Micro-simulation is a form of economic modelling where individual modelled subjects are processed through the model one-by-one, with their results stored and aggregated to represent the experience of the entire cohort. Unlike Markov models, which consider the cohort’s experience in a single pass, micro-simulation models provide a more granular approach.

Key features of micro-simulation include:

– Individual Processing: Each individual in the cohort is modeled separately, allowing for detailed tracking of their unique pathways and outcomes.

– Aggregation of Results: The individual results are aggregated to obtain the overall experience of the cohort.

– Dynamic Risk Factors: Micro-simulation is particularly useful when individuals have a mix of interrelated and potentially changing risk factors influencing their disease progression over time.

– Interaction Modelling: It is effective for scenarios where interactions between individuals are important, such as in the modeling of infectious diseases.

Although micro-simulation models are more complex to create, they offer greater flexibility and applicability compared to cohort Markov models. They are especially valuable for cohorts with varying characteristics at the start of the modeled period, allowing for more personalized and detailed analysis of health interventions and their economic impacts. This approach can accommodate diverse initial risk factor profiles and provide insights into how these factors influence long-term health outcomes and costs.


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