Investigation of the continuous spread of SARS-CoV-2 in the post pandemic time - Insights into the reason for the sustained spread despite the establishment of population immunity

Technical Summary: Investigation of the Continuous Spread of SARS-CoV-2 in the Post-Pandemic Time

Problem Statement
Despite the establishment of global population immunity through prior infection and vaccination, SARS-CoV-2 continues to spread and generate infection waves. Current understanding regarding the mechanisms driving this sustained transmission is limited, making it difficult to predict the virus's future evolution and spreading trends. A central question remains: why has population immunity failed to halt the virus, and what evolutionary forces are responsible for its persistence? While random mutations are known drivers, the role of recombination events in generating variants with unique mutation combinations that influence virulence and transmission requires further investigation.

Methodology
The study employs a comprehensive genomic epidemiology approach, utilizing Germany as a representative location due to its systematic surveillance and high-quality genomic data.

• Data Source: Over 550,000 SARS-CoV-2 sequences collected in Germany between January 2022 and February 2026 were retrieved from GISAID (as of April 30, 2026).
• Quality Control: Sequences were filtered based on strict criteria: complete sequences (>29,000 nt) with less than 5% ambiguous bases (Ns), complete collection dates, and the exclusion of genomes with excessive private mutations (>24 relative to the reference tree) or mutation clusters (6+ private differences within a 100-nucleotide window).
• Lineage Identification: The PANGOLIN software suite was used for dynamic lineage classification.
• Growth Advantage Analysis: A logistic regression model was applied to evaluate the relative weekly growth advantage of predominant variants (specifically XBB.1.5, JN.1, and XEC) during their early spreading periods (approximately 45 days post-community transmission onset) compared to co-circulating variants.

Key Results

1. Lineage Dynamics (2022–2026):

   • 2022: Predominance of early Omicron lineages (BA.1, BA.2, BA.5).
   • 2023: Shift to the XBB family (recombinants of BA.2 subvariants), followed by the emergence of JN.1 (a descendant of BA.2.86) in late 2023.
   • 2024: Predominance of the BA.2.86/JN.1 family, including variants like KP.3.1 and the recombinant XEC (derived from two JN.1 subvariants).
   • 2025–2026: Emergence of new recombinant variants, specifically XFG and NB.1.8.1. Notably, while XFG briefly surpassed NB.1.8.1 in mid-2025, NB.1.8.1 displayed a growth advantage in late 2025, outcompeting XFG to become the predominant lineage by early 2026. NB.1.8.1 is derived from a recombination between an XBB subvariant and JN.1, exhibiting high genetic divergence from other co-existing strains.

2. Relative Growth Advantage:

   • XBB.1.5: Demonstrated a 60% weekly growth advantage over co-circulating BA.5 sub-lineages in early 2023.
   • JN.1: Showed a strong 75% weekly growth advantage over XBB sub-lineages in late 2023.
   • XEC: Displayed a lower relative growth advantage of 38% over other JN.1 sub-lineages in late 2024. This reduction is attributed to the closely related genetic backgrounds of the competing variants.
   • Trend: The study notes that recently emerged variants (like XEC and XFG) exhibit lower growth advantages compared to earlier major variants (XBB.1.5, JN.1), potentially due to the increasing genetic similarity of the circulating viral pool.

Key Contributions

• Identification of Recombination as a Primary Driver: The study establishes that since mid-2024, the majority of predominant SARS-CoV-2 variants have been produced primarily through recombination events, either between closely related lineages (e.g., XEC, XFG) or distantly related ones (e.g., NB.1.8.1).
• Differentiation of Short-term vs. Long-term Drivers: The analysis suggests that while specific viral features (such as antibody evasion) may dictate short-term spreading trends, the long-term spreading trajectory is primarily determined by the genomic diversity and genetic divergence of the virus from the existing population immunity landscape.
• Validation of Predictive Models: The study confirms previous predictions that highly divergent recombinant variants (specifically NB.1.8.1) possess the potential to become predominant, outcompeting variants with verified high-level antibody evasion but lower genetic divergence (such as XFG).

Significance and Claims
The paper argues that the continuous spread of SARS-CoV-2 despite population immunity is largely driven by the evolution of highly divergent recombinant variants. The authors claim that:

• Genomic Diversity is Critical: Long-term spreading trends can be predicted, or at least significantly understood, through phylogenetic and genomic epidemiology investigations that track genomic diversity.
• Future Trends: While the virus may continue to spread, the frequency of infection waves may decrease as the genetic background of co-circulating variants becomes more similar, reducing the relative growth advantage of new variants. However, the possibility of new variants with higher pathogenicity remains.
• Surveillance Imperative: The study emphasizes that maintaining robust genomic surveillance is essential. It is the only effective method to monitor viral evolution, predict spreading patterns, and mitigate potential public health risks, serving both research and clinical protection purposes.

The authors conclude that the establishment of population immunity has not stopped the virus but has altered its evolutionary path, favoring recombination and high genetic divergence as the mechanisms for sustained transmission.