20. Januar 2021 14:00 Uhr / Alle

Seminar: Multiskalen-Modellierung von Covid-19

Machine learning spatio-temporal epidemiological model to evaluate Germany-county-level COVID-19 risk

M2C Teaser 20.02.21

Am 20. Januar wird Lingxiao Wang vom FIAS, der nächste Sprecher in unserem Seminar über die Multiskalenmodellierung von Covid-19 sein. Er wird einen Vortrag über "Machine learning spatio-temporal epidemiological model to evaluate Germany-county-level COVID-19 risk" halten.

Weitere Informationen auf Englisch:

Time: 20.01.2022 14:00


As the COVID-19 pandemic continues to ravage the world, it is of critical importance to provide a timely risk prediction of the COVID-19 in multi-level. To implement it and evaluate the public health policy, we develop a framework with machine learning assisted to extract epidemic dynamics from the real infection maps, in which contains a county-level spatio-temporal epidemiological model that combines a spatial Cellular Automata (CA) with a temporal Susceptible-Undiagnosed-Infected-Removed (SUIR) model. Compared with the existing time risk prediction models, the proposed CA-SUIR model shows the multi-level risk of the county to the government and residents with coronavirus transmission patterns under different policies. This new toolbox is first utilized to the projection of the multi-level COVID-19 prevalence over 412 Landkreis (counties) in the Germany, including t-day-ahead risk forecast and the risk assessment to the travel restriction policy. Such intervenable evaluation system could help decide on economic restarting and public health policy making in pandemic .

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