SARS-CoV-2 Evolution: Implications for Diagnosis, Treatment, Vaccine Effectiveness and Development

Abstract

The COVID-19 pandemic, driven by the rapid evolution of the SARS-CoV-2 virus, presents ongoing challenges to global public health. SARS-CoV-2 is characterized by rapidly evolving mutations, especially in (but not limited to) the spike protein, complicating predictions about its evolutionary trajectory. These mutations have significantly affected transmissibility, immune evasion, and vaccine efficacy, leading to multiple pandemic waves with over half a billion cases and seven million deaths globally. Despite several strategies, from rapid vaccine development and administration to the design and availability of antivirals, including monoclonal antibodies, already having been employed, the persistent circulation of the virus and the emergence of new variants continue to result in high case numbers and fatalities. In the past four years, immense research efforts have contributed much to our understanding of the viral pathogenesis mechanism, the COVID-19 syndrome, and the host-microbe interactions, leading to the development of effective vaccines, diagnostic tools, and treatments. The focus of this review is to provide a comprehensive analysis of the functional impact of mutations on diagnosis, treatments, and vaccine effectiveness. We further discuss vaccine safety in pregnancy and the implications of hybrid immunity on long-term protection against infection, as well as the latest developments on a pan-coronavirus vaccine and nasal formulations, emphasizing the need for continued surveillance, research, and adaptive public health strategies in response to the ongoing SARS-CoV-2 evolution race.

Keywords: COVID-19; SARS-CoV-2; diagnosis; treatments; vaccines; variants.

Figure 1

Diagram of new COVID-19 cases and deaths. The image shows new cases (blue) and deaths (pink) in the United States along a timeline. The vertical lines represent the emergence of the variants of most concern (black font) and vaccine updates available to the population (red font). Data were obtained and modified from the WHO COVID-19 Situation Reports [7].

Figure 2

Genomic phylogeny of SARS-CoV-2 with global subsampling over the past 6 months. This figure presents an unrooted phylogenetic tree depicting the evolutionary relationships among globally circulating SARS-CoV-2 variants. The analysis incorporated viral genomic sequences sampled between December 2019 and September 2024. The phylogeny was built with the online tool nextstrain/ncov [21] and data from the GISAID database [22], updated to 15 October 2024. Variants are indicated with circles and color codes representing the different clades. Only the emerging variant names are indicated. The length of each branch represents the divergence.

Figure 3

COVID-19 genomic sequencing Sankey diagram for the United States. Sankey diagram depicts the relationship between nextclade lineages observed in genomes sequenced from 1 January up to 25 September 2024 in the US (as a reference). The height of each bar represents the relative difference in the sequences for each variant. Data were obtained from gisaid.org [22] and modified by using an online tool [23].

Figure 4

Representation of the SARS-CoV-2 S protein. (A) Schematic primary protein structure and (B) ribbon surface diagram by PyMOL (Schrödinger) using the crystal structure of the S glycoprotein in its closed state (PDB: 6VXX). The antibodies targeted the NTD and RBD with the ACE2 binding sequence, and the main protein domains are consistently indicated in different colors. Single amino acid positions involved in mutations are indicated by purple bars inside the primary structure, with the relative occurrence frequency proportionally represented by the bar height or (C) by different color intensities in the ribbon surface diagram. NTD = N-terminal domain; RBD = receptor-binding domain; CS = protease cleavage site; HR1 = heptad repeat 1; HR2 = heptad repeat 2; TM = transmembrane domain.

Figure 5

Vaccine effectiveness as a function of the viral evolution. This figure shows the relationship between SARS-CoV-2’s antigenic and genetic evolution (S1 mutations and divergence) and the estimated vaccine effectiveness (colored, shaded areas) against different viral variants (green circles). Variants are placed from left to right in order of their evolutionary distance from the original strain (measured by divergence), while each circle’s vertical position indicates the raw number of S1 protein mutations relative to the original strain. The predictions for vaccine effectiveness were inferred based on currently available neutralization and real-world vaccine performance data; they do not represent a single quantitative dataset. Data were obtained and modified from nextstrain/ncov [21] and GISAID [22] against first- (original strain (B)), second- (updated or bivalent (B/BA.1 or BA.4/5)) and third-generation (2024–2025 formula (JN.1)) vaccines.