Accelerated Epidemic Simulation in Large-Scale Networks: Optimization of the Gillespie Algorithm and a Two-Layer Approach
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Date
2025
Authors
Kuryliak, Yulian
Emmerich, Michael
Journal Title
Journal ISSN
Volume Title
Publisher
Національний університет "Києво-Могилянська академія"
Abstract
This study addresses the challenge of accelerating epidemic simulations in large-scale complex networks through algorithmic and structural optimization. Traditional Gillespie-based stochastic simulations accurately reproduce epidemic dynamics but become computationally prohibitive for networks exceeding tens of thousands of nodes. To overcome this limitation, we build upon such efficiency techniques as local rate updates and ordered event-selection structures, which reduce the computational complexity of each simulation step from O(n) to O(log(n)). Building on these principles, we propose a two-layer (micro–macro) modeling framework: the micro layer simulates intra-community dynamics, while the macro layer captures inter-community infections using hazard-integral rates derived from mobility data and the epidemic states of metanodes. This hierarchical approach enables scalable and parallelizable simulations that preserve stochastic accuracy while substantially reducing computational cost, allowing realistic modeling of epidemic spread across millions of agents and multiple cities.
Description
Keywords
Gillespie algorithm, Stochastic simulation, Continuous-Time Markov Chains (CTMC), Agent-based modeling, conference materials
Citation
Kuryliak Y. Accelerated Epidemic Simulation in Large-Scale Networks: Optimization of the Gillespie Algorithm and a Two-Layer Approach / Kuryliak Y. A., Emmerich M. T. M. // Теоретичні та прикладні аспекти побудови програмних систем : праці 16 Міжнародної науково-практичної конференції, 23-24 листопада 2025 року, Київ / [за заг. ред. М. М. Глибовця, Т. В. Панченка та ін. ; Факультет інформатики Національного університету "Києво-Могилянська академія" та ін.]. - Київ : НаУКМА, 2025. - С. 61-63.