Application of discrete event simulation model in analysis on cost-effectiveness of epidemiology screening

Abstract

Discrete event simulation (DES) model is based on individual data, by which discrete events over time are simulated to reflect disease progression. The effects of individual characteristics on disease progression could be considered in the DES model. Moreover, unlike state-transition models, DES model without setting of fixed cycle can contribute to more accurate estimation of event time, especially in the evaluation of the long-term effectiveness of screening strategies for complex diseases in which time dimension needs to be considered. This article introduces the general principles, construction steps, analytic methods and other relevant issues of the DES model. Based on a research case of estimating the cost-effectiveness of screening for abdominal aortic aneurysms in women aged 65 years and above in the United Kingdom, key points in applications of the DES model in analysis on effectiveness of complex disease screening are discussed in detail, including model construction and analysis and interpretation of the results. DES model can predict occurring time of discrete events accurately by establishing the distribution function of their occurring time and is increasingly used to evaluate the screening strategies for complex diseases in which time dimension needs to be considered. In the construction of DES model, it is necessary to pay close attention to the clear presentation of model structure and simulation process and follow the relevant reporting specification to conduct cost-effectiveness analysis to ensure the transparency and repeatability of the research.