Speaker: Dr. Moysey Brio, University of Arizona
Title: A Coupled Spatial-Network Model for Epidemiology
Abstract: There is extensive evidence that network structure (e.g. air transport, rivers, or roads) may significantly enhance the spread of epidemics into the surrounding geographical area, yet models coupling a network structure with a 2D area have largely not been studied. We present our work on coupling the Susceptible-Infected-Removed (SIR) system of differential equations at the population centers, with 1D-travel routes, and a 2D continuum containing the bulk of the population. We describe numerical discretization utilizing finite difference and finite element methods. Numerical examples of the impact of the network structure on the spread of an epidemic, localized solutions and comparison of various edge centrality measures for metric graphs are discussed.
Biography: Moysey Brio is Professor of Mathematics at the University of Arizona, specializing in numerical algorithms for partial differential equations (PDEs). He received his PhD in 1984 from UCLA, and held research fellowships at UCLA, Rice University, NYU, IMPA (Brazil), DTU (Denmark), and INSA de Rouen (France). Besides his recent involvement with the topic of modeling partial differential equations (PDEs), he has extensive research experience in designing novel numerical algorithms with applications to aerospace, optics, and astrophysics, as well as developing algorithms for numerical inversion of the Laplace transform. He is an author of a graduate level textbook, “Numerical Time-Dependent Partial Differential Equations for Scientists and Engineers.”
The faculty host of this speaker is Dr. Hannah Kravitz