Results 1 to 10 of about 217,359 (118)

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

Features of developing SARS-CoV-2 nucleocapsid protein population-based seroprevalence during the first wave of the COVID-19 epidemic in the Russian Federation

Инфекция и иммунитет, 2021
The novel coronavirus (SARS-CoV-2) pandemic, dubbed COVID-19, has become one of the most serious challenges for human populations in the vast majority of countries worldwide.
A. Yu. Popova, E. E. Andreeva, E. A. Babura, S. V. Balakhonov, N. S. Bashketova, M. V. Bulanov, N. N. Valeullina, D. V. Goryaev, N. N. Detkovskaya, E. B. Ezhlova, N. N. Zaitseva, O. A. Istorik, I. V. Kovalchuk, D. N. Kozlovskikh, S. V. Kombarova, O. P. Kurganova, V. V. Kutyrev, A. E. Lomovtsev, L. A. Lukicheva, L. V. Lyalina, A. A. Melnikova, O. M. Mikailova, A. K. Noskov, L. N. Noskova, E. E. Oglezneva, T. P. Osmolovskay, M. A. Patyashina, N. A. Penkovskaya, L. V. Samoilova, V. S. Smirnov, T. F. Stepanova, O. E. Trotsenko, Areg A. Totolyan   +32 more
doaj   +1 more source

Assessment of the COVID-19 epidemiological situation in St. Petersburg

Журнал микробиологии, эпидемиологии и иммунобиологии, 2021
Aim. Identification of epidemiological patterns of the SARS-CoV-2 spread among the population of St. Petersburg during the one-year COVID-19 pandemic period.Materials and methods.
V. G. Akimkin, S. N. Kuzin, E. N. Kolosovskaya, E. N. Kudryavtceva, T. A. Semenenko, A. A. Ploskireva, D. V. Dubodelov, E. V. Tivanova, N. Yu. Pshenichnaya, A. V. Kalenskaya, S. V. Yatcishina, O. Yu. Shipulina, E. N. Rodionova, N. S. Petrova, I. V. Solov'eva, O. A. Kvasova, M. A. Vershinina, M. V. Mamoshina, V. V. Klushkina, M. I. Korabel'nikova, N. S. Churilova, Ya. V. Panasyuk, N. V. Vlasenko, A. A. Ostroushko, E. S. Balmasov, A. V. Mosunov   +25 more
doaj   +1 more source

Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies

Computation, 2022
In the current study, we define a hierarchical epidemic model that helps to describe the propagation of a pathogen in a clustered human population. The estimation of a novel coronavirus spreading worldwide leads to the idea of the hierarchical structure ...
Elena Gubar, Vladislav Taynitskiy, Denis Fedyanin, Ilya Petrov   +3 more
doaj   +1 more source

Cholera: Trends in the Development of the Epidemic Process in 2021, Forecast for 2022

Проблемы особо опасных инфекций, 2022
The aim of the work was to summarize the results of cholera monitoring in 2021, to assess current trends in the development of the epidemic process, and to predict the epidemiological situation in the Russian Federation for 2022.
A. K. Noskov, V. D. Kruglikov, E. A. Moskvitina, E. V. Monakhova, L. V. Mironova, А. A. Kritsky, A. A. Lopatin, O. S. Chemisova, E. G. Soboleva, S. M. Ivanova, A. S. Vodop’yanov, S. I. Stenina, R. V. Pisanov, D. A. Levchenko, O. A. Podoinitsyna, N. B. Nepomnyashchaya, M. I. Ezhova   +16 more
doaj   +1 more source

Cholera: Analysis and Assessment of Epidemiological Situation around the World and in Russia (2013–2022). Forecast for 2023

Проблемы особо опасных инфекций, 2023
The aim of the review was to analyze and assess the epidemiological situation on cholera in the world and Russia in 2013–2022 and to make a forecast for 2023.
A. K. Noskov, V. D. Kruglikov, E. A. Moskvitina, L. V. Mironova, E. V. Monakhova, E. G. Soboleva, O. S. Chemisova, A. S. Vodop’yanov, A. A. Lopatin, S. M. Ivanova, E. A. Men’shikova, O. A. Podoynitsyna, M. I. Ezhova, A. V. Evteev   +13 more
doaj   +1 more source

Features of the epidemic process and epidemic risks of COVID-19 in the subjects of the Northern Caucasus

Эпидемиология и вакцинопрофилактика, 2023
Relevance. The peculiarities of the course of the COVID-19 epidemic process in the regions of the world, as a rule, are determined by the epidemic risks characteristic of them.
V. V. Makhova, O. V. Maletskaya, A. N. Kulichenko   +2 more
doaj   +1 more source

Predicting the dynamics of Covid-19 incidence and planning preventive vaccination measures for Moscow population based on mathematical modeling

Журнал микробиологии, эпидемиологии и иммунобиологии, 2020
The results of the predictive analytical studies on Covid-19 incidence dynamics in Moscow, taking into account different changes in epidemic prevention measures, including vaccination coverage of the population, are presented.Research Objective.
Мarina N. Asatryan, Elita R. Gerasimuk, Denis Yu. Logunov, Tatyana A. Semenenko, Aleksander L. Gintsburg   +4 more
doaj   +1 more source

Assessing of Humoral Immunity to SARS-COV-2 in Residents of Orenburg During the Epidemic Period

Эпидемиология и вакцинопрофилактика, 2022
Relevance. The formation of humoral immunity is one of the most important manifestations of the protective mechanism against an infectious disease.
A. S. Pankov, S. Yu. Nosyreva, I. F. Karimov, A. G. Korneev, S. D. Borisov   +4 more
doaj   +1 more source