In recent years, several vector-borne, parasitic or zoonotic diseases have emerged or re-emerged in different parts of the world, with major public health, socio-economic and political consequences. Emergence of these diseases is linked to climatic change, human-induced landscape changes and human activities that have affected disease ecology. The authors illustrate geographic information system-based approaches to understand epidemiological processes and predict disease patterns. Continent-wide approaches are used to explore vector and host distributions and identify areas where substantial changes in vector and vector-borne disease distributions have occurred. Time series of high-resolution satellite data and locally collected data reveal the spatial relationships between factors impacting disease dynamics. Using Rift Valley fever as a case study, a conceptual approach is proposed to integrate all of these data and to identify key parameters for disease modelling. Some of the challenges posed by different spatial and temporal scales of the biological processes and associated indicators are highlighted.