Can discrete event simulation be of use in modelling major depression?
GROUND: Depression is among the major contributors to worldwide disease burden and adequate modelling requires a framework designed to depict real world disease progression as well as its economic implications as closely as possible. OBJECTIVES: In light of the specific characteristics associated with depression (multiple episodes at varying intervals, impact of disease history on course of illness, sociodemographic factors), our aim was to clarify to what extent “Discrete Event Simulation” (DES) models provide methodological benefits in depicting disease evolution. METHODS: We conducted a comprehensive review of published Markov models in depression and identified potential limits to their methodology. A model based on DES principles was developed to investigate the benefits and drawbacks of this simulation method compared with Markov modelling techniques. RESULTS: The major drawback to Markov models is that they may not be suitable to tracking patients’ disease history properly, unle
