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In the past decade several countries and health care organizations have started using economic evaluations to decide on reimbursement of health care interventions.

Model-based health economic studies are well accepted for the assessment of the cost-effectiveness of medical interventions or strategies, as they allow the integration of efficacy and safety evidence with medical resource use and cost estimates, as well as the possibility to take into account the uncertainties that are entailed in such combination of information.

The modeling experience of Mapi Values is wide and varied and we have experience in several types of economic and disease modeling for reimbursement submissions:

• Decision analytic models
• (Semi) Markov state-transition models
• Dynamic models and infectious disease modeling
• Patient simulation models
• Comprehensive decision-modeling

A comprehensive decision modeling approach integrates Bayesian evidence synthesis and parameter estimation with cost-effectiveness-modeling in a single unified framework. It makes full allowance for any potential inter-relationships between model input parameters, and it removes the need to make parametric distributional assumptions and therefore facilitates scenario analyses.

The models we develop are not only evidence based, scientifically state of the art, and fit for purpose, but also transparent to our clients and reimbursement bodies.

There is growing interest in the cost-effectiveness of vaccines and antibiotics for infectious diseases. Dynamic modeling approaches have become very important for decision-making about the cost-effectiveness of infectious disease interventions and programs. One of the reasons is that traditional decision trees and Markov models do not capture herd immunity, thereby underestimating the cost-effectiveness of the intervention. Dynamic modeling is based on the nonlinear dynamics of infection spread in a population. By differentiating and relating groups of susceptibles (S), infected (E), infectious (I) and recovered (R), SEIR models can provide useful insights into the spread of infectious diseases such as influenza, varicella, and HPV. These relatively simple deterministic models predict the spread of transmitted viral and bacterial infections and can help identify the factors controlling the persistence and stability of these. Mapi Values has developed several dynamic models to evaluate the cost-effectiveness of vaccination, and antimicrobial treatment taking into account the development of antibiotic resistance.