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Investigation of Statistical Machine Learning Models for COVID-19 Epidemic Process Simulation: Random Forest, K-Nearest Neighbors, Gradient Boosting

Computation, 2022
COVID-19 has become the largest pandemic in recent history to sweep the world. This study is devoted to developing and investigating three models of the COVID-19 epidemic process based on statistical machine learning and the evaluation of the results of ...
Dmytro Chumachenko, Ievgen Meniailov, Kseniia Bazilevych, Tetyana Chumachenko, Sergey Yakovlev   +4 more
doaj   +3 more sources

On intelligent agent-based simulation of COVID-19 epidemic process in Ukraine. [PDF]

Procedia Comput Sci, 2022
Chumachenko D, Meniailov I, Bazilevych K, Chumachenko T, Yakovlev S.   +4 more
europepmc   +2 more sources

Similarities and Differences in the Manifestations of the COVID-19 Epidemic Process in Some Countries

Эпидемиология и вакцинопрофилактика, 2023
Relevance. The pandemic of a new coronavirus infection has become an unprecedented challenge for modern society. It took the entire population of the Earth by surprise, changing the lives of millions of people in the world in record time.
O. P. Chernyavskaya, D. V. Kolodina, T. R. Belova   +2 more
doaj   +1 more source

On the Role of Global and Regional Factors in the Development of the Epidemic Process of Anthroponotic Infections

Эпидемиология и вакцинопрофилактика, 2021
Relevance. In the modern period, scientific works that would give a detailed assessment of the influence of certain factors on the development of the epidemic process are extremely rare.
A. A. Yakovlev
doaj   +1 more source

Information system for assessing the informativeness of an epidemic process features

Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2023
The primary objective of this study is to assess the informativeness of various parameters influencing epidemic processes utilizing the Shannon and Kullback–Leibler methods.
Kseniia Bazilevych, Olena Kyrylenko, Yurii Parfenyuk, Sergiy Yakovlev, Serhii Krivtsov, Ievgen Meniailov, Victoriya Kuznietcova, Dmytro Chumachenko   +7 more
doaj   +1 more source

Specific Features of the Spread of New Coronavirus Infection (COVID 19) in Orenburg Region

Эпидемиология и вакцинопрофилактика, 2021
Relevance. They did not learn completely the information of the distribution of morbidity by territory and population sex-age groups in the context of a pandemic of a new coronavirus infection (COVID-19).Aims.
A. S. Pankov, A. G. Korneev, S. Yu. Nosyreva   +2 more
doaj   +1 more source

MPC Controllers in SIIR Epidemic Models

Computation, 2023
Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of ...
Nikita Kosyanov, Elena Gubar, Vladislav Taynitskiy   +2 more
doaj   +1 more source

Characteristics of self-regulation of the epidemic process of infection caused by the Epstein–Barr virus (Herpesviridae: Lymphocryptovirus, HHV-4)

Вопросы вирусологии, 2023
Introduction. Among the available scientific literature, there are no publications addressing processes of self-regulation in the parasite-host population systems with reference to chronic infections, including the infection caused by the EpsteinBarr ...
Tatyana V. Solomay, Tatiana A. Semenenko, Vasiliy G. Akimkin   +2 more
doaj   +1 more source

EPIDEMIC RISE IN THE INCIDENCE OF INFLUENZA IN ST. PETERSBURG IN 2016

Инфекция и иммунитет, 2017
Inf luenza and acute respiratory viral infections (ARVI) account for up to 90% of the total reported infectious morbidity annually in Russia. The economic damage from these infections reaches 86% of the economic losses associated with infectious diseases.
N. S. Bashketova, I. G. Chkyhindzheriya, M. A. Bichurina, T. I. Krainova, E. A. Bryanceva, I. N. Lavrentieva, L. P. Suhobaevskaya, O. V. Degtjarev, T. E. Demakova   +8 more
doaj   +1 more source

COVID-19: evolution of the pandemic in Russia. Report II: dynamics of the circulation of SARS-CoV-2 genetic variants

Журнал микробиологии, эпидемиологии и иммунобиологии, 2022
Background. The ongoing pandemic of the novel coronavirus infection (COVID-19) draws attention to the significance of molecular and genetic monitoring of the SARS-CoV-2 spread among the population of the Russian Federation.
Vasily G. Akimkin, Anna Yu. Popova, Kamil F. Khafizov, Dmitry V. Dubodelov, Svetlana V. Ugleva, Tatyana A. Semenenko, Antonina A. Ploskireva, Alexander V. Gorelov, Natalia Yu. Pshenichnaya, Elena B. Yezhlova, Alexander N. Letyushev, Yulia V. Demina, Vladimir V. Kutyrev, Rinat A. Maksyutov, Vadim M. Govorun, Ivan A. Dyatlov, Areg A. Totolian, Alexandr N. Kulichenko, Sergey V. Balakhonov, Nikolay V. Rudakov, Olga E. Trotsenko, Alexey K. Noskov, Natalia N. Zaitseva, Andrey V. Toporkov, Dmitry A. Lioznov, Elena E. Andreeva, Olga M. Mikailova, Andrey G. Komarov, Vasily Yu. Ananyev, Vladimir V. Moldovanov, Denis Yu. Logunov, Vladimir A. Gushchin, Vladimir G. Dedkov, Anna S. Cherkashina, Stanislav N. Kuzin, Elena V. Tivanova, Larisa Yu. Kondrasheva, Valeria V. Saenko, Semyon Yu. Selezov, Gasan A. Gasanov, Nino Kh. Svanadze, Maxim B. Glazov, Aleksey A. Ostroushko, Konstantin O. Mironov, Anna S. Esman, Natalia A. Osina, Sergei A. Bodnev, Andrey B. Komissarov, Daria М. Danilenko, Aleksandr G. Bogun, Yuriy P. Skryabin, Kristina V. Lopatovskaya, Sergey V. Shtrek, Anna S. Volynkina, Anna S. Gladkikh, Valeria О. Kotova, Alexey S. Vodopyanov, Nadezhda A. Novikova, Anna S. Speranskaya, Andrey E. Samojlov, Alexey D. Neverov, Ivan M. Shpak   +61 more
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