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ABSTRACT / While every network scientist has encountered spreading models in some form and while such models have become increasingly detailed e.g. through the use of temporal networks, the ongoing pandemic has exposed many gaps in our knowledge. My talk will mostly focus on these gaps. To write a detailed model of contagious disease that spreads through temporal networks of contacts, what should we consider? What do we know, and what bits of information are missing? Do we know which characteristic features of temporal contact networks are important? I’ll try to address these questions by breaking a typical spreading model into parts (model of disease progression, model of transmission, model of contact structure). Finally, I will also address some interventions whose modelling benefits from the use of temporal networks.
BIO / Jari Saramäki is a professor of Computational Science and vice head at the Department of Computer Science, Aalto University, Finland. He received his PhD in applied physics in 1998, studying quantum crystals at milliKelvin temperatures. After some career twists and turns involving technology companies and what we would nowadays call data science, he returned to academia in 2003 to study complex networks, a new and rapidly expanding field at that time. Jari Saramäki is probably best known for his work on social and temporal networks, but his broad range of research interests has included topics from ant supercolonies to the human immune system.