An estimate of Omicron’s fitness advantage

The persistent evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has prolonged the current pandemic.

This has led to the emergence of several variants of SARS-CoV-2, some of which have been classified as variants of concern (VOC) or variants of interest (VOI). These classifications are given according to their transmissibility, virulence, and ability to evade the immune response generated by COVID-19 vaccination or natural infection.

Globally, there has been an increase in COVID-19 cases due to the circulation of SARS-CoV-2 Alpha, Delta, and more recently Omicron variants.

To study: Global estimates of the fitness advantage of the Omicron variant of SARS-CoV-2. Image Credit: RCW.studio/Shutterstock.com

Background

Previous studies on the SARS-CoV-2 Omicron variant revealed that this viral strain has a higher transmission capacity compared to the Delta variant. Furthermore, these studies observed that the neutralizing activity of plasma from fully vaccinated individuals exhibited lower neutralizing activity against the Omicron variant.

These findings imply that the Omicron variant can effectively escape immune responses elicited after vaccination. However, a third booster dose of current COVID-19 messenger ribonucleic acid (mRNA) vaccines has improved the efficacy of vaccination against the Omicron variant.

Previous studies have highlighted the relative growth advantage of the Omicron variant in certain countries or settings compared to other SARS-CoV-2 variants. However, the reason behind the heterogeneity in the transmission capacity of these variants between countries remains unclear.

Scientists have hypothesized that this heterogeneity could be due to several reasons, including the difference in variants circulating in each country, different non-pharmaceutical preventive strategies, different immune responses induced by vaccination and natural infection, as well as many other factors.

About the study

In a recent study posted on the preprint server medRxiv*, researchers from Columbia University Irving Medical Center and Los Alamos National Laboratory quantify the transmission advantage of the Omicron variant of SARS-CoV-2 across many countries and determine factors associated with this heterogeneity using a hierarchical turnover model . Here, the researchers also demonstrate the effectiveness of the model structure in quantifying the fitness of a viral variant.

The current study revealed that in a sample of forty countries, the heterogeneity associated with Omicron fitness could not be demonstrated through immunology-related covariates. However, some level of correlation with the fitness of the Delta variant was observed, suggesting the existence of fixed effects at the country level.

Some of the parameters on which the adequacy of the renewal model depends include epidemic growth rates over time, case counts, and variant frequencies. Importantly, the authors suggest that the overall fitness of the model is significantly good, with a mean absolute error in variable frequency of only 2.5 percentage points for weekly aggregated data. Additionally, for daily data, a mean absolute error in variable frequency of 5 percentage points was estimated.

Study Findings

In the current study, the researchers addressed all structural abnormalities in the epidemiological data by aggregating data on a weekly basis. Importantly, the renewal model was used to provide a reasonable estimate of the true trend, even during a sudden spike in reinfection cases.

For most countries of the world, the Omicron variant became the predominant circulating strain within about thirty days. However, this variant was not associated with a sustained increase in the number of infections, as most countries exhibited a decline in COVID-19 cases after the confirmed arrival of Omicron in each respective nation.

The model predicted that in countries like the UK, all COVID-19 cases within the study period could be attributed to the rise and rise of the Omicron variant. This observation was based on the fact that throughout the study period, the effective reproduction number associated with the circulating wild-type strain remained less than one.

In most countries, the growth rate of the wild-type SARS-COV-2 variant decreased with the increase of the Omicron variant. This could be due to both competition with the Omicron variant for susceptible individuals and the efficacy of pharmaceutical and non-pharmaceutical interventions that were implemented in response to the high transmission of the Omicron variant. In particular, this trend was not observed in India and Brazil.

Example model settings;  all countries are shown in Fig. S1.  Case counts (top row) and variant counts (middle row) are grouped by week, while growth rates (bottom row) are forecast by day.  Model-predicted growth rates are shown for the epidemic as a whole (both variants with their actual frequencies; blue) and only for non-Omicron variants (as if the Omicron frequency were zero; gray).  Model predictions are shown with solid lines (median), dark shading (95% confidence interval, which includes uncertainty in model parameters), and light shading (95% posterior predictive interval, which also includes sampling noise). .

Example model settings; all countries are shown in Fig. S1. Case counts (top row) and variant counts (middle row) are grouped by week, while growth rates (bottom row) are forecast by day. Model-predicted growth rates are shown for the epidemic as a whole (both variants with their actual frequencies; blue) and only for non-Omicron variants (as if the Omicron frequency were zero; gray). Model predictions are shown with solid lines (median), dark shading (95% confidence interval, which includes uncertainty in model parameters), and light shading (95% posterior predictive interval, which also includes sampling noise). .

The current model indicated that the selective advantage of the Omicron variant between countries around the world differed considerably. Furthermore, the model assumed that the proportion of reproduction numbers for each country was obtained from a lognormal distribution, which was simultaneously calculated from the data.

The main advantage of the hierarchical structure was the reduction of structural biases presented by the data from one country. Therefore, a more robust prediction could be made based on the overall selection effect and heterogeneity at the country level.

(A) Estimates of the selection coefficient, s, for each country, under the hierarchical or non-hierarchical models.  Dots and lines show median and 95% CrI.  The slope of the data is steeper than the 1:1 line, which means that the estimates are less extreme for the hierarchical model.  (B) Summaries of estimates of the mean value of s for Omicron and of the distribution of s values ​​across countries, calculated from hierarchical or non-hierarchical models.  The dots show the median or mean, and the thick and thin lines show the 50% and 95% CrI or CI.

(A) Estimates of the selection coefficient, s, for each country, under the hierarchical or non-hierarchical models. Dots and lines show median and 95% CrI. The slope of the data is steeper than the 1:1 line, which means that the estimates are less extreme for the hierarchical model. (B) Summaries of estimates of the mean value of s for Omicron and of the distribution of s values ​​across countries, calculated from hierarchical or non-hierarchical models. The dots show the median or mean, and the thick and thin lines show the 50% and 95% CrI or CI.

Conclusions

The hierarchical model used in the present study was confirmed to be effective on a global scale.

The researchers indicated that a higher selection coefficient for the Omicron variant might be associated with countries with higher immunity. However, the effect of several covariates related to immunity at the country level was not statistically significant, which could be the result of inadequate variation between countries.

In the future, scientists will focus on understanding the factors that drive heterogeneity in the transmission of various viral variants in a particular country.

*Important news

medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, guide clinical practice/health-related behavior, or be treated as established information.

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