act with each other. As has been generally observed in the field of complexity studies, remarkably complex behaviors can emerge at a group level from very simple rules governing interagent behaviors. Indeed, Wolfram (2002) suggested that one simple variety of agent-based computational models, termed cellular automata (immobile, identical, grid-based agents), can be used to model all manner of complex scientific phenomena. To date, agent-based models have been used primarily in social and economic modeling. Epstein and Axtell (1996) made an early seminal contribution, and, more recently, a full supplement of the Proceedings of the National Academy of Sciences was devoted to agent-based modeling in the social sciences (Bankes, 2002). A few promising studies have appeared in which agent-based modeling is used to examine infectious diseases (e.g., influenza) and the immune response (Hofmeyr and Forrest, 2000). The rapid rise in freely available computational power should permit the development of a wide variety of infectious disease agent-based simulations (Swarm Development Group website).

FIGURE E-2 Visual display of a two-dimensional agent-based model. Each square represents an individually programmable, mobile agent. Color-coding allows easy visual tracking of agents with different properties.