Duygu Balcan

TL;DR: In this paper, the authors study the interplay between short-scale commuting flows and long-range airline traffic in shaping the spatio-temporal pattern of a global epidemic.

TL;DR: The flexible structure of the model that is open to the inclusion of different disease structures and local intervention policies makes GLEaM suitable for the computational modeling and anticipation of the spatio-temporal patterns of global epidemic spreading.

TL;DR: The analysis shows the potential for an early epidemic peak occurring in October/November in the Northern hemisphere, likely before large-scale vaccination campaigns could be carried out, and suggests that the planning of additional mitigation policies such as systematic antiviral treatments might be the key to delay the activity peak in order to restore the effectiveness of the vaccination programs.

TL;DR: The results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing.

TL;DR: In this paper, a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation model was made for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country.