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Impact of Russian War on COVID-19 Dynamics in Germany: the Simulation Study by Statistical Machine Learning

  • The new coronavirus COVID-19 has been spreading worldwide for almost three years. The global community has developed effective measures to contain and control the pandemic. However, new factors are emerging that are driving the dynamics of COVID-19. One of these factors was the escalation of Russia's war in Ukraine. This study aims to test the hypothesis of the influence of migration flows caused by the Russian war in Ukraine on the dynamics of the epidemic process in Germany. For this, a model of the COVID-19 epidemic process was built based on the polynomial regression method. The model's adequacy was tested 30 days before the start of the escalation of the Russian war in Ukraine. To assess the impact of the war on the dynamics of COVID-19, the model was used to calculate the forecast of cumulative new and fatal cases of COVID-19 in Germany in the first 30 days after the start of the escalation of the Russian war in Ukraine. Modeling showed that migration flows from Ukraine are not a critical factor in the growth of the dynamics of the incidence of COVID-19 in Germany, but they influenced the number of cases. The next stage of the study is the development of more complex models for a detailed analysis of population dynamics, identifying factors influencing the epidemic process in the context of the Russian war in Ukraine, and assessing their information content.

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Metadaten
Author:Dmytro ChumachenkoORCiD, Alina NechyporenkoORCiD, Marcus FrohmeORCiDGND
URN:urn:nbn:de:kobv:526-opus4-19074
URL:https://ceur-ws.org/Vol-3302/short4.pdf
Parent Title (English):Proceedings of the 5th International Conference on Informatics & Data-Driven Medicine, Lyon, France, November 18 - 20, 2022
Publisher:RWTH Aachen
Editor:Natalia Shakhovska, Stéphane Chrétien, Ivan Izonin, Jaime Campos
Document Type:Conference Proceeding
Language:English
Year of Publication:2022
Publishing Institution:Technische Hochschule Wildau
Release Date:2024/04/12
Tag:COVID-19; epidemic model; infectious disease simulation; machine learning; polynomial regression; war
Volume:3302
First Page:78
Last Page:85
Source:Chumachenko, D., Nechyporenko, A., & Frohme, M. (2022). Impact of Russian War on COVID-19 Dynamics in Germany: the Simulation Study by Statistical Machine Learning. (N. Shakhovska, S. Chrétien, I. Izonin, & J. Campos), Proceedings of the 5th International Conference on Informatics & Data-Driven Medicine, Lyon, France, November 18 - 20, 2022. Aachen: CEUR-WS.org. Retrieved from https://ceur-ws.org/Vol-3302/short4.pdf
Faculties an central facilities:Fachbereich Ingenieur- und Naturwissenschaften
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 006 Spezielle Computerverfahren
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
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