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Joint ICTP-SISSA Colloquium | Computational Epidemiology at the time of COVID-19

30 April 2020
A seminar by Alex Vespignani of Northeastern University

The data science revolution is finally enabling the development of large-scale data-driven models that provide real- or near-real-time forecasts and risk analysis for infectious disease threats. These models also provide rationales and quantitative analysis to support policy making decisions and intervention plans. At the same time, the non-incremental advance of the field presents a broad range of challenges: algorithmic (multiscale constitutive equations, scalability, parallelization), real time integration of novel digital data stream (social networks, participatory platform, human mobility etc.). On Wednesday 6 May 2020 at 3 pm Alex Vespignani of Northeastern University will review and discuss recent results and challenges in the area, and focus on ongoing work aimed at responding to the COVID-19 pandemic.

Alex Vespignani is the Director of the Network Science Institute and Sternberg Family Distinguished University Professor with interdisciplinary appointments in the College of Computer and Information Science, College of Science and the Bouvé College of Health
Sciences, Northeastern University, USA. His research interests include complex systems and networks, and the data-driven computational modeling of epidemics.

The video recording is available here.

(Image by Omni Matryx from Pixabay)