Discrete and Continuum Models for the Spread of Infectious Diseases
(James Mac Hyman, Los Alamos National Laboratory)

I will describe a flexible, stochastic agent-based decision simulation model for understanding the spread of a disease within a major city and compare it with a class of deterministic differential equation models.   Although the agent-based model can include far more detail than the differential equation model, we have fewer analysis tools to understand the underlying dynamics in the detailed simulation.   I will describe an approach to define a simple differential equation model that captures the average course of an epidemic as defined by an agent-based model of a million people and over ten thousand locations.   The differential equation model uses the same parameters and  initial conditions as the agent based model, and then can be analyzed directly to predict the course of the epidemic in the more complex agent based model.