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arXiv · 2010.02540

Low Complexity Method for Simulation of Epidemics Based on Dijkstra's Algorithm

Davide Zorzenon·Fabio Molinari·Joerg Raisch
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Abstract

Models of epidemics over networks have become popular, as they describe the impact of individual behavior on infection spread. However, they come with high computational complexity, which constitutes a problem in case large-scale scenarios are considered. This paper presents a discrete-time multi-agent SIR (Susceptible, Infected, Recovered) model that extends known results in literature. Based on that, using the novel notion of Contagion Graph, it proposes a graphbased method derived from Dijkstra's algorithm that allows to decrease the computational complexity of a simulation. The Contagion Graph can be also employed as an approximation scheme describing the "mean behavior" of an epidemic over a network and requiring low computational power. Theoretical findings are confirmed by randomized large-scale simulation.

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Davide Zorzenon, Fabio Molinari, Joerg Raisch. 2021-03-04. Low Complexity Method for Simulation of Epidemics Based on Dijkstra's Algorithm. https://doi.org/10.23919/acc50511.2021.9483311

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