Discrete-Event Simulation Model for Cancer Interventions and Population Health in R (DESCIPHR): An Open-Source Pipeline.

ABSTRACT: Simulation models inform health policy decisions by integrating data from multiple sources and forecasting outcomes when there is a lack of comprehensive evidence from empirical studies. Such models have long supported health policy for cancer, the first or second leading cause of death in over 100 countries. Discrete-event simulation (DES) and Bayesian calibration have gained traction in the field of Decision Science because they enable efficient and flexible modeling of complex health conditions and produce estimates of model parameters that reflect real-world disease epidemiology and data uncertainty given model constraints. This uncertainty is then propagated to model-generated outputs, enabling decision makers to determine the optimal strategy to recommend, assess confidence in the re

SUBMITTER: Pi S 

PROVIDER: S-EPMC12132142 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature