Malaria is a serious ailment that can be life-threatening if not treated early. It has remained a significant global health burden over the past few decades. In Kenya, it is still one of the leading causes of morbidity and mortality despite substantial efforts to provide access to treatment. In this session, we apply microsimulation modelling techniques to estimate the age-specific cost of malaria in Kenya. This involves modelling malaria cost at an individual level, enabling us to retrieve and use person-specific information otherwise concealed in the aggregates. The incorporation of a resistance model helped us to evaluate a vaccination programme.