In recent years a huge flow of quantitative social, demographic and behavioural data is becoming available spurring the quest for innovative technologies that can improve the traditional disease-surveillance systems, providing faster and better localized detection capabilities and resulting in a broad practical impact. Improved ICT techniques and methodologies support the inter-linkage and integration of datasets causing a qualitative change in the ways we can model epidemic processes. Visualization and analysis tools able to cope with multiple levels of representation are being developed along with computer simulations that provide experiments not feasible in the real world. For the first time, ICT and computation enable the study of epidemic in a comprehensive fashion that addresses the complexity inherent to the biological, social and behavioural aspects of health related problems. The EPIWORK project proposes a multidisciplinary research effort aimed at developing the approriate framework of tools and knowledge needed for the design of epidemic forecast infrastructures. The research considers most of the much needed development of modeling, computational and ICT tools such as i) the foundation and development of the mathematical and computational methods needed to achieve prediction and predictability of disease spreading in complex social systems; ii) the development of large scale, data driven computational models endowed with a high level of realism and aimed at epidemic scenario forecast; iii) the design and implemention of original data-collection schemes motivated by identified modelling needs, such as the collection of real-time disease incidence, through innovative web and ICT applications. v) the set up of a computational platform for epidemic research and data sharing that will generate important synergies between research communities and countries.