In this thesis, I investigated the relationship between host and pathogen in multi-host and multi-pathogen systems at the interface between wildlife and domestic species. The term “epidemiological interaction” was central to my thesis, and was defined as “any ecological interaction between two host populations resulting in the transmission of one or more pathogen”. Epidemiological interactions are related to the processes of transmission between hosts and I investigated how these epidemiological interactions between different host populations could be investigated in a given ecosystem. I developed two research frameworks to estimate these epidemiological interactions: 1) an a priori approach based on the host data and assuming that the mobility of hosts and the resulting contacts between host populations would be crucial factors influencing the epidemiological interactions; 2) an a posteriori approach based on the pathogen data, assuming that epidemiological pathways previously used by some pathogen species can be used in the future by other pathogens. The animalpathogen model used to test the first approach was the bird-avian influenza viruses’ model. Longitudinal counting and sampling protocols of domestic and wild birds over two years were used to analyse community composition and abundance of hosts to compare with the prevalence of avian influenza viruses. I could, for the first time, show a persistence of low pathogenic avian influenza strains in an African ecosystem, and investigate the relationships with both the potential maintenance hosts (Afro-tropical ducks and resident species) and hosts that introduced the virus into the system from Europe or Asia (paleartic migrants). With the estimation of epidemiological interaction using host community data, I estimated the contact rate between wild and domestic avian compartments (intensive poultry, backyard and farmed ostrich compartments) and assigned a risk to this interaction based on dynamic and non dynamic factors for each bird species. This approach highlights the species or seasons at risk for the domestic compartments (or for the wild bird compartments depending on the perspective) in order to orientate surveillance or control options. This type of data and framework can also be used in mechanistic modelling to predict the spread of a pathogen after its introduction in one compartment. I tested the host approach in a broader dataset at the Southern African region level with similar counting and sampling database in multiple study sites, showing that the variability of host communities across the region could explain the variability of pathogen detection (however, finding a causal relationship was impossible). Finally, I theoretically developed the pathogen approach by combining tools used in parasite community ecology, molecular epidemiology and social network analysis and gave a theoretical example using a rodent and human macro and microparasite dataset. This thesis has explored the field of transmission ecology and offered ways to quantify the processes of transmission between host populations. Theoretically, I have developed a fundamental reflexion around epidemiological interactions and formulated hypotheses on their potential for being independent of the parasite species. Practically, I have developed tools to provide information for decision-making in order to improve efficiency of surveillance and control programmes at the wildlife/domestic interface particularly adapted to detect emerging infectious disease spill-over process.