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Relevance. COVID-19 vaccination reduces mortality and the course of severe diseases. However, there is an insufficiency of studies evaluating factors leading to infection among COVID-19 vaccinated individuals.Aim. Identification of epidemiological features that distinguish cases of the disease in vaccinated and unvaccinated cohorts.Materials and methods. The analysis of the incidence of COVID-19 in 1126 hospitalized patients in the period from 23.06.2021 to 01.05.2022 was carried out taking into account the presence or absence of vaccination against the SARS-CoV-2 virus.Results. It was found that the risk of COVID-19 getting sick in the unimmunized was 1.5 times higher than in the vaccinated (p < 0.05). The incidence of hospitalization, due to the severity of the condition (moderate, severe and extremely severe), in unvaccinated people with no history of comorbidities, is more than 3 times higher than in vaccinated people (p < 0.05) in the same group. The probability of death from COVID-19 among vaccinated people is 1.5 times lower than among unimmunized people (p < 0.05). The age characteristic of mortality in vaccinated people shifts to the «senile» age (76.93 ± 1.32), while among the unimmunized, the age of death is closer to the category of «elderly» (73.74 ± 1.39 years) (p ≤ 0.05). In the structure of mortality among the vaccinated, the main share was made up of patients with a history of 3 to 7 concomitant systemic diseases (66.7%), while among the unvaccinated, the main share (74.5%) were patients either without comorbidities or with a history of 1 to 2 concomitant diseases.Conclusion. The results of the epidemiological features of the COVID-2 epidemic process have shown that vaccination against the SARS-CoV-2 virus is vital for elderly and senile people with comorbid conditions.
Relevance. COVID-19 vaccination reduces mortality and the course of severe diseases. However, there is an insufficiency of studies evaluating factors leading to infection among COVID-19 vaccinated individuals.Aim. Identification of epidemiological features that distinguish cases of the disease in vaccinated and unvaccinated cohorts.Materials and methods. The analysis of the incidence of COVID-19 in 1126 hospitalized patients in the period from 23.06.2021 to 01.05.2022 was carried out taking into account the presence or absence of vaccination against the SARS-CoV-2 virus.Results. It was found that the risk of COVID-19 getting sick in the unimmunized was 1.5 times higher than in the vaccinated (p < 0.05). The incidence of hospitalization, due to the severity of the condition (moderate, severe and extremely severe), in unvaccinated people with no history of comorbidities, is more than 3 times higher than in vaccinated people (p < 0.05) in the same group. The probability of death from COVID-19 among vaccinated people is 1.5 times lower than among unimmunized people (p < 0.05). The age characteristic of mortality in vaccinated people shifts to the «senile» age (76.93 ± 1.32), while among the unimmunized, the age of death is closer to the category of «elderly» (73.74 ± 1.39 years) (p ≤ 0.05). In the structure of mortality among the vaccinated, the main share was made up of patients with a history of 3 to 7 concomitant systemic diseases (66.7%), while among the unvaccinated, the main share (74.5%) were patients either without comorbidities or with a history of 1 to 2 concomitant diseases.Conclusion. The results of the epidemiological features of the COVID-2 epidemic process have shown that vaccination against the SARS-CoV-2 virus is vital for elderly and senile people with comorbid conditions.
Background: Russian state policy for health protection, rehabilitation, and health improvement requires studying regional mortality rates, including those related to COVID-19.Objective: To assess differences in COVID-19-related mortality between the regions of the same federal district.Materials and methods: Mortality data are sourced from death records in the Unified State Register of Civil Status Acts. The data were analyzed using unweighted arithmetic means, specific indicators, and standard deviation (the mean ± standard deviation). To eliminate the distortion by an age factor in mortality rates comparison, we replaced the age structure of the individual region’s population with that of Russia through indirect standardization of mortality rates. We used K-means clustering to group the regions by COVID-19-related mortality rates.Results: In 2021 Russia had 2,446,922 deaths, i.e. 648,615 (36.1%) and 163,645 (7.2%) cases more compared to 2019 and 2020, respectively. Of the total number, 17.3% of cases (424,252) had COVID-19 as a primary cause of death: nearly three times more than in 2020 (144,691 COVID-19-related deaths). Based on the average sizes of all individual age groups related to the respective region, nonstandardized and standardized COVID-19-related mortality rates were 265.30 ± 103.16 and 279.28 ± 91.07 per 100,000 persons in 2021, respectively. The cluster analysis showed that the largest number of regions (28 regions in 8 federal districts) comprised the third cluster with an average mortality rate of 276.26 ± 15.16 per 100,000 persons. The first cluster with an average mortality rate of 406.43 ± 29.26 per 100,000 persons included 12 regions in 7 federal districts. The second сluster included 21 regions (341.49 ± 18.16 per 100,000 persons) in 6 federal districts, the fourth cluster – 17 regions (196.73 ± 25.05 per 100,000 persons) in 6 districts, and the fifth cluster – 7 regions (87.22 ± 12.42 per 100,000 persons) in 5 districts.Conclusions: There is no common explanation for the COVID-19-related mortality differences not only between the regions of the same country but also between countries. This lack of understanding gets worse because one should also separate the pandemic’s health factors from social, psychological, and economic ones. The government should play a more important role in healthcare management, reform payment systems, and eliminate private financial intermediaries used to pay for medical services.Restrictions: The Unified State Register of Civil Status Acts data, which consisted of preliminary death certificates, may differ from the data of the Federal State Statistics Service, which became available to researchers later in 2022.
Introduction. The COVID-19 pandemic, caused by a novel SARS-CoV-2 coronavirus infection, lasted just over three years. Its end was announced in early May 2023. According to official data, the pandemic claimed 6.9 million lives worldwide, but it is believed that at least 20 million people were victims. The first wave of the pandemic was caused by a virus that spread from China. The virus mainly kills representatives of older age groups of the population and is characterized by a high degree of mutagenicity, which contributes to the emergence of new strains of the virus. The most aggressive and established in the population new strains of the virus spread and gave rise to the second wave of the pandemic, which turned out to be the longest. The third wave was caused by the most aggressive strain, spreading from India, and caused the greatest number of deaths. Aim of the study was to identify the extent to which changes in the virus itself affected the gender and age mortality structure during the three waves of the COVID-19 pandemic observed between 2020 and 2021. Materials and methods. The method of single factor analysis of variance was applied. The study was based on the data of the Operational Headquarters under the Government of Samara region, which were published daily with the indication of gender, age, and cause of each death. Results. The analysis confirmed the influence of the virus variability factor on the age mortality structure at the significance level of p<0.05. Comparison of the diagrams of the shares of the selected age segments in the mortality of men and women in each of the pandemic waves clearly showed how the gender and age mortality structure changed. The result of the analysis of variance showed that the changes occurring in the virus itself, although not as significant, affected the mortality pattern, with male mortality being more affected than female mortality. Conclusion. The result of the analysis of variance showed changes occurring in the virus itself to have an impact on the mortality structure, and on male mortality to a greater extent than on female mortality.
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