The role of computer simulation models in the design of public policies

Abstract

Cardiovascular diseases are the number one cause of death globally, but their optimal prevention remains a challenge. A high-risk approach can only have a limited effect at a population level, while population-based strategies can improve and extend the coverage of a high-risk approach. However, one main problem for promoting cardiovascular diseases prevention public policies is the difficulty to foresee population health benefits of a single policy. Computer simulation models can assist with this problem, due to their ability to estimate intervention effects over different periods, and by scaling up the evidence to a broader, more diverse population. Their applicability to countries with different social, political and economic contexts can assist in the design of public policies. There are several models that assess health and economics scenarios, but regardless which model is chosen, when adequately used, they can provide reasonable estimations of health policies’ impact. There is a growing consensus amongst the public health communities about the powerful role of population-level policies. They are more effective, cost saving and more equitable when compared with individual-level interventions. Policy makers and the public health community need to make further progress in changing the focus of prevention, from individuals to populations.