A model of infectious diseases has been developed for integration within a larger simulation structure to assess the interdependencies of critical infrastructures. The model has been parameterized to model a disease outbreak a large metropolitan area. The model subsequently calculates the spread of the infection and the influence of vaccination policies, quarantine and isolation procedures. Consequences are deaths, illnesses, and a variety of economic costs. Sensitivity analysis is a statistical technique to investigate how uncertainty in the input variables affects the model outputs and which input variables tend to drive variation in the outputs. Such analysis can provide critical information for decision makers and public health officials who may have to deal with the realities of a virulent infectious disease. This paper presents the results of preliminary analyses of the effects of inputs to the infectious disease model on the calculated consequences.