Characterisation of Omicron Variant during COVID-19 Pandemic and the Impact of Vaccination, Transmission Rate, Mortality, and Reinfection in South Africa, Germany, and Brazil
- PMID: 35822785
- PMCID: PMC9264399
- 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
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.
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







References
-
- World Health Organization WHO Timeline—COVID-19. 27 April 2020. [(accessed on 3 February 2021)]. Available online: https://www.who.int/news/item/27-04-2020-who-timeline—covid-19.
-
- Our World in Data Coronavirus Pandemic (COVID-19) [(accessed on 15 February 2022)]. Available online: https://ourworldindata.org/coronavirus.
-
- Li X., Mukandavire C., Cucunubá Z.M., Londono S.E., Abbas K., Clapham H.E., Jit M., Johnson H.L., Papadopoulos T., Vynnycky E., et al. Estimating the health impact of vaccination against ten pathogens in 98 low-income and middle-income countries from 2000 to 2030: A modelling study. Lancet. 2021;397:398–408. doi: 10.1016/S0140-6736(20)32657-X. - DOI - PMC - PubMed
-
- Davies N.G., Abbott S., Barnard R.C., Jarvis C.I., Kucharski A.J., Munday J.D., Pearson C.A., Russell T.W., Tully D.C., Washburne A.D., et al. Estimated transmissibility and impact of SARS-CoV-2 lineage B. 1.1. 7 in England. Science. 2021;372:eabg3055. doi: 10.1126/science.abg3055. - DOI - PMC - PubMed
-
- Ong S.W.X., Chiew C.J., Ang L.W., Mak T.M., Cui L., Toh M.P.H.S., Lim Y.D., Lee P.H., Lee T.H., Chia P.Y., et al. Clinical and virological features of SARS-CoV-2 variants of concern: A retrospective cohort study comparing B.1.1.7 (Alpha), B.1.315 (Beta), and B.1.617.2 (Delta) Clin. Infect. Dis. 2021:ciab721. doi: 10.1093/cid/ciab721. - DOI - PMC - PubMed
LinkOut - more resources
Full Text Sources
Miscellaneous