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Neutralising antibodies predict protection from severe COVID-19
Open accessAbstract
Background: Vaccine protection from COVID-19 has been shown to decline with time-since-vaccination and against SARS-CoV-2 variants. Protection against severe COVID-19 is higher than against symptomatic infection, and also appears relatively preserved over time and against variants. Although Protection protection from symptomatic SARS-CoV-2 infection has been shown to be strongly correlated with neutralising antibody titres, however, this relationship has been is less well described for severe COVID-19. Protection against severe COVID-19 is higher than against symptomatic infection, and also appears relatively preserved over time and against variants. Here we analyse whether neutralising antibody titre remains predictive of protection against severe COVID-19 in the face of waning neutralising antibody levels and emerging variants. Methods: We extracted data from 15 studies reporting on protection against a range of SARS-CoV-2 clinical endpoints ("any infection", "symptomatic infection" and "severe COVID-19"). We then estimated the concurrent neutralising antibody titres using existing parameters on vaccine potency, neutralising antibody decay, and loss of recognition of variants and investigated the relationship between neutralising antibody titre and vaccine effectiveness against severe COVID-19. Findings: Predicted neutralising antibody titres are strongly correlated with vaccine effectiveness against symptomatic and severe COVID-19 (Spearman rho = .94 and 0.63 respectively, p<.001 for both), consistent with previous estimates of the relationship between neutralisation and protection. Indeed 82% (137 of 167) of reported values of protection against severe COVID-19 across a range of vaccines and variants lie within the 95% confidence intervals of the published model. Interpretation: Neutralising antibody titres are predictive of vaccine effectiveness against severe COVID-19 including in realistic scenarios of waning immunity and viral variants. Funding: National Health and Medical Research Council (Australia), Medical Research Future Fund (Australia).
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“It has been postulated that neutralizing antibodies can also protect against severe disease, albeit at lower concentrations than needed to protect against symptomatic disease [36]”
From Assessing COVID-19 vaccine effectiveness against Omicron subvariants: Report from a meeting of the World Health Organization (2023) · cites this paper as [36]
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Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine
Polack, F. P., Thomas, S. J., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Perez, J. L., Pérez Marc, G., Moreira, E. D., Zerbini, C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2034577 · Cited by 14,592
Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
Baden, L. R., El Sahly, H. M., Essink, B., Kotloff, K., Frey, S., Novak, R., Diemert, D., Spector, S. A., Rouphael, N., Creech, C. B., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2035389 · Cited by 10,119
Voysey, M., Clemens, S. A. C., Madhi, S. A., Weckx, L. Y., Folegatti, P. M., Aley, P. K., Angus, B., Baillie, V. L., Barnabas, S. L., Bhorat, Q. E., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32661-1 · Cited by 4,616
Khoury, D. S., Cromer, D., Reynaldi, A., Schlub, T. E., Wheatley, A. K., Juno, J. A., Subbarao, K., Kent, S. J., Triccas, J. A., & Davenport, M. P. (2021) · Nature Medicine · doi:10.1038/s41591-021-01377-8 · Cited by 3,742 · cited 1×
“MMWR Morb Mortal Wkly Rep 2022; 71(4): 139-45.”
Self-citationAn mRNA Vaccine against SARS-CoV-2 — Preliminary Report
Jackson, L. A., Anderson, E. J., Rouphael, N. G., Roberts, P. C., Makhene, M., Coler, R. N., McCullough, M. P., Chappell, J. D., Denison, M. R., Stevens, L. J., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2022483 · Cited by 3,237
Immunological memory to SARS-CoV-2 assessed for up to 8 months after infection.
Dan, J. M., Mateus, J., Kato, Y., Hastie, K. M., Yu, E. D., Faliti, C. E., Grifoni, A., Ramirez, S. I., Haupt, S., Frazier, A., et al. (2021) · Science · doi:10.1126/science.abf4063 · Cited by 2,656
RNA-Based COVID-19 Vaccine BNT162b2 Selected for a Pivotal Efficacy Study
Walsh, E. E., Frenck, R., Falsey, A. R., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Neuzil, K., Mulligan, M. J., Bailey, R., et al. (2020) · doi:10.1101/2020.08.17.20176651 · Cited by 2,615
Effectiveness of COVID-19 vaccines against the Omicron (B.1.1.529) variant of concern
Andrews, N., Stowe, J., Kirsebom, F., Toffa, S., Rickeard, T., Gallagher, E., Gower, C., Kall, M., Groves, N., O’Connell, A.-M., et al. (2021) · doi:10.1101/2021.12.14.21267615 · Cited by 2,420
Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine through 6 Months
Thomas, S. J., Moreira, E. D., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Perez, J. L., Pérez Marc, G., Polack, F. P., Zerbini, C., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2110345 · Cited by 1,640
Covid-19 Breakthrough Infections in Vaccinated Health Care Workers
Bergwerk, M., Gonen, T., Lustig, Y., Amit, S., Lipsitch, M., Cohen, C., Mandelboim, M., Levin, E. G., Rubin, C., Indenbaum, V., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2109072 · Cited by 1,345 · cited 1×
“MMWR Morb Mortal Wkly Rep 2022; 71(7): 255-63.”
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Research works printed but not linked: 3
- [36]Walsh EE Safety and immunogenicity of two RNA-based Covid-19 vaccine candidates N. Engl. J. Med. 2020 383 2439 2450 10.1056/NEJMoa2027906 33053279 PMC7583697 · DOI · Paper page
- [39]Stadler, E. et al. Determinants of passive antibody effectiveness in SARS-CoV-2 infection. Preprint at medRxiv10.1101/2022.1103.1121.22272672 (2022).
- [47]Andrews, N. et al. Effectiveness of COVID-19 vaccines against the Omicron (B.1.1.529) variant of concern. Preprint at medRxiv10.1101/2021.1112.1114.21267615 (2021).
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Shinde, P. S., Willemsen, L., Anderson, M., Aoki, M., Basu, S., Burel, J. G., Cheng, P., Dastidar, S. G., Dunleavy, A., Einav, T., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.04.611290 · Cited by 1
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Bansal, A., Trieu, M.-C., Eriksson, E. M., Zhou, F., McVernon, J., Brokstad, K. A., & Cox, R. J. (2024) · Research Square · doi:10.21203/rs.3.rs-4602421/v1
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Bansal, A., Trieu, M.-C., Eriksson, E. M., Zhou, F., McVernon, J., Brokstad, K. A., & Cox, R. J. (2024) · Research Square · doi:10.21203/rs.3.rs-4602421/v2
Kumaravel, S. K., Nagaram, N. B., Murugesan, R., Mohan, K. R., & Rasappan, S. (2024) · Springer proceedings in physics · doi:10.1007/978-3-031-69146-1_44
Reinhart, A. M., Tian, Y., & Lilly, A. E. (2025) · Health Communication · doi:10.1080/10410236.2025.2485296
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Yuan, X., Zhang, L., Chen, K., Chu, Q., Lei, L., Li, J., Feng, W., Cheng, Z., Wang, X., Yang, Y., et al. (2025) · International Journal of Surgery · doi:10.1097/js9.0000000000004407
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Mortari, E. P., Laffranchi, M., Cinicola, B. L., Sugoni, C., Barresi, S., Marcellini, V., Agolini, E., Albano, C., Volpe, G., Scarsella, M., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.17.719191
Liu, H., Mou, X., Wang, Y., & Qian, D. (2026) · Research Square · doi:10.21203/rs.3.rs-9457087/v1
Kohli, M. A., Maschio, M., Lee, A., Kissler, S. M., Carroll, S., van de Velde, N. C., Beck, E. C., BALOGH, O., & Joshi, K. (2026) · Vaccine · doi:10.1016/j.vaccine.2026.128687
Liu, C., Okoli, G. N., Chen, R. Y. L., Sullivan, S. G., & Cowling, B. J. (2026) · Clinical Infectious Diseases · doi:10.1093/cid/ciag346 · Cited by 1
Uppuluri, V. (2026) · International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV) · doi:10.1109/icicv68925.2026.11554636
Derakhshani, L., Feddern, S., Grüne, B., Haberstock, L., Kossow, A., Nießen, J., Rost, S., Wiesmüller, G. A., Schmidt, N., & Joisten, C. (2026) · BMC Public Health · doi:10.1186/s12889-026-28249-5
Jaishwal, P., & Singh, S. P. (2026) · Biophysica · doi:10.3390/biophysica6040055
D'Avanzo, M., Myint, A. P., Cacciapaglia, G., Hohenegger, S., Conventi, F., & Nunes, M. C. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1014707
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Metadata
- Authors
- Cromer, D., Steain, M., Reynaldi, A., Schlub, T. E., Sasson, S. C., Kent, S. J., Khoury, D. S., & Davenport, M. P.
- Affiliations
- UNSW Sydney (AU)
- The University of Sydney (AU)
- The University of Melbourne (AU)
- Corresponding author
- Cromer, Deborah
- ORCID
- Venue
- Nature Communications
- Publisher
- openRxiv
- Published
- 2022-06-14
- Volume
- 14
- Issue
- 1
- Pages
- 1633-1633
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC10036966
- OpenAlex
- W4360871696
- Cited by
- 139
- References
- 53
- Citations by year
- 2026: 15 · 2025: 40 · 2024: 50 · 2023: 30 · 2022: 3
- FWCI
- 6.39
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Nature Communications (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- University of New South Wales
- Medical Research Council
- National Health and Medical Research Council (1149990, 1136452, 1173528)
- Medical Research Future Fund
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- COVID-19 vaccine effectiveness, severe COVID-19, SARS-CoV-2, neutralizing antibodies, antibody waning, SARS-CoV-2 variants of concern, time since vaccination, vaccine regimens, symptomatic infection
- MeSH terms
- COVID-19, SARS-CoV-2, Vaccine Efficacy, Antibodies, Viral, Humans, Vaccination, Antibodies, Neutralizing
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