only())
+            .transform(transform_routine_proportion(Test.FIT, 0.0))
+            .transform(transform_routine_proportion(Test.COLONOSCOPY, 1.0))
+            .transform(transform_initial_compliance(1.0))
+            .transform(
+                transform_conditional_compliance_rates(
+                    ConditionalComplianceParam.PREV_COMPLIANT, [float(1.0)] * 31
                 )
             )
-            implementation_extra_low_cost.name = (
-                f"{fqhc}_{compliance}_implementation_extra_low_initial_treat_cost"
+            .transform(
+                transform_conditional_compliance_rates(
+                    ConditionalComplianceParam.NOT_PREV_COMPLIANT, [float(1.0)] * 31
+                )
             )
-            scenarios.append(implementation_extra_low_cost)
+            .transform(transform_propagate_diagnostic_noncompliance(propagation_value))
+        )
+        scenarios.append(full_Colonoscopy_compliance)
     return scenarios
 
 

crcsim/experiment/pyproject.toml

@@ -16,9 +16,9 @@ authors = [
 ]
 
 dependencies = [
-    # Clone the specific commit of the model that you want to use for the experiment
-    "crcsim @ git+https://github.com/RTIInternational/crcsim.git@6c264ca5e35c1b9ae20a6e4b95818f6e00970d71",
-    "fire==0.5.0",
+    # installing crcsim from latest commit on main to get propagate noncompliance feature
+    "crcsim @ git+https://github.com/RTIInternational/crcsim.git@c4e08bffba34c07d18b784c0632de506a36611e8",
+    "fire==0.7.0",
     "pandas==2.1.1",
     "openpyxl==3.0.9",
     "wheel==0.41.2",

crcsim/experiment/run_iteration.sh

@@ -12,7 +12,7 @@ if [ ! -d "$output_dir" ]; then
   mkdir $output_dir
 fi
 
-aws s3 cp "s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-interaction/scenarios/$scenario/params.json" "./params.json" 
+aws s3 cp "s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-together/scenarios/$scenario/params.json" "./params.json" 
 
 crc-simulate \
     --npeople=$npeople \
@@ -23,5 +23,5 @@ crc-simulate \
 crc-analyze \
     --params-file=./params.json &&
 
-aws s3 cp ./results.csv "s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-interaction/scenarios/$scenario/results_$iteration.csv"
-aws s3 cp ./output.csv "s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-interaction/$scenario/output_$iteration.csv"
+aws s3 cp ./results.csv "s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-together/scenarios/$scenario/results_$iteration.csv"
+aws s3 cp ./output.csv "s3://crcsim-exp-fqhc-diagnostic-and-screening-compliance-together/$scenario/output_$iteration.csv"