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.

Leveraging social network topology could improve the efficiency of SARS-CoV-2 epidemic control strategies in resource-limited contexts

“…The incubation period (α) followed a gamma distribution with a mean of 3.1 days () followed a gamma distribution with a mean of 3.1 days ( sd 2.6), including one day of pre-symptomatic transmission (40). The mean recovery period (γ) followed a) followed a Poisson distribution with a mean of 9.67 days (41) (Fig. S2.2).…”

Changes in population immunity against infection and severe disease from SARS-CoV-2 Omicron variants in the United States between December 2021 and November 2022

“…During the first Omicron wave (December 2021 – February 2022) over 25 million COVID-19 diagnoses were reported in the US, equivalent to 8% of the US population. Many more infections were likely undiagnosed and, due to waning immunity and increased immune evasion, reinfections are occurring more frequently 2 , even amongst those vaccinated 3 .…”

Older age and depressive state are risk factors for re-positivity with SARS-CoV-2 Omicron variant

“…These changes make it more infectious and transmissible, and simultaneously cause immune escape. This leads to reduced efficacy and poor therapeutic effect of existing vaccines ( 2 , 3 ), and it usually spreads widely before symptoms appear ( 4 ).…”

“…The high infectivity made the Omicron threaten more people, especially for elderly ( 8 , 9 ), and one study have demonstrated that rate of severe illness would not be decreased for some population without vaccination ( 10 ). Experimental studies show that Omicron has many mutations in its structure compared with SARS-CoV-2, which increases the risk of reinfection ( 2 , 11 – 13 ). In previous outbreaks, the total reinfection rate of the SARS-CoV-2 variant was <2% ( 6 ).…”