4.7 Article

Mathematical modeling and estimation for next wave of COVID-19 in Poland

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SPRINGER
DOI: 10.1007/s00477-021-02119-5

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COVID-19; Prediction; Mathematical Modelling; Gaussian Mixture Model; Pandemics

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Researchers successfully modeled and predicted the development of the COVID-19 epidemic in Poland using a Gaussian mixture model, with high match between machine predictions and actual data, which is crucial for future medical preparedness.
We investigate the problem of mathematical modeling of new corona virus (COVID-19) in Poland and tries to predict the upcoming wave. A Gaussian mixture model is proposed to characterize the COVID-19 disease and to predict a new / future wave of COVID-19. This prediction is very much needed to prepare for medical setup and continue with the upcoming program. Specifically, data related to the new confirmed cases of COVID-19 per day are considered, and then we attempt to predict the data and statistical activity. A close match between actual data and analytical data by using the Gaussian mixture model shows that it is a suitable model to present new cases of COVID-19. In addition, it is thought that there are N waves of COVID-19 and that information for each future wave is also present in current and previous waves as well. Using this concept, predictions of a future wave can be made.

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