The data science revolution is finally enabling the development of large-scale data-driven network models that provide scenarios, 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 streams (social networks, participatory platform, human mobility etc.). I will review and discuss recent results and challenges in the area, and focus on ongoing work aimed at responding to the COVID-19 pandemic.
Alessandro Vespignani is the Sternberg Family Distinguished University professor at Northeastern University. He is the founding director of the Network Science Institute and leads the Laboratory for the Modeling of Biological and Socio-technical Systems. Vespignani’s recent work focuses on data-driven computational modeling and forecast of emerging infectious diseases; resilience of complex networks; and collective behavior of techno-social systems. Vespignani is an elected fellow of the American Physical Society, member of the Academy of Europe, and fellow of the Institute for Quantitative Social Sciences at Harvard University. He has received the John Graunt award for extraordinary achievements in population sciences, the Senior Scientific award of the Complex Systems Society for outstanding contributions to Complex Systems & Network sciences, and the Aspen Institute Italia Award for scientific research.