OBJECTIVES: The objective was to compare two modeling approaches to estimate the future burden of hepatitis C in selected countries. Due to varying efficacy depending on host factors such as viral load at baseline, disease duration, pre-treatment status, and disease severity more complex modeling is required. METHODS: Two models were developed. Model A was based on a classic Markov model with seven disease states modeling the impact of the new drugs based on response-guided therapy and efficacy. Drug acquisition cost, treatment management and annual health care cost were determined and the potential budget impact was assessed. Several “what if” analyses were performed. Model B is a dynamic, individual-based, stochastic model providing a powerful tool to perform sensitivity analysis on uncertain and disputed parameters. All input variables (incidence, prevalence, genotype distribution, cost, drug efficacy) were derived from a systematic literature and database review and analysis. RESULTS: In “what if” scenarios with varying treatment rates the time and cost to potential elimination of hepatitis C were modeled. Assuming all patients currently infected with hepatitis C would be treated from 2012 onwards, with efficacies (SVR) ranging between 70% and 80%, and assuming constant infection rates resulted in elimination of hepatitis C by the year 2030 in model A. In model B, in which individual-based host factors were taken into account, elimination was not achieved in the same time period. Different “what if” scenarios for non-responders, variations in baseline host factors, potential relapses and development of resistance were modeled more reliable with the individual-based model. CONCLUSIONS: Modeling “what if” scenarios on the basis of expected drug efficacy utilizing a dynamic, individual-based stochastic model results in a more comprehensive tool to estimate the distribution of expected future burden of HCV.