Speakers
Description
Understanding infectious disease dynamics increasingly requires models that can capture forms of heterogeneity which are invisible to standard population-level compartmental frameworks. Real-world data reveal substantial variation across individuals and groups (e.g., in terms of spatial distribution, age structure, viral-load trajectories, contact patterns, risk exposure, and behavioural responses) that cannot be adequately represented by homogeneous models.
This minisymposium aims to explore the role and impact of such heterogeneities on epidemic spread, and how they can be incorporated through mathematically rigorous modelling approaches. These include network-based ODE models, renewal equations, and continuously structured systems such as PDEs or integro-differential equations. We are interested both in theoretical insights arising from these models and in methodologies that allow heterogeneous structures to be inferred from, or compared to, data.
Given the diverse audience of ECMTB, ranging from theoretical mathematicians to researchers working closely with real-world datasets, our session aims at bridging rigorous theoretical insight from mathematical modelling with data-driven perspectives, fostering dialogue between experts from heterogeneous backgrounds.
