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oai:munzur-rdlopen.rawdatalibrary.net:munzur/20452026-10-28T15:29:22Zopenairedrivercom_munzur_1col_munzur_2com_munzur_8col_munzur_154

Spread patterns of COVID-19 in European countries: hybrid deep learning model for prediction and transmission analysisUtku, AnılAkcayol, M. AliCOVID-19Deep learningEuropean countriesMachine learningThe COVID-19 pandemic has profoundly impacted healthcare systems and economies worldwide, leading to the implementation of travel restrictions and social measures. Efforts such as vaccination campaigns, testing, and surveillance have played a crucial role in containing the spread of the virus and safeguarding public health. There needs to be more research exploring the transmission dynamics of COVID-19, particularly within European nations. Therefore, the primary objective of this research was to examine the spread patterns of COVID-19 across various European countries. Doing so makes it possible to implement preventive measures, allocate resources, and optimize treatment strategies based on projected case and mortality rates. For this purpose, a hybrid prediction model combining CNN and LSTM models was developed. The performance of this hybrid model was compared against several other models, including CNN, k-NN, LR, LSTM, MLP, RF, SVM, and XGBoost. The empirical findings revealed that the CNN-LSTM hybrid model exhibited superior performance compared to alternative models in effectively predicting the transmission of COVID-19 within European nations. Furthermore, examining the peak of case and death dates provided insights into the dynamics of COVID-19 transmission among European countries. Chord diagrams were drawn to analyze the inter-country transmission patterns of COVID-19 over 5-day and 14-day intervals.Springer Science and Business Media Deutschland GmbH2024Articlehttps://rdlopen.rawdatalibrary.net/r/munzur/2045https://doi.org/10.1007/s00521-024-09597-y0941-0643enNeural Computing and Applicationsinfo:eu-repo/semantics/openAccessinfo:eu-repo/semantics/articlehttps://munzur-rdlopen.rawdatalibrary.net/tr/items/munzur/2045