Scalable, efficient epidemiological simulation
Proceedings of the 2002 ACM symposium on Applied computing
Spatial Models of Persistence in RNA Worlds: Exploring the Origins of Life
PPAM '01 Proceedings of the th International Conference on Parallel Processing and Applied Mathematics-Revised Papers
Stochastic Simulation of a Marine Host-Parasite System Using a Hybrid MPI/OpenMP Programming
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Parallel simulation of the global epidemiology of Avian influenza
Proceedings of the 40th Conference on Winter Simulation
Applications of multilevel cellular automata in epidemiology
ACMOS'11 Proceedings of the 13th WSEAS international conference on Automatic control, modelling & simulation
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This paper describes a series of stepwise refinements of a biological model resulting in a high-performance simulation system for models of the coevolutionary dynamics of epidemic processes. Our model includes two competing host species, a macroparasite capable of serving as a vector, and the vector-borne microparasite. Genetic algorithms are used to simulate genetic change; we are particularly interested in the evolution of pathogen virulence. The simulation system employs cellular automata to track individual organisms distributed over a two-dimensional lattice. We present a series of experiments that demonstrate how individual-based modeling and explicit representation of space, although computationally expensive, can produce qualitatively new biological results.