Chronic disease models can be used to assess the public health impact of secular changes in disease incidence, improved treatments, and starting or changing prevention and screening programs, among others. Age and time are crucial dimensions of disease models. Many approaches to chronic disease modeling exist, including analytical models, life-table models, decision analysis models, more complex macrosimulation models and microsimulation models. Whatever the approach, models should be validated to the best available primary data. Public health impact is measured in life-years or quality- or disability adjusted life-years gained. Actual models include Prevent, DisMod, MISCAN, POHEM and Archimedes. Models are increasingly used to support policy decision making and guidelines development.

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Keywords Chronic disease models, Cost-effectiveness, Decision analysis models, Life-table models, Macrosimulation, Markov models, Mathematical models, Microsimulation, Model structure, Multistate models, Population models, Public health impact, QALY, Validation
Persistent URL dx.doi.org/10.1016/B978-0-12-803678-5.00072-2, hdl.handle.net/1765/105165
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Citation
Habbema, J.D.F, Boer, R, & Barendregt, J.J.M. (2016). Chronic Disease Modeling. In International Encyclopedia of Public Health (pp. 22–27). doi:10.1016/B978-0-12-803678-5.00072-2