Tingting202/sdr-model-2026

Python simulation model for evaluating maternal health outcomes, health-system requirements, and cost-effectiveness of Service Delivery Redesign scenarios in Kakamega, Kenya. # Kakamega SDR Simulation Model This repository contains the open-access Python implementation of the Kakamega Service Delivery Redesign (SDR) simulation model used to evaluate maternal health outcomes, health-system requirements, and cost-effectiveness under alternative SDR implementation scenarios. ## Repository Contents - `model_run.py`: main model runner used by the dashboard and scenario analyses. - `parameters.py`: model parameters and cost assumptions. - `global_func.py`: shared probability, sampling, and DALY helper functions. - `LB_effect.py`: antenatal care and delivery-location transition logic. - `intrapartum.py`: intrapartum outcomes, maternal complications, neonatal complications, referrals, transfers, labor, and equipment requirements. - `mortality.py`: maternal mortality logic. - `costing.py`: Appendix B-aligned cost and ICER calculations. - `SDR_Dash.py`: Streamlit dashboard for interactive model exploration. - `Scenario testing/scenario_analysis.ipynb`: scenario-analysis workflow for generating multi-run simulation outputs. Model calibration and parameter definitions are described in Appendix A of the manuscript. ## Installation This project was developed with Python 3.11. ```bash python -m venv .venv source .venv/bin/activate pip install -r requirements.txt ``` If you use conda, create and activate a Python 3.11 environment before running the same `pip install -r requirements.txt` command. ## Running the Dashboard ```bash streamlit run SDR_Dash.py ``` The dashboard supports interactive baseline-versus-intervention comparisons. It reuses a cached baseline when model settings are unchanged and reruns the intervention when users adjust intervention sliders. The cost-effectiveness dashboard calls `costing.py`, so dashboard cost outputs use the same costing assumptions as Appendix B. ## Running the Model From Python The main model function is `run_model_dash()` in `model_run.py`. ```python import numpy as np from global_func import rese …