Related Experiment Video
Updated: Jun 11, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
A Coupled Spatial-Network Model: A Mathematical Framework for Applications in Epidemiology
Hannah Kravitz1, Christina Durón2, Moysey Brio3
1Fariborz Maseeh Department of Mathematics and Statistics, Portland State University, 1825 SW Broadway, Portland, OR, 97201, USA. hkravitz@pdx.edu.
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. A new compartmental modeling framework is proposed which couples well-mixed (ODE in time) population centers at the vertices, 1D travel routes on the graph's edges, and a 2D continuum containing the rest of the population to simulate how an infection spreads through a population. The edge equations are coupled to the vertex ODEs through junction conditions, while the domain equations are coupled to the edges through boundary conditions. A numerical method based on spatial finite differences for the edges and finite elements in the 2D domain is described to approximate the model, and numerical verification of the method is provided. The model is illustrated on two simple and one complex example geometries, and a parameter study example is performed. The observed solutions exhibit exponential decay after a certain time has passed, and the cumulative infected population over the vertices, edges, and domain tends to a constant in time but varying in space, i.e., a steady state solution.
Related Concept Videos
Steps in Outbreak Investigation
Statistical Software for Data Analysis and Clinical Trials
Mechanistic Models: Compartment Models in Individual and Population Analysis
Causality in Epidemiology
Selected Data About Geographic Locations
Applications of GIS: Disaster Management and Emergency Response

