This project aims to develop a decision support platform for epidemic interventions’ simulation and recommendation (including pandemics like COVID-19). The platform provides an interactive analytic front-end that enables decision-makers to simulate, analyze, visualize and predict different interventions and their effects, and it supports both macro and micro-level interventions design and recommendation. The platform will be developed by experts in AI, mathematical modeling, and disease spreading simulations, and will be built on top of digital twin replicas of cities. The digital twin model incorporated in the platform takes into account many special factors related to the modeled city and it is able to capture a variety of its complex dynamics. All of this enables the platform to support a wide range of legislations and recommendations. For example, the platform is able to estimate the risk of disease spreading inside the different points-of-interest, which can be used to prioritize social distancing rules enforcement where it matters the most. In addition, the platform is able to spatially and temporally predict the future trajectories of disease spreading, which can guide the process of devising suitable precautionary measures.