Leishmaniasis, caused by infections due to species of the genus Leishmania, occurs in cutaneous, mucocutaneous and visceral forms. The disease affects over 350 million people worldwide (mostly in developing nations) with an incidence rate of about 1.5-2 million cases per year. Existing forms of treatment are either too expensive or have toxic side effects, and resistance to some treatments is on the rise. In an effort to identify innovative drug targets, understand biological mechanisms of disease transmission, characterize pathology and develop public health strategies, we present a novel integrated engineering framework called IDEAS (Infectious Disease Engineering, Analysis and Simulation). IDEAS couples genome-scale metabolic reconstructions with life-cycle, population dynamics and immunological simulations. We reconstructed the metabolic network of the recently sequenced Leishmania major and accounted for the gene-protein-reaction relationships of a significant portion of the annotated genome. Furthermore, using flux balance analysis, we made predictions of growth dynamics in various cellular environments, analyzed the lethality of gene knockouts and compared our results to experimental data. This work constitutes one of the first network analyses of a pathogen responsible for an emerging and uncontrolled disease. We will also discuss the recent use of agent-based modeling to characterize immune system responses to various Leishmania species. The human immune response to species that elicit a non-fatal cutaneous infection is different from the response to species causing life-threatening visceral leishmaniasis. Ultimately, IDEAS aims to build multi-level computational models that connect genome-scale metabolic network reconstructions with parasite epidemiology to generate potential therapeutic applications.