Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine
Background. Unfortunately, the COVID-19 pandemic is still far from stabilizing. Of particular concern is the sharp increase in the number of diseases in June-July, September-October 2020 and February-March 2021. The causes and consequences of this sharp increase in the number of cases are still wait...
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2021
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oai:doaj.org-article:357b1d1dd1d840e7af6f5a4216f08d0d2021-12-05T14:10:44ZDetections and SIR simulations of the COVID-19 pandemic waves in Ukraine2544-729710.1515/cmb-2020-0117https://doaj.org/article/357b1d1dd1d840e7af6f5a4216f08d0d2021-07-01T00:00:00Zhttps://doi.org/10.1515/cmb-2020-0117https://doaj.org/toc/2544-7297Background. Unfortunately, the COVID-19 pandemic is still far from stabilizing. Of particular concern is the sharp increase in the number of diseases in June-July, September-October 2020 and February-March 2021. The causes and consequences of this sharp increase in the number of cases are still waiting for their researchers, but there is already an urgent need to assess the possible duration of the pandemic, the expected number of patients and deaths. Correct simulation of the infectious disease dynamics needs complicated mathematical models and many efforts for unknown parameters identification. Constant changes in the pandemic conditions (in particular, the peculiarities of quarantine and its violation, situations with testing and isolation of patients) cause various epidemic waves, lead to changes in the parameter values of the mathematical models.Nesteruk IgorDe Gruyterarticlecovid-19 pandemiccovid-19 epidemic in ukrainemathematical modeling of infection diseasessir modelparameter identificationstatistical methods34a3462j0592c60BiotechnologyTP248.13-248.65PhysicsQC1-999ENComputational and Mathematical Biophysics, Vol 9, Iss 1, Pp 46-65 (2021) |
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covid-19 pandemic covid-19 epidemic in ukraine mathematical modeling of infection diseases sir model parameter identification statistical methods 34a34 62j05 92c60 Biotechnology TP248.13-248.65 Physics QC1-999 |
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covid-19 pandemic covid-19 epidemic in ukraine mathematical modeling of infection diseases sir model parameter identification statistical methods 34a34 62j05 92c60 Biotechnology TP248.13-248.65 Physics QC1-999 Nesteruk Igor Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine |
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Background. Unfortunately, the COVID-19 pandemic is still far from stabilizing. Of particular concern is the sharp increase in the number of diseases in June-July, September-October 2020 and February-March 2021. The causes and consequences of this sharp increase in the number of cases are still waiting for their researchers, but there is already an urgent need to assess the possible duration of the pandemic, the expected number of patients and deaths. Correct simulation of the infectious disease dynamics needs complicated mathematical models and many efforts for unknown parameters identification. Constant changes in the pandemic conditions (in particular, the peculiarities of quarantine and its violation, situations with testing and isolation of patients) cause various epidemic waves, lead to changes in the parameter values of the mathematical models. |
format |
article |
author |
Nesteruk Igor |
author_facet |
Nesteruk Igor |
author_sort |
Nesteruk Igor |
title |
Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine |
title_short |
Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine |
title_full |
Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine |
title_fullStr |
Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine |
title_full_unstemmed |
Detections and SIR simulations of the COVID-19 pandemic waves in Ukraine |
title_sort |
detections and sir simulations of the covid-19 pandemic waves in ukraine |
publisher |
De Gruyter |
publishDate |
2021 |
url |
https://doaj.org/article/357b1d1dd1d840e7af6f5a4216f08d0d |
work_keys_str_mv |
AT nesterukigor detectionsandsirsimulationsofthecovid19pandemicwavesinukraine |
_version_ |
1718371782513131520 |