SLIDE 2 NOTES: Elements of the Miscan Model’s structure are shown in this frame. The micro-simulation model treats time as a continuous variable, with discrete events occurring along the time line. So, for example, the appearance of a polyp of a particular size is a discrete event. (The model identifies three sizes.) But the dwelling time of such a polyp before it progresses to a larger size can be any length. Probability functions determine when the transition from one state to another will occur.
By parallel universe, we mean that the model first generates a complete simulated, or hypothetical, population of individuals with their complete natural history in the absence of screening. The results of that baseline simulation, with all pertinent clinical details, are stored. Then, the model begins again with the same population as before, but this time a particular screening strategy is imposed. Assumptions about the effect of screening on the clinical course of each patient determine a new set of simulated results. The net effect of the screening strategy is determined per life history by the changes that occur compared with the baseline.
The model provides outputs on a real population in any specific calendar year. Most of our published work has taken that approach. However, the model is flexible in that a specific cohort of individuals (such as 50 year old men) can be followed throughout the rest of their lives. For the pre-workshop exercise, we did adapt the model to a cohort structure.