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The article highlights the use of high-performance computing technologies and the capabilities of advanced supercomputers to predict, prevent and reduce losses from epidemics that generate pandemic events. The advantages of the agent approach for modeling large-scale epidemic spreading scenarios in heterogeneous populations at a detailed level are identified. The architecture of agent-based models of epidemics are considered, as well as the key aims that have to be solved in distributed modeling of epidemic processes. The software for the design and technical implementation of large-scale agent-based epidemic models on high-performance clusters and supercomputers are listed. Examples of using optimization algorithms to increase the performance of large-scale agent-based epidemic models are discussed.

Large-scale Agent-Based Epidemic Models and Their Technical Implementation on Supercomputers