Utilizza questo identificativo per citare o creare un link a questo documento: http://elartu.tntu.edu.ua/handle/lib/36939

Titolo: The coronavirus disease COVID-19 Spreadi ng prediction in Ukraine by means of microsoft Excel
Autori: Palaniza, Yuri
Shadrina, Halyna
Khvostivskyy, Mykola
Affiliation: Ternopil National Ivan Puluj Technical University, Rus’ka str. 56, 46001, Ternopil, Ukraine
Bibliographic description (Ukraine): Palaniza Y. The coronavirus disease COVID-19 Spreadi ng prediction in Ukraine by means of microsoft Excel / Yuri Palaniza, Halyna Shadrina, Mykola Khvostivskyy // ICAAEIT 2021, 15-17 December 2021. — Tern. : TNTU, Zhytomyr «Publishing house „Book-Druk“» LLC, 2021. — P. 139–144. — (Biomedical engineering).
Bibliographic description (International): Palaniza Y., Shadrina H., Khvostivskyy M. (2021) The coronavirus disease COVID-19 Spreadi ng prediction in Ukraine by means of microsoft Excel. ICAAEIT 2021 (Tern., 15-17 December 2021), pp. 139-144.
Is part of: Proceedings of the International Conference „Advanced applied energy and information technologies 2021”, 2021
Data: 15-dic-2021
Date of entry: 28-dic-2021
Editore: TNTU, Zhytomyr «Publishing house „Book-Druk“» LLC
Place of the edition/event: Ternopil
Temporal Coverage: 15-17 December 2021
Parole chiave: SARS-CoV-2
COVID-19
Microsoft Excel
Software
SIR Model
GRG Nonlinear solving method
Number of pages: 6
Page range: 139-144
Start page: 139
End page: 144
Abstract: COVID-19 has completely eclipsed the morbidity, mortality, and economic impact of any other seasonal flu or communicable disease in the past century, and it is vitally important to have means that make it possible to predict its spreading. Analysis of the situation regarding the course of COVID-19 as well as diagrams of the future pandemic emphasizes their ability to change the configuration and behavior, which requires a rapid response to these changes. In view of this, an important factor is the efficiency and the need to develop a simple model, suitable for understanding even by non-specialists and with the possibility of use in the "field". Based on the Excel-project of the North-Western University, a system of automatic identification of the SIR-model (Susceptible, Infectious, Recovered) of COVID-19 was developed.
URI: http://elartu.tntu.edu.ua/handle/lib/36939
ISBN: 978-617-8079-60-4
Copyright owner: © Ternopil Ivan Puluj National Technical University, Ukraine, 2021
URL for reference material: https://www.worldometers.info/coronavirus/coronavirus-cases/#case-tot-outchina
https://www.worldometers.info/coronavirus/country/ukraine/
References (International): 1. Coronavirus Cases. Total Cases (worldwide) [online cit.: 2020-04-07]. Retrieved from: https://www.worldometers.info/coronavirus/coronavirus-cases/#case-tot-outchina
2. Tatskov, O.O., Palaniza, Yu.B. (2020). The problem of predicting the spread of coronavirus COVID-19 in the world by people without special skills and without the use of specialized software on a personal computer with the operating system MICROSOFT WINDOWS. Natural Sciences and Humanities. Topical issues, Proceedings of the III International Student Scientific and Technical Conference. Ternopil, Ukraine.
3. Coronavirus Cases. Total Cases (Ukraine) [online cit.: 2021-04-21]. Retrieved from: https://www.worldometers.info/coronavirus/country/ukraine/
4. Suba, M. Current Mathematical Models and Numerical Simulation of SIR Model for Coronavirus Disease-2019 (COVID-19). European Journal of Molecular & Clinical Medicine 7.05 (2020): 41-54.
Content type: Conference Abstract
È visualizzato nelle collezioni:International conference „Advanced Applied Energy and Information Technologies 2021“, (ICAAEIT 2021)



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