The rate of new emerging infectious diseases entering the human population has increased over the past century, with pathogens originating from animals or from products of animal origin accounting for the vast majority. Primary risk factors for the emergence and spread of emerging zoonoses include expansion and intensification of animal agriculture and long-distance live animal transport, live animal markets, bushmeat consumption and habitat destruction. Developing effective control strategies is contingent upon the ability to test causative hypotheses of disease transmission within a statistical framework. Broadly speaking, molecular phylogeography offers a framework in which specific hypotheses regarding pathogen gene flow and dispersal within an ecological context can be compared. A number of different methods has been developed for this application. Here, our intent is firstly to discuss the application of a wide variety of statistically based methods (including Bayesian reconstruction, network parsimony analysis and regression) to specific viruses (influenza, salmon anaemia virus, foot and mouth disease and Rift Valley Fever) that have been associated with animal farming/movements; and secondly to place them in the larger framework of the threat of potential zoonotic events as well as the economic and biosecurity implications of pathogen outbreaks among our animal food sources.