Modelling of Disease Spread Through Heterogeneous Population

Explore a 54-minute colloquium talk on modelling disease spread through heterogeneous populations, presented by Theodore Kolokolnikov from Dalhousie University at the Fields Institute. Delve into a simple model incorporating spatial variability in population density, leading to a novel partial differential equation with state-dependent diffusion. Discover how this model exhibits higher infection rates in densely populated areas and variable-speed infection waves. Learn about the possibility of super-diffusive propagation, where infections can "jump" across low-density areas to high-density regions. Examine a case study of coronavirus spread in Nova Scotia, showcasing density-dependent infection rates and infection jumps between population centers. Gain insights from Kolokolnikov's research, which spans pattern formation, multi-particle systems, PDEs, dynamical systems, and applications to mathematical biology and social sciences.

Modelling of disease spread through heterogeneous population