Nataša Djurdjevac Conrad, Martin Weiser, Sarah Wolf, Edda Klipp
Jan-Hendrik Niemann (FU Berlin), Björn Goldenbogen (HU Berlin)
01.01.2022 – 31.12.2023
FU Berlin, HU Berlin
Agent-based epidemiological models such as the geospatially referenced demographic ABM (GERDA) can simulate and forecast infection spreading in much detail and, if parametrized correctly, with high accuracy. They incur, however, a huge computational effort and a large set of uncertain parameters. We develop multilevel representations of ABMs using network-based coarsening and model identification techniques in order to improve the understanding of pattern formation and to accelerate parameter identification and policy optimization.
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