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Validation of Population-Based Disease Simulation Models: A Review

2010

This article develops a framework for validating population-based chronic disease simulation models, and reviews the principles and methods for such models. While computer simulation models are used increasingly to support public health research and policy, questions about their quality persist.

Based on the review, the authors formulated a set of recommendations for gathering evidence of model credibility. They find that evidence of model credibility derives from examining: 1) the process of model development, 2) the performance of a model, and 3) the quality of decisions based on the model. Many important issues in model validation are insufficiently addressed by current guidelines.

These issues include a detailed evaluation of different data sources, graphical representation of models, computer programming, model calibration, between-model comparisons, sensitivity analysis, and predictive validity. The role of external data in model validation depends on the purpose of the model (e.g., decision analysis versus prediction).

 

Source:

Kopec JA, Finès P, Manuel DG et al. Validation of Population-Based Disease Simulation Models: A Review of Concepts and Methods. BMC Public Health 2010; 10: 710. https://doi.org/10.1186/1471-2458-10-710