Coronasummer in Ukraine and Austria

Nesteruk, Igor

doi:10.13140/rg.2.2.32738.56002

Cited by 12 publications

(8 citation statements)

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“…To predict the first wave of the pandemic, the classical SIR model [15-17] and the statistics-based method of its parameter identification [18] were used. To simulate new epidemic waves, a numerical method of their detection [3, 19], a generalized SIR-model [20], and a corresponding parameter identification procedure [21] were developed. In particular, eleven epidemic waves were simulated for Ukraine [4, 7-10] and five pandemic waves for the whole world [4].…”

Section: Introductionmentioning

confidence: 99%

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Final sizes and durations of new COVID-19 pandemic waves in Ukraine and around the world predicted by generalized SIR model

Nesteruk

2021

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New waves of the COVID-19 pandemic in Ukraine, which began in the summer of 2021, and after holidays in the middle of October 2021, were characterized by almost exponential growth of smoothed daily numbers of new cases. This is a matter of great concern and the need to immediately predict the epidemic dynamics in order to assess the possible maximum values of new cases, the risk of infection and the number of deaths. The generalized SIR-model and corresponding parameter identification procedure was used to simulate and predict the dynamics of two new epidemic waves in Ukraine and one in the whole world. Results of calculations show that new cases in Ukraine will not stop to appear before November 2022. If the global situation with vaccination, testing and treatment will not change, the pandemic could continue for another ten years.

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Section: Introductionmentioning

confidence: 99%

“…Since daily numbers of new cases are random and characterized by some weekly periodicity, we will use the smoothed daily number of accumulated cases: and its numerical derivative: to estimate the smoothed number of new daily cases [3, 4, 9, 19].…”

Section: Introductionmentioning

confidence: 99%

Final sizes and durations of new COVID-19 pandemic waves in Ukraine and around the world predicted by generalized SIR model

Nesteruk

2021

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“…Since the V j values are random and demonstrate some weekly periodicity, we need proper smoothing. Like the approach proposed in [18,25,26], we will use the averaged CC values (calculated with the use of the nearest 7-day figures):…”

Section: Data and Averaged CC And Dcc Valuesmentioning

confidence: 99%

Influences of seasonal and demographic factors on the COVID-19 pandemic dynamics

Nesteruk¹,

Rodionov²,

Nikitin³

et al. 2022

EAI Endorsed Transactions on Bioengineering and Bioinformatics

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INTRODUCTION:The number of COVID-19 cases per capita (accumulated (CC) and daily (DCC)) are important characteristics of the pandemic dynamics indicating the effectiveness of quarantine, testing, and vaccination. They also indicate the appearance of new waves (e.g., caused by new coronavirus strains) and may be the result of various demographic and seasonal factors. OBJECTIVES: We investigate the influence of the volume and the density of population and the urbanisation level on the CC values accumulated in European countries and regions of Ukraine at the end of June 2021 and the impact of seasonal factors on the DCC values by comparing their dynamics in the spring and summer of 2020 and 2021 for northern and southern regions. METHODS: The influence of demographic factors on CC values was investigated with the use of linear regression. Since DCC values are very random and demonstrate some weekly period, we have used the 7-days smoothing proposed before. The second year of the pandemic allows us to compare its dynamics in the spring and the summer of 2020 with the same period in 2021 and investigate the influence of seasonal factors. We have chosen some northern countries and regions: Ukraine, EU, the UK, USA and some countries located in the tropical zone and Southern Hemisphere: India, Brazil, South Africa and Argentina. The dynamics in these regions was compared with the global one. RESULTS: The accumulated number of cases per capita CC does not depend on the demographic factors used for analysis, although it may differ by about 4 times for different regions of Ukraine and more than 9 times for different European countries. The number of COVID-19 per capita registered in Ukraine is comparable with the same characteristic in other European countries but much higher than in China, South Korea and Japan. Some seasonal similarities are visible for global dynamics, EU and South Africa. Before July 2020, the southern countries demonstrated exponential growth, but northern regions showed some stabilization trends. CONCLUSION: The CC values in Europe do not show any visible dependence on the volume of population, its density and the urbanization level. More or less similar seasonal behaviour of DCC values are visible for global dynamics in July and August. Unfortunately, we cannot conclude where the quarantine restrictions were the most effective since the dynamics of the pandemic are influenced by many other factors not considered in this study, in particular, the emergence of new strains and the large number of unreported cases.

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“…The averaged daily numbers of new COVID-19 cases per capita (DCC) and deaths per capita (DDC) may indicate the effectiveness of quarantine, testing, vaccination, treatment, and also the virulence of coronavirus strains circulating in particular regions at some fixed periods of time. The DCC and DDC values can be calculated with the use of the accumulated number of cases per capita (CC) and deaths per capita (DC) and the simple smoothing procedure proposed in [1-3]. The CC and DC numbers are regularly reported by the World Health Organization, [4] and COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU), [5].…”

Section: Introductionmentioning

confidence: 99%

“…We denote these values as V j corresponding time moments t j measured in days. Similar to the approach proposed in [1-3], we will use the averaged CC and DC values which can be calculated with the use of smoothing…”

Section: Introductionmentioning

confidence: 99%

How dangerous is omicron and how effective are vaccinations?

Nesteruk

Rodionov²

2022

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The sharp increase in the number of new COVID-19 cases in late 2021 and early 2022, which is associated with the spread of a new strain of coronavirus - omicron - is of great concern and makes it necessary to make at least approximate forecasts for the pandemic dynamics of the epidemic. As this rapid growth occurs even in countries with high levels of vaccinations, the question arises as to their effectiveness. The smoothed daily number of new cases and deaths per capita and the ratio of these characteristics were used to reveal the appearance of new coronavirus strains and to estimate the effectiveness of quarantine, testing and vaccination. The third year of the pandemic allowed us to compare the pandemic dynamics in the period from September 2020 to January 2021 with the same period one year later for Ukraine, EU, the UK, USA, India, Brazil, South Africa, Argentina, Australia, and in the whole world. Record numbers of new cases registered in late 2021 and early 2022 once again proved that existing vaccines cannot prevent new infections, and vaccinated people can spread the infection as intensively as non-vaccinated ones. Fortunately, the daily number of new cases already diminishes in EU, the UK, USA, South Africa, and Australia. In late January - early February 2022,the maximum averaged numbers of new cases are expected in Brazil, India, EU, and worldwide. Omicron waves can increase the numbers of deaths per capita, but in highly vaccinated countries, the deaths per case ratio significantly decreases.

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Coronasummer in Ukraine and Austria

Cited by 12 publications

References 0 publications

Final sizes and durations of new COVID-19 pandemic waves in Ukraine and around the world predicted by generalized SIR model

Final sizes and durations of new COVID-19 pandemic waves in Ukraine and around the world predicted by generalized SIR model

Influences of seasonal and demographic factors on the COVID-19 pandemic dynamics

How dangerous is omicron and how effective are vaccinations?

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