Exp accsis scenarios

crcsim/experiment/README.md

@@ -1,10 +1,10 @@
-# Experiment: Test 100% and 80% Diagnostic Compliance for FQHCs and No Screening, All FIT, and ALL Colonocscopy
+# Experiment: ACCSIS Runs and No Screening, All FIT, and ALL Colonocscopy
 
-This branch tests 80% and 100% compliance for FQHCs 1-8 with differing screening uptake, differing test costs, and low and extra low costs for Stage III and Stage IV inital treatment. Scenarios for no screening, 100% colonoscopy, and 100% FIT were also added.
+This branch tests ACCSIS inital and diagnostic screening compliance for different sites. Scenarios for no screening, 100% colonoscopy, and 100% FIT were also added to ensure model is running as expected.
 
 ## Results
 
-The results for the 100% diagnostic compliance match a previous run from April 2025. The results differ between 80% and 100% compliance.
+The results for the 100% diagnostic compliance match a previous run from April 2025. Results for NC are included now but more will be added.
 
 ## 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-compliance-comp-additional-scenarios/scenarios --recursive
+aws s3 cp ./scenarios s3://crcsim-exp-accsis-scenarios/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 +1,5 @@
 import json
 import random
-from copy import deepcopy
 from enum import Enum, unique
 from pathlib import Path
 from typing import Callable, Dict, List, Optional
@@ -27,6 +26,11 @@ class Test(Enum):
     COLONOSCOPY = "Colonoscopy"
 
 
+@unique
+class IRR(Enum):
+    irr = 1.19
+
+
 @unique
 class ConditionalComplianceParam(Enum):
     PREV_COMPLIANT = "compliance_rate_given_prev_compliant"
@@ -200,122 +204,54 @@ def transform(params):
 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.
-    initial_compliance = {
-        "fqhc1": (0.522, 0.593),
-        "fqhc2": (0.154, 0.421),
-        "fqhc3": (0.519, 0.568),
-        "fqhc4": (0.278, 0.374),
-        "fqhc5": (0.383, 0.572),
-        "fqhc6": (0.211, 0.392),
-        "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,
-    }
 
-    FIT_cost_dict = {
-        "Public": 22,
-        "Patient+Public": 44,
+    compliance_rates = {
+        "NC": {
+            "initial": (0.097, 0.300),
+            "diagnostic": (0.444, 0.688),
+        },
+        # other items
     }
 
-    Colonoscopy_cost_dict = {
-        "Public": 912,
-        "Patient+Public": 1437,
+    costs = {
+        "public": {
+            "FIT": 22,
+            "Colonoscopy": 912,
+        },
+        #'Patient-Public": {"FIT": 44, "Colonoscopy": 1437,}
     }
 
     scenarios = []
 
-    for fqhc, screening_rates in initial_compliance.items():
-        for compliance, diagnostic_rate in diagnostic_compliance_rates.items():
-            for cost_category in (
-                FIT_cost_dict.keys() & Colonoscopy_cost_dict.keys()
-            ):  # Only common keys
-                FIT_cost = FIT_cost_dict[cost_category]
-                Col_cost = Colonoscopy_cost_dict[cost_category]
-                baseline = (
-                    Scenario(
-                        name=f"{fqhc}_{cost_category}_{compliance}_baseline",
-                        params=get_default_params(),
-                    )
-                    .transform(transform_initial_compliance(screening_rates[0]))
-                    .transform(transform_diagnostic_compliance(diagnostic_rate))
-                    .transform(transform_test_cost(Test.FIT, FIT_cost))
-                    .transform(transform_test_cost(Test.COLONOSCOPY, Col_cost))
-                )
-                scenarios.append(baseline)
-
-                implementation = (
-                    Scenario(
-                        name=f"{fqhc}_{cost_category}_{compliance}_implementation",
-                        params=get_default_params(),
-                    )
-                    .transform(transform_initial_compliance(screening_rates[1]))
-                    .transform(transform_diagnostic_compliance(diagnostic_rate))
-                    .transform(transform_test_cost(Test.FIT, FIT_cost))
-                    .transform(transform_test_cost(Test.COLONOSCOPY, Col_cost))
+    for site, rates in compliance_rates.items():
+        for cost_category, test_costs in costs.items():
+            FIT_cost = test_costs["FIT"]
+            Col_cost = test_costs["Colonoscopy"]
+            baseline = (
+                Scenario(
+                    name=f"{site}_{cost_category}_baseline",
+                    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
-                    )
-                )
-                baseline_low_cost.name = f"{fqhc}_{cost_category}_{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
-                    )
-                )
-                implementation_low_cost.name = f"{fqhc}_{cost_category}_{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
-                    )
-                )
-                baseline_extra_low_cost.name = f"{fqhc}_{cost_category}_{compliance}_baseline_extra_low_initial_treat_cost"
-                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_initial_compliance(rates["initial"][0]))
+                .transform(transform_diagnostic_compliance(rates["diagnostic"][0]))
+                .transform(transform_test_cost(Test.FIT, FIT_cost))
+                .transform(transform_test_cost(Test.COLONOSCOPY, Col_cost))
+                .transform(transform_lesion_risk_alpha(IRR.irr.value))
+            )
+            scenarios.append(baseline)
+
+            implementation = (
+                Scenario(
+                    name=f"{site}_{cost_category}_implementation",
+                    params=get_default_params(),
                 )
-                implementation_extra_low_cost.name = f"{fqhc}_{cost_category}_{compliance}_implementation_extra_low_initial_treat_cost"
-                scenarios.append(implementation_extra_low_cost)
+                .transform(transform_initial_compliance(rates["initial"][1]))
+                .transform(transform_diagnostic_compliance(rates["diagnostic"][1]))
+                .transform(transform_test_cost(Test.FIT, FIT_cost))
+                .transform(transform_test_cost(Test.COLONOSCOPY, Col_cost))
+                .transform(transform_lesion_risk_alpha(IRR.irr.value))
+            )
+            scenarios.append(implementation)
 
     # No screening baseline scenario
     no_screening = (

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-compliance-comp-additional-scenarios/scenarios/$scenario/params.json" "./params.json" 
+aws s3 cp "s3://crcsim-exp-accsis-scenarios/scenarios/$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-compliance-comp-additional-scenarios/scenarios/$scenario/results_$iteration.csv"
-aws s3 cp ./output.csv "s3://crcsim-exp-fqhc-diagnostic-compliance-comp-additional-scenarios/$scenario/output_$iteration.csv"
+aws s3 cp ./results.csv "s3://crcsim-exp-accsis-scenarios/scenarios/$scenario/results_$iteration.csv"
+aws s3 cp ./output.csv "s3://crcsim-exp-accsis-scenarios/$scenario/output_$iteration.csv"

crcsim/experiment/scenarios/fqhc1_Public_100Compliance_implementation/params.json → crcsim/experiment/scenarios/NC_public_baseline/params.json

@@ -55,11 +55,11 @@
   "surveillance_freq_cancer_rest": 5,
   "surveillance_end_age": 85,
   "use_conditional_compliance": true,
-  "initial_compliance_rate": 0.593,
+  "initial_compliance_rate": 0.097,
   "never_compliant_rate": 0.0,
-  "diagnostic_compliance_rate": 1.0,
+  "diagnostic_compliance_rate": 0.444,
   "surveillance_compliance_rate": 1.0,
-  "lesion_risk_alpha": 0.47,
+  "lesion_risk_alpha": 0.5592999999999999,
   "lesion_risk_beta": 2.45,
   "lesion_incidence_ages": [
     0,

crcsim/experiment/scenarios/fqhc1_Public_100Compliance_baseline/params.json → crcsim/experiment/scenarios/NC_public_implementation/params.json

@@ -55,11 +55,11 @@
   "surveillance_freq_cancer_rest": 5,
   "surveillance_end_age": 85,
   "use_conditional_compliance": true,
-  "initial_compliance_rate": 0.522,
+  "initial_compliance_rate": 0.3,
   "never_compliant_rate": 0.0,
-  "diagnostic_compliance_rate": 1.0,
+  "diagnostic_compliance_rate": 0.688,
   "surveillance_compliance_rate": 1.0,
-  "lesion_risk_alpha": 0.47,
+  "lesion_risk_alpha": 0.5592999999999999,
   "lesion_risk_beta": 2.45,
   "lesion_incidence_ages": [
     0,