The DOI matches its Crossref record; 252 of the 252 references it cites were found in a registry or an index.
The evolution of SARS-CoV-2
Open accessAbstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The higher end of the ranges, with evolutionary rates up to 8 × 10 -3 substitutions per site per year, emphasises the potential for SARS-CoV-1 and similar coronaviruses to evolve rapidly, possibly even quicker than SARS-CoV-2.126”
From Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review (2025) · cites this paper as [126]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Hoffmann, M., Kleine-Weber, H., Schroeder, S., Krüger, N., Herrler, T., Erichsen, S., Schiergens, T. S., Herrler, G., Wu, N.-H., Nitsche, A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.02.052 · Cited by 20,286
EVOLUTION IN MENDELIAN POPULATIONS
Wright, S. (1931) · Genetics · doi:10.1093/genetics/16.2.97 · Cited by 9,237
Virological assessment of hospitalized patients with COVID-2019
Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., Niemeyer, D., Jones, T. C., Vollmar, P., Rothe, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2196-x · Cited by 6,661
Origin and evolution of pathogenic coronaviruses
Cui, J., Li, F., & Shi, Z. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0118-9 · Cited by 5,729
Korber, B., Fischer, W. M., Gnanakaran, S., Yoon, H., Theiler, J., Abfalterer, W., Hengartner, N., Giorgi, E. E., Bhattacharya, T., Foley, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.043 · Cited by 4,281
Coronaviruses: An Overview of Their Replication and Pathogenesis
Fehr, A. R., & Perlman, S. M. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-2438-7_1 · Cited by 3,910
Structural basis of receptor recognition by SARS-CoV-2
Shang, J., Ye, G., Shi, K., Wan, Y., Luo, C., Aihara, H., Geng, Q., Auerbach, A., & Li, F. (2020) · Nature · doi:10.1038/s41586-020-2179-y · Cited by 3,661
SARS-CoV-2 variants, spike mutations and immune escape
Harvey, W. T., Carabelli, A. M., Jackson, B., Gupta, R. K., Thomson, E. C., Harrison, E. M., Ludden, C., Reeve, R., Rambaut, A., COVID-19 Genomics UK (COG-UK) Consortium, et al. (2021) · Nature Reviews Microbiology · doi:10.1038/s41579-021-00573-0 · Cited by 3,528
Nextstrain: real-time tracking of pathogen evolutionPreprint
Hadfield, J., Megill, C., Bell, S. M., et al. (2017) · bioRxiv · doi:10.1101/224048 · Cited by 3,172
Nextstrain: real-time tracking of pathogen evolution
Hadfield, J., Megill, C., Bell, S. M., Huddleston, J., Potter, B., Callender, C., Sagulenko, P., Bedford, T., & Neher, R. A. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty407 · Cited by 3,154
Cited by
Sorted by citations
A molnupiravir-associated mutational signature in global SARS-CoV-2 genomes
Sanderson, T., Hisner, R., Donovan-Banfield, I., Hartman, H. B., Løchen, A., Peacock, T. P., & Ruis, C. (2023) · Nature · doi:10.1038/s41586-023-06649-6 · Cited by 219
Implications of diversity in sperm size and function for sperm competition and fertility
Gomendio, M., & Roldán, E. R. S. (2008) · The International Journal of Developmental Biology · doi:10.1387/ijdb.082595mg · Cited by 187
Persistent SARS-CoV-2 infection: significance and implications
Machkovech, H. M., Hahn, A. M., Garonzik‐Wang, J., Grubaugh, N. D., Halfmann, P., Johnson, M. C., Lemieux, J. E., O’Connor, D. H., Piantadosi, A. L., Wei, W., et al. (2024) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(23)00815-0 · Cited by 161
Moodley, A., Stegger, M., BAĞCIGİL, A. F., Baptiste, K. E., Loeffler, A., Lloyd, D. H., Williams, N. J., Leonard, N., Abbott, Y., Skov, R. L., et al. (2006) · Journal of Antimicrobial Chemotherapy · doi:10.1093/jac/dkl394 · Cited by 146
Influenza-associated and COVID-19-associated pulmonary aspergillosis in critically ill patients
Feys, S., Carvalho, A., Clancy, C. J., Gangneux, J., Hoenigl, M., Lagrou, K., Rijnders, B. J. A., Seldeslachts, L., Vanderbeke, L., van de Veerdonk, F. L., et al. (2024) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(24)00151-6 · Cited by 140
Metadata
- Authors
- Markov, P. V., Ghafari, M., Beer, M., Lythgoe, K., Simmonds, P., Stilianakis, N. I., & Katzourakis, A.
- Affiliations
- University of London (GB)
- University of Oxford (GB)
- Friedrich-Loeffler-Institut (DE)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Corresponding author
- Markov, Peter V.
- Katzourakis, Aris
- ORCID
- Venue
- Nature Reviews Microbiology
- Published
- 2023-04-05
- Volume
- 21
- Issue
- 6
- Pages
- 361-379
- ISSN
- 1740-1526 (ISSN-L)
- 1740-1534
- OpenAlex
- W4362609000
- Semantic Scholar
- b6c3324e790174aac7a7b28fcfe0bc22f5461418
- Cited by
- 1,179
- References
- 225
- Citations by year
- 2026: 204 · 2025: 390 · 2024: 441 · 2023: 130
- FWCI
- 55.63
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature Reviews Microbiology (publishedVersion)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- OpenAgrar (submittedVersion)
- Funders
- Wellcome Trust (107652/Z/15/Z)
- H2020 European Research Council (101001623)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Virus Infections Studies
- Keywords
- SARS-CoV-2, viral evolution, genetic variation, variants of concern, antigenic evolution, immune evasion, reinfection, recombination, chronic infection, reservoir hosts, transmissibility, disease severity, COVID-19 pandemic, evolutionary trajectories
- MeSH terms
- COVID-19, SARS-CoV-2, Animals, Genomics, Immune Evasion, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
