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On-Line Data Processing, Simulation and Forecasting of the Coronavirus Disease (COVID-19) Propagation in Ukraine Based on Machine Learning Approach

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Data Stream Mining & Processing (DSMP 2020)

Abstract

The article analyzes the epidemic process of a new coronavirus infection. The influence of COVID-19 on society, education, healthcare and other areas is analyzed. The analysis of restrictive measures that are implemented in different countries is carried out. Based on machine learning methods, a model for the spread of the incidence of COVID-19 has been developed. The forecast of incidence in Ukraine is calculated. The accuracy of the forecast is 97.6%. For automatic calculation of predicted morbidity, a web service has been developed for processing data in real time. The developed model enables to conduct prospective monitoring of the epidemic situation, redistribute limited resources between different regions of the country that need them more at the forecast time, introduce new control methods or, on the contrary, weaken restrictive measures, and adjust measures depending on the forecast situation on the simulated territory.

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Chumachenko, D., Chumachenko, T., Meniailov, I., Pyrohov, P., Kuzin, I., Rodyna, R. (2020). On-Line Data Processing, Simulation and Forecasting of the Coronavirus Disease (COVID-19) Propagation in Ukraine Based on Machine Learning Approach. In: Babichev, S., Peleshko, D., Vynokurova, O. (eds) Data Stream Mining & Processing. DSMP 2020. Communications in Computer and Information Science, vol 1158. Springer, Cham. https://doi.org/10.1007/978-3-030-61656-4_25

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  • DOI: https://doi.org/10.1007/978-3-030-61656-4_25

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