The transmission dynamics of SARS-CoV2 Omicron variant

In a latest research posted to the medRxiv* preprint server, researchers developed a coronavirus illness (COVID-19) model-inference system in South Africa to find out transmission dynamics and immune evasion related to extreme acute respiratory syndrome-associated coronavirus illness (SARS-CoV-2) Omicron variant.

Study: SARS-CoV-2 transmission dynamics in South Africa and epidemiological characteristics of the Omicron variant. Image Credit: ShutterstockExamine: SARS-CoV-2 transmission dynamics in South Africa and epidemiological traits of the Omicron variant. Picture Credit score: Shutterstock

Immunity and transmissibility related to Omicron

After the preliminary instances of the SARS-CoV-2 Omicron variant had been reported in South Africa in late November 2021, the variety of Omicron instances elevated quickly in a number of provinces of South Africa in addition to internationally.

Earlier laboratory research indicated that the Omicron variant might erode adaptive immunity, evident from the diminished Omicron neutralizing capacity of convalescent COVID-19 sufferers and vaccine recipients. As well as, a number of preliminary research confirmed that the replication fee of Omicron is larger in comparison with the SARS-CoV-2 Delta variant.

These shreds of proof point out elevated immune erosion and transmission dynamics with the Omicron variant.

Concerning the research

Within the current research, the authors reconstructed SARS-CoV-2 transmission dynamics in 9 provinces of South Africa utilizing a model-inference system and decided the immune erosion and transmissibility of the novel SARS-CoV-2 Omicron variant.

The model-inference system used on this research was primarily based on the authors’ earlier research on immune erosion and transmissibility related to SARS-CoV-2 variants of issues (VOCs) like Alpha, Beta, Gamma, and Delta.

Pandemic dynamics in South Africa, model-fit and validation utilizing unbiased information. (A) Pandemic dynamics in every of the 9 provinces (see legend); dots depict reported weekly numbers of instances and deaths; strains present mannequin imply estimates (in the identical coloration). For validation, mannequin estimated an infection charges are in comparison with seroprevalence measures over time from a number of sero-surveys summarized in ref 1 (B), COVID-related hospitalizations (left panel) and age-adjusted extra mortality (proper panel) throughout the Ancestral (C), Beta (D), and Delta (E) waves. Boxplots depict the estimated distribution for every province (center bar = imply; edges = 50% CrIs) and whiskers (95% CrIs). Crimson dots present corresponding measurements. Correlation (r) between mannequin estimated cumulative an infection fee and cumulative hospitalization or age-adjusted extra mortality (C-E) for every wave is proven in every plot. Word that hospitalization information start from 6/6/20 and extra mortality information start from 5/3/20 and thus are incomplete for the Ancestral wave.

Weekly instances and mortality information accounting for the an infection seasonality, under-detection of an infection, vaccination, and carried out nonpharmaceutical interventions (NPIs) had been used within the mannequin. Databases comparable to coronavirus COVID-19 (2019-nCoV) Knowledge Repository for South Africa (COVID19ZA), Nationwide Oceanic and Atmospheric Administration (NOAA), and Google Neighborhood Mobility Studies had been used for information assortment.

The model-inference estimates had been validated utilizing serology information from South African COVID-19 Modelling Consortium, COVID-19-associated hospital admission information collected from COVID19ZA, and the ancestral and Delta wave related age-adjusted extra mortality information collected from the South African Medical Analysis Council (SAMRC). The important thing model-inference estimates had been developed from the Gauteng province information because it had the earliest surge of SARS-CoV-2 Omicron variant, and the vast majority of their inhabitants had been beforehand contaminated by SARS-CoV-2 ancestral, Beta, or Delta variants.


After accounting for the an infection seasonality, under-detection of an infection, vaccination, and NPIs, the outcomes indicated that SARS-CoV-2 contaminated most South Africans earlier than the Omicron wave.

The model-estimated cumulative an infection charges had been larger than the province-based seroprevalence measures obtained at numerous time factors. They correlated properly with the COVID-19-associated hospitalization information from the ancestral SARS-CoV-2, Beta, and Delta variants throughout the 9 South African provinces. The estimated an infection numbers additionally correlated with the age-adjusted extra mortality related to the SARS-COV-2 ancestral and Delta wave; nevertheless, they didn’t correlate with the SARS-COV-2 Beta wave.

Aside from the Gauteng province, excessive cumulative an infection charges throughout the first three COVID-19 waves had been estimated from Western Cape and Northern Cape provinces. The estimated common cumulative COVID-19 an infection charges diverse from 58% of the inhabitants in Limpopo to 126% within the Northern Cape provinces.

The Beta variant was 38.5% extra transmissible in comparison with ancestral SARS-CoV-2 and related to 72.1% immune erosion in ancestral SARS-CoV-2-infected people. Compared, the Delta variant was 38.3% extra transmissible in comparison with ancestral SARS-CoV-2 and related to 32.5% immune erosion in ancestral SARS-CoV-2, Beta variant-infected people, or vaccine recipients.

Primarily based on the info from the Gauteng province alone, the Omicron variant transmissibility in comparison with SARS-CoV-2 ancestral and Delta variant had been 100.3% and 36.5%, respectively. Furthermore, the Omicron variant was related to a lower of 63.7% of inhabitants immunity amassed from earlier SARS-CoV-2 infections and vaccinations. From the Gauteng, Northwest, and Western Cape province information, the transmissibility of the Omicron variant was 92.2% in comparison with ancestral SARS-CoV-2 and led to 55% immune erosion in beforehand contaminated and vaccinated people.


The researchers developed a complete model-inference system for SARS-CoV-2 and estimated the transmissibility and immune erosion related to the Omicron variant. In response to the research, there was a excessive fee of immune erosion and transmissibility related to Omicron among the many convalescent COVID-19 sufferers and vaccine recipients.

This research signifies the elevated want for vaccination and booster vaccines in addition to the institution of secure and efficient therapeutics for populations worldwide. Moreover, the research outcomes aligned with the earlier preliminary and laboratory research stories related to Omicron. Therefore, these findings assist contextualize and interpret the transmission dynamics of Omicron exterior South Africa.

*Necessary discover

medRxiv publishes preliminary scientific stories that aren’t peer-reviewed and, due to this fact, shouldn’t be considered conclusive, information scientific observe/health-related habits, or handled as established info.

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