Disease control is of paramount importance in public health, with total eradication as the ultimate goal. Mathematical models of disease spread in populations are an important component in implementing effective vaccination and treatment campaigns. However, human behavior in response to an outbreak of disease has only recently been included in the modeling of epidemics on networks. In this talk, I will review some of the mathematical models and machinery used to describe the underlying dynamics of rare events in finite population disease models, which include human reactions on what are called adaptive networks. I will show how to derive a new model that includes a dynamical systems description of the force of the noise that drives the disease to extinction. Coupling the effective force of noise with vaccination as well as human behavior reveals how to best utilize stochastic disease controlling resources such as vaccination and treatment programs. Finally, I will also present a general theory to derive the most probable paths to extinction for heterogeneous networks. This research has been supported by the Office of Naval Research, Air Force of Scienti?c Research and the National Institutes of Health.=