This research will construct a mathematical model of the spread of the Ebola virus. The model will include parameters based on the characteristics of the pathogen as well as the behavior of people during outbreak situations. The results from this model will help public health officials to design and execute efficient intervention strategies for the current outbreak based on realistic pathogen features and human behaviors and help them prepare for future outbreaks. Stemming from existing models, the investigators will develop contact networks utilizing explicit agent mobility based on human behaviors. The model will generate two types of networks: a mobility and contact network as well as a disease transmission network. The model will incorporate behaviors based on evolving self-knowledge, e.g. the set of behaviors that people employ once they are aware or suspect they are infected; as well as behaviors that are in response to interventions and messaging, e.g. complying with recommendations for quarantine or not. This modeling effort contrasts with previous work on disease transmission modeling, because the contact networks will be generated by this model based on representative behaviors as opposed to being applied to the model based on theoretical network structures or previous outbreak data.