The End or a New Era of Development of SARS-CoV-2 Virus: Genetic Variants Responsible for Severe COVID-19 and Clinical Efficacy of the Most Commonly Used Vaccines in Clinical Practice

Miteva, Dimitrina; Kitanova, Meglena; Batselova, Hristiana; Lazova, Snezhina; Chervenkov, Lyubomir; Peshevska-Sekulovska, Monika; Sekulovski, Metodija; Gulinac, Milena; Vasilev, Georgi; Томов, Л; Velikova, Tsvetelina

doi:10.3390/vaccines11071181

Cited by 7 publications

(1 citation statement)

References 155 publications

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“…However, it is essential to mention that virus variants change over time along with the clinical and epidemiological picture, as it was discussed recently by Miteva et al [ 39 ].…”

Section: Resultsmentioning

confidence: 99%

Applications of time series analysis in epidemiology: Literature review and our experience during COVID-19 pandemic

Tomov,

Chervenkov,

Miteva

et al. 2023

World J Clin Cases

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Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.

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“…However, it is essential to mention that virus variants change over time along with the clinical and epidemiological picture, as it was discussed recently by Miteva et al [ 39 ].…”

Section: Resultsmentioning

confidence: 99%

Applications of time series analysis in epidemiology: Literature review and our experience during COVID-19 pandemic

Tomov,

Chervenkov,

Miteva

et al. 2023

World J Clin Cases

Self Cite

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Neutralization of Different Variants of SARS-CoV-2 by a F(ab′)2 Preparation from Sera of Horses Immunized with the Viral Receptor Binding Domain

Rodriguez-Nuñez,

Cepeda,

Bello

et al. 2023

Antibodies

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The Receptor Binding Domain (RBD) of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, is the functional region of the viral Spike protein (S), which is involved in cell attachment to target cells. The virus has accumulated progressively mutations in its genome, particularly in the RBD region, many of them associated with immune evasion of the host neutralizing antibodies. Some of the viral lineages derived from this evolution have been classified as Variant of Interest (VOI) or Concern (VOC). The neutralizing capacity of a F(ab′)2 preparation from sera of horses immunized with viral RBD was evaluated by lytic plaque reduction assay against different SARS-CoV-2 variants. A F(ab′)2 preparation of a hyperimmune serum after nine immunizations with RBD exhibited a high titer of neutralizing antibodies against the ancestral-like strain (1/18,528). A reduction in the titer of the F(ab’)2 preparation was observed against the different variants tested compared to the neutralizing activity against the ancestral-like strain. The highest reduction in the neutralization titer was observed for the Omicron VOC (4.7-fold), followed by the Mu VOI (2.6), Delta VOC (1.8-fold), and Gamma VOC (1.5). Even if a progressive reduction in the neutralizing antibodies titer against the different variants evaluated was observed, the serum still exhibited a neutralizing titer against the Mu VOI and the Omicron VOC (1/7113 and 1/3918, respectively), the evaluated strains most resistant to neutralization. Therefore, the preparation retained neutralizing activity against all the strains tested.

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Molecular Mechanisms of Pathogenesis, Prevention, and Therapy of COVID-19: Summarizing the Results of 2022

Gusev

2023

IJMS

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The End or a New Era of Development of SARS-CoV-2 Virus: Genetic Variants Responsible for Severe COVID-19 and Clinical Efficacy of the Most Commonly Used Vaccines in Clinical Practice

Cited by 7 publications

References 155 publications

Applications of time series analysis in epidemiology: Literature review and our experience during COVID-19 pandemic

Applications of time series analysis in epidemiology: Literature review and our experience during COVID-19 pandemic

Neutralization of Different Variants of SARS-CoV-2 by a F(ab′)2 Preparation from Sera of Horses Immunized with the Viral Receptor Binding Domain

Molecular Mechanisms of Pathogenesis, Prevention, and Therapy of COVID-19: Summarizing the Results of 2022

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