Forecasting of COVID-19 incidence in Ukraine using the method of exponential smoothing.
| Autor: | Malysh N; Department of Infectious Diseases with Epidemiology, Sumy State University, Rymskogo-Korsakova 2, Sumy, Ukraine. malysh.ng@gmail.com., Podavalenko A; Department of Hygiene, Epidemiology and Occupational Diseases, Kharkiv Medical Academy of Postgraduate Education, Amosova, 58, Kharkiv, Ukraine., Kuzmenko O; Department of Economic Cybernetics, Sumy State University, Rymskogo-Korsakova 2, Sumy, Ukraine., Kolomiets S; Department of Economic Cybernetics, Sumy State University, Rymskogo-Korsakova 2, Sumy, Ukraine. |
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| Jazyk: | angličtina |
| Zdroj: | Folia medica Cracoviensia [Folia Med Cracov] 2022 Jun 29; Vol. 62 (1), pp. 103-120. |
| DOI: | 10.24425/fmc.2022.141694 |
| Abstrakt: | Coronavirus infection (COVID-19) is a highly infectious disease of viral etiology. SARS-CoV-2 virus was first identified during the investigation of the outbreak of respiratory disease in Wuhan, China in December 2019. And already on March 11, 2020 COVID-19 in the world was characterized by the WHO as a pandemic. In Ukraine the situation with incidence COVID-19 remains difficult. The purpose of this study is to to develop a mathematical forecasting model for COVID-19 incidence in Ukraine using an exponential smoothing method. The article analyzes reports on basic COVID-19 incidence rates from 29.02.2019 to 01.10.2021. In order to determine the forecast levels of statistical indicators that characterize the epidemic process of COVID-19 the method of exponential smoothing was used. It is expected that from 29.02.2019 to 01.10.2021 the epidemic situation of COVID-19 incidence will stabilize. The indicator of "active patients" will range from 159.04 to 353.63 per 100 thousand people. The indicator of "hospitalized patients" can reach 15.43 and "fatalities" ‒ 1.87. The use of the method of exponential smoothing based on time series models for modeling the dynamics of COVID-19 incidence allows to develop and implement scientifically sound methods in order to prevent, quickly prepare health care institutions for hospitalization. |
| Databáze: | MEDLINE |
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