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. 2022 Apr 26;11(2):12.
doi: 10.3390/biotech11020012.

Characterisation of Omicron Variant during COVID-19 Pandemic and the Impact of Vaccination, Transmission Rate, Mortality, and Reinfection in South Africa, Germany, and Brazil

Affiliations

Characterisation of Omicron Variant during COVID-19 Pandemic and the Impact of Vaccination, Transmission Rate, Mortality, and Reinfection in South Africa, Germany, and Brazil

Carolina Ribeiro Xavier et al. BioTech (Basel). .

Abstract

Several variants of SARS-CoV-2 have been identified in different parts of the world, including Gamma, detected in Brazil, Delta, detected in India, and the recent Omicron variant, detected in South Africa. The emergence of a new variant is a cause of great concern. This work considers an extended version of an SIRD model capable of incorporating the effects of vaccination, time-dependent transmissibility rates, mortality, and even potential reinfections during the pandemic. We use this model to characterise the Omicron wave in Brazil, South Africa, and Germany. During Omicron, the transmissibility increased by five for Brazil and Germany and eight for South Africa, whereas the estimated mortality was reduced by three-fold. We estimated that the reported cases accounted for less than 25% of the actual cases during Omicron. The mortality among the nonvaccinated population in these countries is, on average, three to four times higher than the mortality among the fully vaccinated. Finally, we could only reproduce the observed dynamics after introducing a new parameter that accounts for the percentage of the population that can be reinfected. Reinfection was as high as 40% in South Africa, which has only 29% of its population fully vaccinated and as low as 13% in Brazil, which has over 70% and 80% of its population fully vaccinated and with at least one dose, respectively. The calibrated models were able to estimate essential features of the complex virus and vaccination dynamics and stand as valuable tools for quantifying the impact of protocols and decisions in different populations.

Keywords: COVID-19; Omicron variant; SIRD; computational epidemiology; vaccination.

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Conflict of interest statement

The authors declare no conflict of interest. The founders 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
Weekly deaths per million people in recent since 9 October 2021 in South Africa, Germany, and Brazil. Each point represents the cumulative number of confirmed deaths over the previous week.
Figure 2
Figure 2
Choropleth map of vaccination around the globe by 15 February 2022. It presents the share of people who received all doses prescribed by the initial vaccination protocol, divided by the total population of the country.
Figure 3
Figure 3
Percentage of Omicron variant of all analysed sequences. This figure was adapted from the one generated by Our World in Data website.
Figure 4
Figure 4
Evolution of the number of active cases (upper left), deaths (upper right), recovered cases (lower left), and confirmed cases (lower right) in Brazil. All simulations with errors below 10% are presented.
Figure 5
Figure 5
Evolution of the number of active cases (upper left), deaths (upper right), recovered cases (lower left), and confirmed cases (lower right) in South Africa. All simulations with errors below 10% are presented.
Figure 6
Figure 6
Evolution of the number of active cases (upper left), deaths (upper right), recovered cases (lower left), and confirmed cases (lower right) in Germany. All simulations with errors below 10% are presented.
Figure 7
Figure 7
Violin plots of the parameters: br1, r2, m, mrd, effd, srate for Brazil, South Africa, and Germany. (a) br1. (b) r2. (c) m. (d) mrd. (e) effd. (f) srate.

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