Titles and abstracts:

Nicos Georgiou: Mean-field limit and parameter estimation for contagion dynamics on higher-order structures

Classical models of contagion epidemics have graph based representations where the nodes represent the population and infections occur from an infected individual to a susceptible individual via a network link between them. At the same time, healing mechanisms try to fight the epidemic at node level. The simple descriptions of these representations also underscore their limitations, since the propagation of contagions in complex systems often involves repeated or simultaneous stimuli that individuals receive from their social contacts (such as their work or household). One may mechanistically encode these non-linear effects into contagion models by considering interactions that go beyond simple pairwise connections, by using hypergraphs rather than graphs. In this talk we will see the role higher-order interactions can play in the behaviour of the model when a rigorous mean-field can be obtained. Furthermore, we will discuss some inference techniques for the parameters of the epidemic (rates of infection) when only partial information on the type of infection is available and with only a single realisation of the epidemic curve as a datum.  

Christian Kühn: Epidemic Dynamics: From Simple Models to Complex Systems

In this talk, I am going to give an overview of various techniques to analyze contact processes and their nonlinear dynamics with a focus on moment-based methods. The main results will be (a) the existence of periodic motion in systems with waning immunity, (b) warning signs for outbreaks in adaptive epidemic models with social distancing and quarantining, (c) the influence of transport in multiplex networks, and (d) the influence of multiscale group interactions to prevent epidemics. We shall also see how to locally justify moment closure expansions of the dynamics.