Publikation
Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study
Gerrit Großmann; Michael Backenköhler; Verena Wolf
In: Marco Gribaudo; David N. Jansen; Anne Remke (Hrsg.). Quantitative Evaluation of Systems. International Conference on Quantitative Evaluation of Systems (QEST-2020), 17th International Conference, QEST 2020, October 31 - September 1, Vienna, Austria, Pages 211-229, Vol. 12289, ISBN 9783030598549, Springer International Publishing, Switzerland, 9/2020.
Zusammenfassung
In the recent COVID-19 pandemic, computer simulations are used to predict the evolution of the virus propagation and to evaluate the prospective effectiveness of non-pharmaceutical interventions. As such, the corresponding mathematical models and their simulations are central tools to guide political decision-making. Typically, ODE-based models are considered, in which fractions of infected and healthy individuals change deterministically and continuously over time.
In this work, we translate an ODE-based COVID-19 spreading model from literature to a stochastic multi-agent system and use a contact network to mimic complex interaction structures. We observe a large dependency of the epidemic’s dynamics on the structure of the underlying contact graph, which is not adequately captured by existing ODE-models. For instance, existence of super-spreaders leads to a higher infection peak but a lower death toll …