Abstract
Multi-agent based systems offer the possibility to examine the effects of policies down to specific target groups while also considering the effects on a population-level scale. To examine the impact of different schooling strategies, an agent-based model is used in the context of the COVID-19 pandemic using a German city as an example. The simulation experiments show that reducing the class size by rotating weekly between in-person classes and online schooling is effective at preventing infections while driving up the detection rate among children through testing during weeks of in-person attendance. While open schools lead to higher infection rates, a surprising result of this study is that school rotation is almost as effective at lowering infections among both the student population and the general population as closing schools. Due to the continued testing of attending students, the overall infections in the general population are even lower in a school rotation scenario, showcasing the potential for emergent behaviors in agent-based models.
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Acknowledgement
This model was created in the context of AScore, a consortium project funded from 01/2021 until 12/2021 within the special program “Zivile Sicherheit - Forschungsansätze zur Aufarbeitung der Corona-Pandemie” by the German Federal Ministry of Education and Research (BMBF) under grant number 13N15663.
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Tapp, L., Kurchyna, V., Nogatz, F., Berndt, J.O., Timm, I.J. (2022). School’s Out? Simulating Schooling Strategies During COVID-19. In: Melo, F.S., Fang, F. (eds) Autonomous Agents and Multiagent Systems. Best and Visionary Papers. AAMAS 2022. Lecture Notes in Computer Science(), vol 13441. Springer, Cham. https://doi.org/10.1007/978-3-031-20179-0_2
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