The study suggests that the behavior of an emerging variant of SARS-CoV-2 may be sensitive to the immunological and demographic context of its location.

In a recent study published on bioRxiv*, researchers describe heterogeneity in the speed, magnitude, and timing of 13 variable mutations/waves of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Study: The changing transmission dynamics of SARS-CoV-2 are associated with vaccination rates, number of circulating variants, and natural immunity.  Image credit: ETAJOE/Shutterstock
Stady: The changing transmission dynamics of SARS-CoV-2 are associated with vaccination rates, number of circulating variants, and natural immunity.. Image credit: ETAJOE/Shutterstock


SARS-CoV-2 continues to evolve, and global shifts to newly emerging variants could lead to new waves of transmission. The selective advantage of the new variants over the existing variants could stem from increased infectivity (through enhanced binding to the host cell receptor) and resistance to neutralizing antibodies.

Previous infections with different variants of SARS-CoV-2 can confer different levels of protection against new variants. The authors speculate that the variants’ infection history and vaccination rates may influence the rate at which a new variant can outcompete existing variants and become the dominant variant.

about studying

In this study, the researchers tested the set hypothesis and described differences in global time, magnitude, and speed of variable transitions. They performed a retrospective analysis of the SARS-CoV-2 genome sequence submitted to the Global Initiative on Sharing All Influenza Data (GISAID) database between October 2020 and October 2022.

Data for more than 12.8 million SARS-CoV-2 genome sequences were obtained from the GISAID repository through the coronavirus disease 2019 (COVID-19) viral genome analysis pipeline. Sequences were arranged by variant according to Pango nomenclature. Data on confirmed COVID-19 cases and confirmed deaths per day was obtained from the Johns Hopkins Center for Systems Science and Engineering.

The age, population density and information for each location (country) were accessed from WorldPop. The researchers proposed a model of the changing proportions over time for each site, taking into account multiple competing variables as changing landscapes remain dynamic in a given community. For the primary analysis, up to 13 Pangu lineage classes were considered for each of 215 geographic locations (countries and sub-country regions).

The initial analysis did not consider emerging Omicron Pango lineage populations due to insufficient data. In a sub-analysis of their own emerging variants, the researchers described the current data for SARS-CoV-2 Omicron variants BA.2.75, BQ.1, and XBB/XBB.1. Hierarchical clustering analysis was performed to characterize site similarities via Omicron waves for only 155 sites.

The researchers obtained site attributes such as demographics, the clinical landscape of COVID-19, and the general policy associated with when the proportion of sequences for a particular variant first reached 5% anywhere. They identified two proxies for variant competition when a new variant appeared at each site: 1) the number of circulating variants with a minimum prevalence of 5% and 2) the proportion of competition, a maximum percentage increase in the prevalence of existing variants.

the findings

SARS-CoV-2 Beta, Epsilon, Iota, Gamma, and Mu variants have been associated with reduced prevalence and transmission speeds, with the exception of beta transmission in South Africa and gamma transmission in South America. Delta and Omicron variants (BA.1, BA.1.1, BA.2, and BA.5) had fast transitions, although the prevalence and transition speeds of Omicron BA.1 and BA.1.1 varied worldwide.

The Alpha variant had a small and slow transmission in South America and South Africa due to the variant’s competition. The Omicron BA.1.1 variant has achieved a strong presence in the Americas. In contrast, there was little heterogeneity in the spread and transmission speeds of SARS-CoV-2 Delta, which showed complete and rapid transformation in most locations.

Omicron variants BA.4 and BA.5 had different trajectories in terms of maximum transition slopes, relative time to transition, and maximum diffusion, indicating a selective advantage of the BA.5 variant over BA.4. The transition slopes of the new Omicron sub-variants (BA.2.75, BQ.1 and XBB/XBB.1) were on par with the previous Omicron sub-variants.

Hierarchical clustering analysis yielded seven clusters and indicated that transmissions of the SARS-CoV-2 Omicron variant are likely to be more similar between some pairs of geolocations than others, suggesting a link between transmission dynamics and geolocation characteristics. The researchers studied the relationship between the number of co-circulating variables (when each variable had a 5% prevalence) and the maximum transition slope.

There was a significant association between a greater number of circulating variants and lower transmission speeds for several SARS-CoV-2 variants, including Epsilon, Gamma, Delta, and Omicron (BA.1, BA.2, and BA.5) variants. Higher vaccination rates have been associated with a slower and later global spread of variants before the emergence of delta and mu variants. However, there was a weak correlation between grafting rates and speed/timing of transitions for the Omicron variant.

Inoculation rates were significantly associated with changing pre-emergence delta/mo transmission dynamics, even after adjusting for site traits and multiple testing. A shorter time since the peak of the last wave, a higher previous COVID-19 case rate, and lower population density were associated with later shifts. It is likely that areas with more people aged 65 or older have a higher prevalence of the peak variant.


In summary, the researchers explain the associations of the behavior of the emerging SARS-CoV-2 variant with the number of variants in circulation, previous COVID-19 case rate, and vaccination rates. There was a strong association between higher vaccination rates and variable pre-transmission dynamics of the delta/mo variant.

Overall, the results indicate significant heterogeneity in how the variant competes with circulating variants across geographic sites, suggesting that the contemporary site-specific immune landscape may contribute to these interactions. These data on historical variable heterogeneity and shifts may be leveraged in future work to predict the behavior of emerging variables.

*Important note

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, directing clinical practice/health-related behaviour, or treated as hard information

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