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. 2023 Sep 27;15(10):2014.
doi: 10.3390/v15102014.

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

Natalia V Palyanova  1 , Ivan A Sobolev  1 , Andrey Yu Palyanov  1   2   3 , Olga G Kurskaya  1 , Andrey B Komissarov  4 , Daria M Danilenko  4 , Artem V Fadeev  4 , Alexander M Shestopalov  1
Affiliations

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

Natalia V Palyanova et al. Viruses. .

Abstract

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.

Keywords: COVID-19; SARS-CoV-2; Siberia; epidemiology; phylogenetics; recombinants.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
The map of the Siberian Federal District in Russia.
Figure 2
Figure 2
Moving average number of SARS-CoV-2 infections detected per day in the Siberian Federal District and in Russia. Blue—averaged data for the whole of Russia, red—Siberian Federal District.
Figure 3
Figure 3
Daily number of SARS-CoV-2 cases according to official data in the Siberian Federal District during the first and second waves (7 day moving average).
Figure 4
Figure 4
The daily number of people infected with SARS-CoV-2, according to official data in the Siberian Federal District, in the third wave, corresponding to the arrival of the Delta variant in Russia, smoothly flowing into the fourth wave (7 day moving average).
Figure 5
Figure 5
The daily number of people infected with SARS-CoV-2 according to official data in the Siberian Federal District in the fifth and sixth waves of incidence (7 day moving average).
Figure 6
Figure 6
Daily COVID-19 mortality in the Siberian Federal District in 2020–2022 (7 day moving average).
Figure 7
Figure 7
The phylogenetic dendrogram computed and visualized with MEGA11 and based on the whole genome nucleotide sequences of SARS-CoV-2 in the Siberian Federal District (SFD) in 2020–2022. Round label: red—reference sequences, blue—recombinants from SFD. We used MEGA11 [25] software for phylogenetic analysis with the Maximum Likelihood method with bootstrap support (500 replications) and utilizing a GTR + G + I substitution model.
See this image and copyright information in PMC

References

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