Epidemiological Features of COVID-19 in Northwest Russia in 2021

The relative prevalence of the Omicron variant within SARS-CoV-2 infected cohorts in different countries: A systematic review

The Omicron variant of SARS-CoV-2 was detected in October 2021 and exhibited high transmissibility, immune evasion, and reduced severity when compared to the earlier variants. The lesser vaccine effectiveness against Omicron and its reduced severity created vaccination hesitancy among the public. This review compiled data reporting the relative prevalence of Omicron as compared to the early variants to give an insight into the existing variants, which may shape the decisions regarding the targets of the newly developed vaccines. Complied data revealed more than 90% prevalence within the infected cohorts in some countries. The BA.1 subvariant predominated over the BA.2 during the early stages of the Omicron wave. Moreover, BA.4/BA.5 subvariants were detected in South Africa, USA and Italy between October 2021 and April 2022. It is therefore important to develop vaccines that protect against Omicron as well as the early variants, which are known to cause more severe complications.

COVID-19 Incidence Proportion as a Function of Regional Testing Strategy, Vaccination Coverage, and Vaccine Type

Introduction: The COVID-19 pandemic has become a serious challenge for humanity almost everywhere globally. Despite active vaccination around the world, the incidence proportion in different countries varies significantly as of May 2022. The reason may be a combination of demographic, immunological, and epidemiological factors. The purpose of this study was to analyze possible relationships between COVID-19 incidence proportion in the population and the types of SARS-CoV-2 vaccines used in different countries globally, taking into account demographic and epidemiological factors. Materials and methods: An initial database was created of demographic and immunoepidemiological information about the COVID-19 situation in 104 countries collected from published official sources and repository data. The baseline included, for each country, population size and density; SARS-CoV-2 testing coverage; vaccination coverage; incidence proportion; and a list of vaccines that were used, including their relative share among all vaccinations. Subsequently, the initial data set was stratified by population and vaccination coverage. The final data set was subjected to statistical processing both in general and taking into account population testing coverage. Results: After formation of the final data set (including 53 countries), it turned out that reported COVID-19 case numbers correlated most strongly with testing coverage and the proportions of vaccine types used, specifically, mRNA (V1); vector (V2); peptide/protein (V3); and whole-virion/inactivated (V4). Due to the fact that an inverse correlation was found between 'reported COVID-19 case numbers' with V2, V3, and V4, these three vaccine types were also combined into one analytic group, 'non-mRNA group' vaccines (Vnmg). When the relationship between vaccine type and incidence proportion was examined, minimum incidence proportion was noted at V1:Vnmg ratios (%:%) from 0:100 to 30:70. Maximum incidence proportion was seen with V1:Vnmg from 80:20 to 100:0. On the other hand, we have shown that the number of reported COVID-19 cases in different countries largely depends on testing coverage. To offset this factor, countries with low and extremely high levels of testing were excluded from the data set; it was then confirmed that the largest number of reported COVID-19 cases occurred in countries with a dominance of V1 vaccines. The fewest reported cases were seen in countries with a dominance of Vnmg vaccines. Conclusion: In this paper, we have shown for the first time that the level of reported COVID-19 incidence proportion depends not only on SARS-CoV-2 testing and vaccination coverage, which is quite logical, but probably also on the vaccine types used. With the same vaccination level and testing coverage, those countries that predominantly use vector and whole-virion vaccines feature incidence proportion that is significantly lower than countries that predominantly use mRNA vaccines.

The Development of the SARS-CoV-2 Epidemic in Different Regions of Siberia in the 2020-2022 Period

The comparison of the development of the SARS-CoV-2 epidemic in several neighboring regions can help researchers to assess the risks and develop more effective strategies and approaches in the field of preventive medicine. We analyzed the infection and mortality statistics for the 2020-2022 period in ten individual regions of the Siberian Federal District of Russia. We also sequenced complete genomes, which allowed us to analyze the genetic diversity of SARS-CoV-2 circulated in each of the ten regions and to build a phylogenetic dendrogram for the virus variants. The ParSeq v.1.0 software was developed to automate and speed up the processing and analysis of viral genomes. At the beginning of the pandemic, in the first two waves, the B.1.1 variant (20B) dominated in all regions of the Siberian Federal District. The third and fourth waves were caused by the Delta variant. Mortality during this period was at a maximum; the incidence was quite high, but the number of deposited genomes with GISAID during this period was extremely low. The maximum incidence was at the beginning of 2022, which corresponds to the arrival of the Omicron variant in the region. The BA.5.2 variant became the dominant one. In addition, by using NextClade, we identified three recombinants in the most densely populated areas.

Correction: Gladkikh et al. Epidemiological Features of COVID-19 in Northwest Russia in 2021. Viruses 2022, 14, 931

There was an error in the original publication [...].

HLA Genotypes in Patients with Infection Caused by Different Strains of SARS-CoV-2

The aggressive infectious nature of SARS-CoV-2, its rapid spread, and the emergence of mutations necessitate investigation of factors contributing to differences in SARS-CoV-2 susceptibility and severity. The role of genetic variations in the human HLA continues to be studied in various populations in terms of both its effect on morbidity and clinical manifestation of illness. The study included 484 COVID-19 convalescents (northwest Russia residents of St. Petersburg). Cases in which the responsible strain was determined were divided in two subgroups: group 1 (n = 231) had illness caused by genovariants unrelated to variant of concern (VOC) strains; and group 2 (n = 80) had illness caused by the delta (B.1.617.2) VOC; and a control group (n = 1456). DNA typing (HLA-A, B, DRB1) was performed at the basic resolution level. HLA-A*02 was associated with protection against infection caused by non-VOC SARS-CoV-2 genetic variants only but not against infection caused by delta strains. HLA-A*03 was associated with protection against infection caused by delta strains; and allele groups associated with infection by delta strains were HLA-A*30, B*49, and B*57. Thus, in northwest Russia, HLA-A*02 was associated with protection against infection caused by non-VOC SARS-CoV-2 genetic variants but not against delta viral strains. HLA-A*03 was associated with a reduced risk of infection by delta SARS-CoV-2 strains. HLA-A*30, HLA-B*49, and HLA-B*57 allele groups were predisposing factors for infection by delta (B.1.617.2) strains.

Uninvited Guest: Arrival and Dissemination of Omicron Lineage SARS-CoV-2 in St. Petersburg, Russia

Following its emergence at the end of 2021, the Omicron SARS-CoV-2 variant rapidly spread around the world and became a dominant variant of concern (VOC). The appearance of the new strain provoked a new pandemic wave with record incidence rates. Here, we analyze the dissemination dynamics of Omicron strains in Saint Petersburg, Russia's second largest city. The first case of Omicron lineage BA.1 was registered in St. Petersburg on 10 December 2021. Rapid expansion of the variant and increased incidence followed. The peak incidence was reached in February 2022, followed by an observed decline coinciding with the beginning of spread of the BA.2 variant. SARS-CoV-2 lineage change dynamics were shown in three categories: airport arrivals; clinical outpatients; and clinical inpatients. It is shown that the distribution of lineage BA.1 occurred as a result of multiple imports. Variability within the BA.1 and BA.2 lineages in St. Petersburg was also revealed. On the basis of phylogenetic analysis, an attempt was made to trace the origin of the first imported strain, and an assessment was made of the quarantine measures used to prevent the spread of this kind of infection.