A COMBINATORIAL MATHEMATICAL MODEL OF THE DYNAMICS OF THE INCIDENCE OF COVID-19 ON THE EXAMPLE OF THE SITUATION IN THE UKRAINE
DOI:
https://doi.org/10.30890/2709-2313.2024-34-00-011Keywords:
acute respiratory viral infection, morbidity dynamics, prognosis, mathematical modelAbstract
The authors, based on a study of a wide range of statistical data, proposed a mathematical model of the dynamics of COVID-19 and other similar infections. The proposed model aids in understanding the mechanisms of acute respiratory viral infections, theirMetrics
References
Виленкин Н.Я. Комбинаторика [Текст]. –М.: Наука, 1969. — 328 с.
Johns Hopkins Center For System Science and Engineering: COVID-19 Unified Dataset [Інтернет ресурс]. https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series.
Эпидемии в свете чисел (Л. А. Рвачев, доктор физико-математических наук) [Інтернет ресурс]. http://mathemlib.ru/books/item/f00/s00/z0000015/st007.shtm.
Горобец В.Л. Прогнозирование динамических процессов путем идентификации параметров линейной системы/ В.Л. Горобец, О.Л. Зиненко А.Л. Чирков // Вестник Восточноукраинского национального университета им. В. Даля. - № 1(143). –2010. – С. 60-67.
Иванников Ю. Г. Опыт математического компьютерного прогнозирования эпидемий гриппа для больших территорий [Текст] /Ю. Г. Иванников, П. И. Огарков/ Журнал инфектологии: Том 4. – С.-Пб. 2012 – № 3. – С. 101,106.
Математическое моделирование и прогнозирование COVID-19 в Москве и Новосибирской области/ Криворотько О.И., Кабанихин С.И., Зятьков Н.Ю., Приходько А.Ю., Прохошин Н.М., Шишленин М.А.//Сиб. журн. вычисл. матем.:том 23. – 2020. – № 4. С. 395–414.
N.B. Noll, I. Aksamentov, V. Druelle, A. Badenhorst, B. Ronzani, G. Jefferies, J.Albert, R. Neher. COVID-19 Scenarios: an interactive tool to explore the spread and associated morbidity and mortality of SARS-CoV-2. 2020. medRxiv 2020.05.05.20091363. DOI: 10.1101/2020.05.05.20091363.
E.M. Koltsova, E.S. Kurkina, A.M. Vasetsky. Mathematical Modeling of the Spread of COVID-19 in Moscow and Russian Regions. 2020. arXiv: 2004.10118 [q-bio.PE].
A. Zlojutro, D. Rey, L. Gardner. Optimizing border control policies for global out-break mitigation. Scientific Reports. 2019. Vol. 9. P. 2216. https://rdcu.be/bniOs.
Y. Chen, J. Cheng, Y. Jiang and K. Liu. A time delay dynamical model for outbreak of 2019-nCoV and the parameter identification. Journal of Inverse and Ill-posed Problems. 2020. Vol. 28, Issue 2. P. 243–250.
B. Tang, X. Wang, Q. Li, N.L. Bragazzi, S. Tang, Y. Xiao, J. Wu. Estimation of the transmission risk of 2019-nCoV and its implication for public health interventions. SSRN: https://ssrn.com/abstract=3525558.
E. Unlu, H. Leger, O. Motornyi, A. Rukubayihunga, T. Ishacian, M. Chouiten. Epidemic analysis of COVID-19 Outbreak and Counter-Measures in France. 2020. medRxiv 2020.04.27.20079962. DOI: 10.1101/2020.04.27.20079962.
Bellu G., Saccomani M.P., Audoly S., D’Angi’o L. DAISY: A new software tool to test global identifiability of biological and physiological systems. Computer Methods and Programs in Biomedicine. 2007. V. 88, no. 1. P. 52-61.
R. Sameni. Mathematical Modeling of Epidemic Diseases; A Case Study of the COVID-19 Coronavirus. arXiv:2003.11371. 2020.
Зменшимо сприйнятливість до COVID та грипу!: YouTube channel. https://www.youtube.com/watch? v=-M3jPw1j7BE.
Reduce susceptibility to COVID and influenza! YouTube channel https://www.youtube.com/watch?v=3odogM0tD6k.
Al-arydah Mo'tassem. Mathematical modeling of the spread of the coronavirus under strict social restrictions/Mo'tassem Al-arydah, Hailay Berhe, Khalid Dib. Kalyanasundaram Madhu. https://onlinelibrary.wiley.com/doi/10.1002/mma.7965/
Hyun Mo Yang. Mathematical modeling of the transmission of SARS-CoV-2 – d Evaluating the impact of isolation in São Paulo State (Brazil) and lockdown in Spain associated with protective measures on the epidemic of CoViD-19/Hyun Mo Yang, Luis Pedro Lombardi Junior, Fábio Fernandes Morato Castro, Ariana Campos Yang. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252271.
Li Hui-Jia. Editorial: Mathematical Modelling of the Pandemic of 2019 Novel Coronavirus (COVID-19): Patterns, Dynamics, Prediction, and Control DOI=10.3389/fphy.2021.738602/ Hui-Jia Li, Lin Wang, Zhen Wang, Zhanwei Du, Chengyi Xia, Aristides Moustakas, Sen .Pei.
A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia https://advancesindifferenceequations.springeropen.com/articles/10.1186/s13662-021-03410-z
Zeb Anwar. Mathematical Model for Coronavirus Disease 2019 (COVID-19) Containing Isolation Class/ Anwar Zeb, Ebraheem Alzahrani, Vedat Suat Erturk, Gul Zaman. https://www.hindawi.com/journals/bmri/2020/3452402/
Ivorra B. Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China. // B. Ivorra, M.R. Ferrбndez , M. Vela-Pйrez, A.M. Ramos, ∗Ivorra B, Ferrández MR, Vela-Pérez M, Ramos AM.Commun Nonlinear Sci Numer Simul. 2020;88:105303. doi: 10.1016/j.cnsns.2020.105303https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190554/
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