Abstract

The use of mathematical modeling in economic evaluation is a frequent practice seeking toinform priority setting in healthcare. The main advantages are the possibilities of extending the analyses of randomized controlled trails to specific po-pulation groups, and in routine conditions. Likewise, modeling allows transforming intermediate outcomes (such as subrogate markers) into final health outcomes. Models, help estimating the potential impact of an intervention in the population prior implementation, and for different scenarios. In the case of diseases with complex epidemiological characteristics, such as transmission dynamics of inflectious diseases, models allow to reproduce these dynamics based on assumptions of the relationships among the variables. In this way, cost-effectiveness analysis of control interventions can be estimated. Additionally, models allow evaluating the uncertainty associated to the limitations of the available evidence, in a systematic, comprehensive and economic way. Nonetheless, the use of modeling is not free of criticisms, being the main ones related to the high number of assumptions and the luck of transparency of the internal processes (black box).