PreprintCited by 139SARS-CoV-2 and COVID-19 ResearchCOVID-19 epidemiological studiesCOVID-19 Clinical Research Studies

The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.

Neutralising antibodies predict protection from severe COVID-19

Open access

Cromer, Deborah, Steain, Megan, Reynaldi, Arnold, Schlub, Timothy E, Sasson, Sarah C, Kent, Stephen J, Khoury, David S, Davenport, Miles Philip·2022·Nature Communications

DOI 10.1101/2022.06.09.22275942PMC PMC10036966

Open this paper in CoChat — free account Open PDF

Abstract

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).

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

Crossref · 10.1101/2022.06.09.22275942

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Fig. 1 Summary of previously available data linking neutralising antibodies and vaccine effectiveness and data contributing to this analysis. A Previously reported relationship between neutralising antibody titre and vaccine efficacy in the prevention of symptomatic (dark red) and severe (orange) COVID-19 (reproduced from Khoury et al.4). Solid lines indicate best-fit model and shaded areas indicate 95% confidence intervals. Neutralisation titre and efficacy data used to parameterise the model are indicated as dots (95% CI indicated as whiskers). B–D Summary of the clinical studies used in this analysis (Table 1).CC BY · PubMed Central

Fig. 2 Results of linear mixed effects regression model fit to vaccine effectiveness data against severe COVID-19 extracted from our systematic review. Vaccine effectiveness data against severe COVID-19 (points and whiskers for 95% CI) are shown for pre-Delta (top row, panels (A)–(D), Delta (middle row, panels (E)–(H)) and Omicron (bottom row, panels (I)–(L)) variants. Note that for panels (D) and (I), no effectiveness data was available. Opacity indicates the degree of confidence in the data as determined by the width of the confidence interval. Predicted vaccine effectiveness using a linear mixed effects regression model (solid lines) and 95% confidence intervals (shaded area) are overlaid. The figure shows effectiveness following mRNA-1273 (red), BNT162b2 (blue), any mRNA (purple) and ChAdOx-nCov-1 (pink) vaccination.CC BY · PubMed Central

Fig. 3 Correlation between estimated neutralising antibody titres and vaccine effectiveness. Correlation between estimated neutralising antibody titres (accounting for vaccine used, variant studied and time since vaccination) and clinical data for A vaccine effectiveness against symptomatic SARS-CoV-2 infection, B vaccine effectiveness against severe COVID-19. C Correlation between vaccine effectiveness against symptomatic and severe COVID-19. Solid lines indicate the predicted relationship taken from ref. 4, and shading indicates 95% CI of the model estimates. X-axis confidence intervals in (A) and (B) represent the degree of confidence in the estimate neutralising antibody titre. A breakdown of the relationship shown in panels (A) and (B) by variant and study type is shown in Supplementary Fig. S1. Figure shows effectiveness following mRNA-1273 (red), BNT162b2 (blue), any mRNA (purple) and ChAdOx-nCov-1 (pink) vaccination against pre-Delta (pink background) Delta (blue background) and Omicron (green background) variants.CC BY · PubMed Central

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

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
Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK
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
Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection
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-citation
An 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.”

Show all 53 references

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).

Sorted by citations

Omicron BA.4/BA.5 escape neutralizing immunity elicited by BA.1 infection
Khan, K., Karim, F., Ganga, Y., Bernstein, M. P., Jule, Z., Reedoy, K., Cele, S., Lustig, G., Amoako, D. G., Wolter, N., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32396-9 · Cited by 225
SARS-CoV-2 breakthrough infection induces rapid memory and de novo T cell responses
Koutsakos, M., Reynaldi, A., Lee, W. S., Nguyen, J. T., Amarasena, T. H., Taiaroa, G., Kinsella, P. M., Liew, K. C., Tran, T., Kent, H. E., et al. (2023) · Immunity · doi:10.1016/j.immuni.2023.02.017 · Cited by 112
Self-citation
Predicting the efficacy of variant-modified COVID-19 vaccine boosters
Khoury, D. S., Docken, S. S., Subbarao, K., Kent, S. J., Davenport, M. P., & Cromer, D. (2023) · Nature Medicine · doi:10.1038/s41591-023-02228-4 · Cited by 104
Self-citation
Prior vaccination promotes early activation of memory T cells and enhances immune responses during SARS-CoV-2 breakthrough infection
Painter, M. M., Johnston, T. S., Lundgreen, K. A., Santos, J. J. S., Qin, J. S., Goel, R. R., Apostolidis, S. A., Mathew, D., Fulmer, B., Williams, J. C., et al. (2023) · Nature Immunology · doi:10.1038/s41590-023-01613-y · Cited by 106
Evolution and neutralization escape of the SARS-CoV-2 BA.2.86 subvariant
Khan, K., Lustig, G., Roemer, C., Reedoy, K., Jule, Z., Karim, F., Ganga, Y., Bernstein, M. P., Baig, Z., Jackson, L., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43703-3 · Cited by 93
Monoclonal antibody levels and protection from COVID-19
Stadler, E., Burgess, M. T., Schlub, T. E., Khan, S. R., Chai, K. L., McQuilten, Z., Wood, E. M., Polizzotto, M. N., Kent, S. J., Cromer, D., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40204-1 · Cited by 63
Self-citation
Antibody-independent protection against heterologous SARS-CoV-2 challenge conferred by prior infection or vaccination
Fumagalli, V., Ravà, M., Marotta, D., Lucia, P. D., Bono, E. B., Giustini, L., Leo, F. D., Casalgrandi, M., Monteleone, E., Mouro, V., et al. (2024) · Nature Immunology · doi:10.1038/s41590-024-01787-z · Cited by 61
Study of the mechanism by which Bacillus subtilis improves the soil bacterial community environment in severely saline-alkali cotton fields
Xia, H., Liu, H., Gong, P., Li, P., Xu, Q., Zhang, Q., Sun, M., Meng, Q., Ye, F., & Yin, W. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.178000 · Cited by 47
Immune correlates analysis of a phase 3 trial of the AZD1222 (ChAdOx1 nCoV-19) vaccine
Benkeser, D. C., Fong, Y., Janes, H., Kelly, E. J., Hirsch, I., Sproule, S., Stanley, A. M., Maaske, J., Villafana, T. L., Houchens, C. R., et al. (2023) · npj Vaccines · doi:10.1038/s41541-023-00630-0 · Cited by 41
“Progress in this direction stems from Cromer et al.45 and preceding papers from the Davenport group that developed a model to predict vaccine effectiveness for a given COVID-19 vaccine regimen, time period, and variant, based on the convalescent-sera standardized geometric mean titer of neutralizing antibodies to the…”
ResultInfluential
Predicting Vaccine Effectiveness for Hospitalization and Symptomatic Disease for Novel SARS-CoV-2 Variants Using Neutralizing Antibody Titers
Gardner, B. J., & Kilpatrick, A. M. (2024) · Viruses · doi:10.3390/v16030479 · Cited by 43
Assessing COVID-19 vaccine effectiveness against Omicron subvariants: Report from a meeting of the World Health Organization
Feikin, D. R., Higdon, M. M., Andrews, N., Collie, S., Deloria Knoll, M., Kwong, J. C., Link-Gelles, R., Pilishvili, T., & Patel, M. K. (2023) · Vaccine · doi:10.1016/j.vaccine.2023.02.020 · Cited by 36
Case fatality rates of COVID‐19 during epidemic periods of variants of concern: A meta-analysis by continents
Xia, Q., Yang, Y., Wang, F., Huang, Z., Qiu, W., & Mao, A. (2024) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2024.01.017 · Cited by 38
Likelihood of Post-COVID Condition in people with hybrid immunity; data from the German National Cohort (NAKO)
Mikolajczyk, R., Diexer, S., Klee, B., Pfrommer, L. R., Purschke, O., Fricke, J., Ahnert, P., Gabrysch, S., Gottschick, C., Bohn, B., et al. (2024) · Journal of Infection · doi:10.1016/j.jinf.2024.106206 · Cited by 24
Neutralizing antibody correlate of protection against severe-critical COVID-19 in the ENSEMBLE single-dose Ad26.COV2.S vaccine efficacy trial
Carpp, L. N., Hyrien, O., Fong, Y., Benkeser, D. C., Roels, S., Stieh, D. J., Dromme, I. V., Roey, G. A. V., Kenny, A., Huang, Y., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53727-y · Cited by 22
Modelling the dynamics of infection, waning of immunity and re-infection with the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand
Vattiato, G., Lustig, A. G., Maclaren, O. J., & Plank, M. J. (2022) · Epidemics · doi:10.1016/j.epidem.2022.100657 · Cited by 24
Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes
Xie, J., Mothe, B., Alcalde‐Herraiz, M., Li, C., Xu, Y., Jödicke, A. M., Gao, Y., Wang, Y., Feng, S., Wei, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48339-5 · Cited by 23
COVID-19 vaccine effectiveness and evolving variants: understanding the immunological footprint
Zaeck, L. M., GeurtsvanKessel, C. H., & de Vries, R. D. (2023) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(23)00140-6 · Cited by 22
Discovery of highly potent covalent SARS-CoV-2 3CLpro inhibitors bearing 2-sulfoxyl-1,3,4-oxadiazole scaffold for combating COVID-19
Zhang, F.-M., Huang, T., Wang, F., Zhang, G.-S., Liu, D., Dai, J., Zhang, J., Li, Q., Lin, G., Gao, D., et al. (2023) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2023.115721 · Cited by 21
SARS-CoV-2 infection rates and associated risk factors in healthcare workers: systematic review and meta-analysis
Bansal, A., Trieu, M.-C., Eriksson, E. M., Zhou, F., McVernon, J., Brokstad, K. A., & Cox, R. J. (2025) · Scientific Reports · doi:10.1038/s41598-025-89472-5 · Cited by 20
Comparative duration of neutralizing responses and protections of COVID-19 vaccination and correlates of protection
Liu, C., Tsang, T. K., Sullivan, S. G., Cowling, B. J., & Yang, B. (2025) · Nature Communications · doi:10.1038/s41467-025-60024-9 · Cited by 19
Inference of epidemic dynamics in the COVID-19 era and beyond
Cori, A., & Kucharski, A. J. (2024) · Epidemics · doi:10.1016/j.epidem.2024.100784 · Cited by 18
Original COVID-19 priming regimen impacts the immunogenicity of bivalent BA.1 and BA.5 boosters
Zaeck, L. M., Tan, N. H., Rietdijk, W. J. R., Geers, D., Sablerolles, R. S. G., Bogers, S., van Dijk, L. L. A., Gommers, L., van Leeuwen, L. P. M., Rugebregt, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48414-x · Cited by 18
Deaths averted by vaccination due to reduced transmission can exceed those from direct protection of vaccinated individuals for SARS-CoV-2Preprint
Gardner, B. J., & Kilpatrick, A. M. (2021) · medRxiv · doi:10.1101/2021.10.25.21265500 · Cited by 20
Applying bio-organic fertilizer improved saline alkaline soil properties and cotton yield in Xinjiang
Xia, H., Liu, H., Gong, P., Li, P., Xu, Q., Zhang, Q., Yang, C., & Meng, Q. (2025) · Scientific Reports · doi:10.1038/s41598-025-97776-9 · Cited by 23
Effectiveness of a bivalent mRNA vaccine dose against symptomatic SARS-CoV-2 infection among U.S. Healthcare personnel, September 2022–May 2023
Plumb, I. D., Hagen, M. B., Wiegand, R. E., Dumyati, G. K., Myers, C., Harland, K. K., Krishnadasan, A., James-Gist, J., Abedi, G. R., Fleming-Dutra, K. E., et al. (2023) · Vaccine · doi:10.1016/j.vaccine.2023.10.072 · Cited by 16
Ursodeoxycholic acid does not affect the clinical outcome of SARS‐CoV‐2 infection: A retrospective study of propensity score‐matched cohorts
Marrone, G., Covino, M., Merra, G., Piccioni, A., Amodeo, A., Novelli, A., Murri, R., Pompili, M., Gasbarrini, A., & Franceschi, F. (2023) · Liver International · doi:10.1111/liv.15736 · Cited by 15
Predicting COVID-19 booster immunogenicity against future SARS-CoV-2 variants and the benefits of vaccine updates
Cromer, D., Reynaldi, A., Mitchell, A., Schlub, T. E., Juno, J. A., Wheatley, A. K., Kent, S. J., Khoury, D. S., & Davenport, M. P. (2024) · Nature Communications · doi:10.1038/s41467-024-52194-9 · Cited by 15
Self-citation
Neutralizing antibody levels associated with injectable and aerosolized Ad5-nCoV boosters and BA.2 infection
Wang, F., Huang, B., Deng, Y., Zhang, S., Liu, X., Wang, L., Liu, Q., Zhao, L., Tang, L., Wang, W., et al. (2023) · BMC Medicine · doi:10.1186/s12916-023-02942-3 · Cited by 14
From Detection to Protection: Antibodies and Their Crucial Role in Diagnosing and Combatting SARS-CoV-2
Kumar, A., Tripathi, P., Kumar, P., Shekhar, R., & Pathak, R. (2024) · Vaccines · doi:10.3390/vaccines12050459 · Cited by 17
Omicron COVID-19 immune correlates analysis of a third dose of mRNA-1273 in the COVE trial
Zhang, B., Fong, Y., Fintzi, J., Chu, E., Janes, H., Kenny, A., Carone, M., Benkeser, D. C., van der Laan, L. W. P., Deng, W., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-52348-9 · Cited by 14
Modelling the impact of the Omicron BA.5 subvariant in New Zealand
Lustig, A. G., Vattiato, G., Maclaren, O. J., Watson, L. M., Datta, S., & Plank, M. J. (2023) · Journal of The Royal Society Interface · doi:10.1098/rsif.2022.0698 · Cited by 13
A unique cytotoxic CD4 + T cell‐signature defines critical COVID‐19
Baird, S., Ashley, C. L., Marsh‐Wakefield, F., Alca, S., Ashhurst, T. M., Ferguson, A. L., Lukeman, H., Counoupas, C., Post, J. J., Koneçny, P., et al. (2023) · Clinical & Translational Immunology · doi:10.1002/cti2.1463 · Cited by 12
Self-citation
The impact of Covid-19 vaccination in Aotearoa New Zealand: A modelling study
Datta, S., Vattiato, G., Maclaren, O. J., Hua, N., Sporle, A. A., & Plank, M. J. (2024) · Vaccine · doi:10.1016/j.vaccine.2024.01.101 · Cited by 14
Quantifying how single dose Ad26.COV2.S vaccine efficacy depends on Spike sequence features
Magaret, C. A., Li, L., deCamp, A. C., Rolland, M., Juraska, M., Williamson, B. D., Ludwig, J., Molitor, C., Benkeser, D. C., Luedtke, A. R., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46536-w · Cited by 14
Safety and Immunogenicity of SARS-CoV-2 Recombinant Spike Protein Vaccine in Children and Adolescents in India
Gunale, B., Kapse, D., Kar, S., Bavdekar, A., Kohli, S., Lalwani, S. K., Meshram, S., Raut, A. V., Kulkarni, P., Samuel, C., et al. (2023) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2023.2552 · Cited by 12
Obesity does not influence SARS-CoV-2 humoral vaccine immunogenicity
D’Souza, M., Keeshan, A., Gravel, C. A., Langlois, M., & Cooper, C. (2024) · npj Vaccines · doi:10.1038/s41541-024-01022-8 · Cited by 14
Vaccine-induced T cell responses correlate with reduced risk of severe COVID-19 in a placebo-controlled efficacy trial
Hertoghs, N., Roels, S., Brückner, M., SADOFF, J. C., Banbury, B. L., Akers, N. K., Howie, B., Robins, H. S., Roey, G. A. V., Tolboom, J. T. B. M., et al. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105809 · Cited by 15
Stochastic interventional approach to assessing immune correlates of protection: Application to the COVE messenger RNA-1273 vaccine trial
Hejazi, N. S., Shen, X., Carpp, L. N., Benkeser, D. C., Follmann, D. A., Janes, H., Baden, L. R., Sahly, H. M. E., Deng, W., Zhou, H., et al. (2023) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2023.09.012 · Cited by 11
The Asymptomatic Proportion of SARS‐CoV‐2 Omicron Variant Infections in Households: A Systematic Review
Shi, N. D. J., Marcato, A. J., Spirkoska, V., Meagher, N., Villanueva‐Cabezas, J. P., & Price, D. J. (2024) · Influenza and Other Respiratory Viruses · doi:10.1111/irv.13348 · Cited by 10
Meeting Report From “Correlates of Protection for Next Generation Influenza Vaccines: Lessons Learned From the COVID‐19 Pandemic”
Krammer, F., Katz, J. M., Engelhardt, O. G., Post, D. J., Roberts, P. C., Sullivan, S. G., Tompkins, S. M., Chiu, C., Schultz‐Cherry, S., & Cox, R. J. (2024) · Influenza and Other Respiratory Viruses · doi:10.1111/irv.13314 · Cited by 10
Using machine learning for personalized prediction of longitudinal coronavirus disease 2019 vaccine responses in transplant recipients
Azarfar, G., Sun, Y., Pasini, E., Sidhu, A., Brudno, M., Humar, A., Kumar, D., Bhat, M., Ferreira, V. H., Delisle, J., et al. (2024) · American Journal of Transplantation · doi:10.1016/j.ajt.2024.11.033 · Cited by 12
Retracted
Individual variation in vaccine immune response can produce bimodal distributions of protection
Zachreson, C., Tobin, R. J., Szanyi, J., Walker, C., Cromer, D., Shearer, F. M., Conway, E. J., RYAN, G. E., Cheng, A., McCaw, J. M., et al. (2023) · Vaccine · doi:10.1016/j.vaccine.2023.09.025 · Cited by 9
Self-citation
Single Ad26.COV2.S booster dose following two doses of BBIBP-CorV vaccine against SARS-CoV-2 infection in adults: Day 28 results of a phase 1/2 open-label trial
Muangnoicharoen, S., Wiangcharoen, R., Nanthapisal, S., Kamolratanakul, S., Lawpoolsri, S., Jongkaewwattana, A., Thitithanyanont, A., Luvira, V., Chinwangso, P., Thanthamnu, N., et al. (2023) · Vaccine · doi:10.1016/j.vaccine.2023.06.043 · Cited by 9
Modelling the impact of hybrid immunity on future COVID-19 epidemic waves
Le, T. P., Abell, I. R., Conway, E. J., Campbell, P. T., Hogan, A. B., Lydeamore, M., McVernon, J., Müeller, I., Walker, C. R., & Baker, C. M. (2024) · BMC Infectious Diseases · doi:10.1186/s12879-024-09282-4 · Cited by 10
“Neutralising antibody titres, which are boosted by exposure to infection and/or vaccination, are correlated with efficacy against clinical endpoints of infection, symptoms and severe disease outcomes [15, 16, 17].”
Background
An adjuvanted chimeric spike antigen boosts lung-resident memory T-cells and induces pan-sarbecovirus protective immunity
Counoupas, C., Chan, E., Pino, P., Armitano, J., Johansen, M. D., Smith, L. J., Ashley, C. L., Estapé, E., Troyon, J., Alca, S., et al. (2025) · npj Vaccines · doi:10.1038/s41541-025-01144-7 · Cited by 8
Self-citation
High interleukin-6 levels induced by COVID-19 pneumonia correlate with increased circulating follicular helper T cell frequency and strong neutralization antibody response in the acute phase of Omicron breakthrough infection
Kawasuji, H., Morinaga, Y., Nagaoka, K., Tani, H., Yoshida, Y., Yamada, H., Takegoshi, Y., Kaneda, M., Murai, Y., Kimoto, K., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1377014 · Cited by 8
Immunogenicity of COVID-19 booster vaccination in IEI patients and their one year clinical follow-up after start of the COVID-19 vaccination program
van Leeuwen, L. P. M., Grobben, M., GeurtsvanKessel, C. H., Ellerbroek, P. M., de Bree, G. J., Potjewijd, J., Rutgers, A., Jolink, H., van de Veerdonk, F. L., van Gils, M. J., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1390022 · Cited by 8
Long-term COVID-19 vaccine- and Omicron infection-induced humoral and cell-mediated immunity
Belik, M., Reinholm, A., Kolehmainen, P., Heroum, J., Maljanen, S., Altan, E., Österlund, P., Laine, L., Ritvos, O., Pasternack, A. H., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1494432 · Cited by 9
Prior vaccination enhances immune responses during SARS-CoV-2 breakthrough infection with early activation of memory T cells followed by production of potent neutralizing antibodiesPreprint
Painter, M. M., Johnston, T. S., Lundgreen, K. A., Santos, J. J. D. S., Qin, J. S., Goel, R. R., Apostolidis, S. A., Mathew, D., Fulmer, B., Williams, J. C., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.05.527215 · Cited by 7
Pre-existing and early cellular immune factors correlate with functionally complete protection against primary controlled human SARS-CoV-2 infection
Wagstaffe, H. R., Thwaites, R. S., Sidhu, J. K., Lindeboom, R. G. H., Kretschmer, L., Worlock, K. B., Dratva, L. M., Huang, A., Ascough, S., Papargyris, L., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-67017-8 · Cited by 6
Identification of highly conserved surface-exposed peptides of spike protein for multiepitope vaccine design against emerging omicron variants: An immunoinformatic approach
Khan, M. S., Shakya, M., Verma, C. K., & Mukherjee, R. (2024) · Human Immunology · doi:10.1016/j.humimm.2024.111117 · Cited by 6
Functional and structural investigation of a broadly neutralizing SARS-CoV-2 antibody
Chang, Y.-H., Hsu, M., Chen, W.-N., Wu, M., Kong, W., Lu, M. J., Huang, C.-H., Chang, F.-J., Chang, L., Tsai, H.-Y., et al. (2024) · JCI Insight · doi:10.1172/jci.insight.179726 · Cited by 5
Effects of individual variation and seasonal vaccination on disease risks
Hart, W. S., Amin, J., Park, H., Kitagawa, K., Jeong, Y. D., Kaye, A. R., Iwami, S., & Thompson, R. N. (2025) · Nature Communications · doi:10.1038/s41467-025-63375-5 · Cited by 5
SARS-CoV-2 Neutralization Capacity in Hemodialysis Patients with and without a Fifth Vaccination with the Updated Comirnaty Original/Omicron BA.4-5 Vaccine
Liao, B., Platen, L., Grommes, M., Cheng, C., Holzmann‐Littig, C., Christa, C., Haller, B., Kappler, V., Bester, R., Werz, M. L., et al. (2024) · Vaccines · doi:10.3390/vaccines12030308 · Cited by 5
Comparison of Humoral Response between Third and Fourth Doses of COVID-19 Vaccine in Hemodialysis Patients
Joo, Y., Kim, D. K., Jeon, Y. G., Kim, A., Do, H. N., Yoon, S., Kim, J. S., Jung, S. W., Hwang, H. S., Moon, J.-Y., et al. (2023) · Vaccines · doi:10.3390/vaccines11101584 · Cited by 5
Regional geographies and public health lessons of the COVID-19 pandemic in the Arctic
Tiwari, S., Petrov, A. N., Golosov, N., Devlin, M. K., Mark, W., DeGroote, J. P., Degai, T. S., & Ksenofontov, S. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1324105 · Cited by 6
Projections of the incidence of COVID-19 in Japan and the potential impact of a Fall 2023 COVID-19 vaccine
Kohli, M. A., Maschio, M., Lee, A., & Igarashi, A. (2024) · Vaccine · doi:10.1016/j.vaccine.2024.01.093 · Cited by 5
Longitudinal antibody titers measured after COVID-19 mRNA vaccination can identify individuals at risk for subsequent infection
Park, H., Nakamura, N., Miyamoto, S., Sato, Y., Kim, K. S., Kitagawa, K., Kobashi, Y., Tani, Y., Shimazu, Y., Zhao, T., et al. (2025) · Science Translational Medicine · doi:10.1126/scitranslmed.adv4214 · Cited by 6
Enabling the evaluation of COVID-19 vaccines with correlates of protection
Marchant, A., Damme, P. V., Plotkin, S. A., Neels, P., Cassetti, M. C., Cramer, J. P., Gruber, M. F., Goldblatt, D., King, D., Hartig-Merkel, W., et al. (2023) · Biologicals · doi:10.1016/j.biologicals.2023.101723 · Cited by 6
Australia’s COVID-19 vaccine journey: progress and future perspectives
Triccas, J. A., & Steain, M. C. (2024) · Microbiology Australia · doi:10.1071/ma24009 · Cited by 4
Self-citation
Optimisation of a multiplexed, high throughput assay to measure neutralising antibodies against SARS-CoV-2 variants
Ashley, C. L., Bloul, M., Alca, S., Smith, L., Jin, W., Khoury, D. S., Counoupas, C., Davenport, M. P., Triccas, J. A., & Steain, M. C. (2024) · Journal of Virological Methods · doi:10.1016/j.jviromet.2024.115073 · Cited by 4
Self-citation
Effectiveness of COVID-19 Vaccines Over Time Against Clinical and Radiologic Outcomes Related to Severe SARS-CoV-2 Infection
Lee, J. E., Jin, K. N., Hong, H., Jeong, Y. J., & Yoon, S. H. (2024) · Radiology · doi:10.1148/radiol.231928 · Cited by 4
The Effectiveness of the Third Dose of COVID-19 Vaccine: When Should It Be Performed?
Biganzoli, G., Mendola, M., Perrone, P. M., Antonangeli, L. M., Longo, A. B. E., Carrer, P., Colosio, C., Consonni, D., Marano, G., Boracchi, P., et al. (2024) · Vaccines · doi:10.3390/vaccines12030315 · Cited by 4
Should SARS-CoV-2 serological testing be used in the decision to deliver a COVID-19 vaccine booster? A pro-con assessment
Augello, M., Wagenhäuser, I., Krone, M., Dauby, N., Ferrara, P., Sabbatucci, M., Ruță, S. M., Rezahosseini, O., Velikov, P., Gkrania‐Klotsas, E., et al. (2024) · Vaccine · doi:10.1016/j.vaccine.2024.126184 · Cited by 4
Association between ursodeoxycholic acid use and COVID-19 in individuals with chronic liver disease: a nationwide case-control study in South Korea
Moon, S. Y., Son, M., Kang, Y. W., Koh, M., Lee, J. Y., & Baek, Y. H. (2024) · Virology Journal · doi:10.1186/s12985-024-02464-1 · Cited by 3
Impact of pre-Omicron COVID-19 vaccine boosters on the risk of Omicron variant infections: A systematic review and meta-regression
Pan, B.-Y., Tseng, I., Feng, Y. A., & Fang, C. (2025) · Journal of the Formosan Medical Association · doi:10.1016/j.jfma.2025.04.002 · Cited by 3
Clinical characteristics, SARS-CoV-2 variants, and outcomes of adults hospitalized due to COVID-19 in Latin American countries
López-Macías, C. I. R., López-Medina, E., Alves, M. B., Matos, A. D. R., Hernández-Villena, J. V., Torres, Z. A., Sarabia, L. E., Manrique-Ramirez, P., Tejado-Gallegos, L. F., Ramirez, L., et al. (2025) · Clinics · doi:10.1016/j.clinsp.2025.100648 · Cited by 3
The Mirror of Erised: a retrospective population-wide study of Czech all-cause mortality data by COVID-19 vaccination status
Vencálek, O., Fürst, T., Princova, E., & Fürstová, J. (2025) · BMC Public Health · doi:10.1186/s12889-025-23619-x · Cited by 3
Neutralizing and binding antibodies are a correlate of risk of COVID-19 in the CoVPN 3008 study in people with HIV
Mkhize, N. N., Zhang, B., Brackett, C., Elyanu, P., Tapley, A., Dadabhai, S. S., Hu, J., Do, B. T. N., Schuster, D. J., Heptinstall, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63948-4 · Cited by 3
Antibody Titers and the Risk of Infection During the SARS-CoV-2 Omicron Phase in Bizen City, Japan
Kadowaki, T., Sasaki, A., Matsumoto, N., Mitsuhashi, T., Hagiya, H., Takao, S., & Yorifuji, T. (2024) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiae207 · Cited by 6
Early antiviral CD4 and CD8 T cell responses and antibodies are associated with upper respiratory tract clearance of SARS-CoV-2Preprint
Ramirez, S. I., Lopez, P. G., Faraji, F., Parikh, U. M., Heaps, A., Ritz, J., Moser, C., Eron, J. J., Wohl, D. A., Currier, J. S., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.25.564014 · Cited by 3
Clinical and Economic impact of updated Fall 2023 COVID-19 vaccines in the Immunocompromised Population in CanadaPreprint
Lee, A. S., Jayasundara, K., Kohli, M. A., Maschio, M., Fust, K., Joshi, K., de Velde, N. V., & Beck, E. C. (2023) · medRxiv · doi:10.1101/2023.11.10.23298369 · Cited by 3
T cell-mediated protection in absence of virus neutralizing antibodies
Alpizar, Y. A., & Dallmeier, K. (2025) · Nature Microbiology · doi:10.1038/s41564-024-01921-5 · Cited by 2
Reverse vaccinology-based multi-epitope COVID-19 vaccine targeting SARS-CoV-2 structural and non-structural proteins induces immune responses in mice
Fibriani, A., Yamahoki, N., Shani, A. M., Rofiqoh, A., Siregar, A. L. F., Gunawan, C., Mayorga, C. G. D., Tjia, T. O. S., Nugrahapraja, H., Giri-Rachman, E. A., et al. (2025) · Vaccine X · doi:10.1016/j.jvacx.2025.100632 · Cited by 2
Putting computational models of immunity to the test—An invited challenge to predict B.pertussis vaccination responses
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. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012927 · Cited by 2
Immune Response Against Recent Omicron Sub-Lineages in Persons with HIV Receiving a Protein-Based or mRNA XBB.1.5 SARS-CoV-2 Booster Vaccine
Vergori, A., Matusali, G., Cimini, E., Cozzi‐Lepri, A., Mazzotta, V., Mariotti, D., Colavita, F., Gili, S., Cristofanelli, F., Fusto, M., et al. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26083521 · Cited by 2
Impact of vaccination on SARS-CoV-2 infections and long COVID symptoms: a cross-sectional study in China
Yan, X., Zhao, X., Wang, H. B., Du, Y., Liu, L., Liu, J., Wang, Q., & Wei, S. (2025) · BMC Infectious Diseases · doi:10.1186/s12879-025-11677-w · Cited by 2
Modelling the interaction between ethnicity and infectious disease transmission dynamics in Aotearoa New Zealand during the first Omicron wave of the COVID-19 pandemic
Lomas, V. X., Chambers, T. J., & Plank, M. J. (2025) · Mathematics in Medical and Life Sciences · doi:10.1080/29937574.2025.2591407 · Cited by 2
COVID-19 convalescent plasma safety and efficacy analysis for biologics license application approval
Sullivan, D. J., Reik, R., Prichard, A. B., Pagan, M., Tobian, A. A. R., Caturegli, P., Pekosz, A. S., Klein, S. L., Bloch, E. M., Shoham, S., et al. (2026) · Expert Review of Anti-infective Therapy · doi:10.1080/14787210.2026.2623136 · Cited by 2
Immune responses associated with protection from SARS-CoV-2 infection
Reynaldi, A., Lee, W. S., Selva, K. J., Audsley, J., Trieu, M.-C., Chung, A. W., Cromer, D., Tan, H., Wheatley, A. K., Juno, J. A., et al. (2026) · Vaccine · doi:10.1016/j.vaccine.2026.128579 · Cited by 2
Self-citation
An optimal control model with contact restrictions applied to COVID-19 pandemic
Lv, W., & Xu, M. (2024) · Journal of Industrial and Management Optimization · doi:10.3934/jimo.2024068 · Cited by 2
Kinetics of SARS-CoV-2 antibody titers after booster vaccinations during an Omicron surge in Japan
Matsumoto, N., Sasaki, A., Kadowaki, T., Mitsuhashi, T., Takao, S., & Yorifuji, T. (2024) · Vaccine · doi:10.1016/j.vaccine.2024.126156 · Cited by 3
Comparison of Phenotypes of Headaches After COVID-19 Vaccinations Differentiated According to the Vaccine Used
Göbel, C. H., Heinze, A., Heinze‐Kuhn, K., Karstedt, S. C., Morscheck, M., Tashiro, L., Cirkel, A., Hamid, Q. A., Halwani, R., Temsah, M.-H. A., et al. (2025) · Vaccines · doi:10.3390/vaccines13020113 · Cited by 2
A humanised ACE2, TMPRSS2, and FCGRT mouse model reveals the protective efficacy of anti-receptor binding domain antibodies elicited by SARS-CoV-2 hybrid immunity
Ana‐Sosa‐Batiz, F., Verma, S. K., Shafee, N., Miller, R., Conner, C., Hastie, K. M., Timis, J., Maule, E., Nguyen, M. N., Tran, L., et al. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105619 · Cited by 2
Estimated US Trends in SARS-CoV-2 Spike Antibody Concentrations and Correlation to Risk of First-Time Infections Based on Blood Donations, 2022
Jones, J. M., Grebe, E., Lartey, I., Stone, M., Spencer, B. R., Akinseye, A., Manrique, I. M., Fink, R. V., Green, V., Saá, P., et al. (2025) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiaf329 · Cited by 2
Modelling the impact of hybrid immunity on future COVID-19 epidemic wavesPreprint
Le, T. P., Abell, I. R., Conway, E. J., Campbell, P. T., Hogan, A. B., Lydeamore, M., McVernon, J., Müeller, I., Walker, C. R., & Baker, C. M. (2023) · medRxiv · doi:10.1101/2023.03.12.23287174 · Cited by 2
Emergence of neutralizing antibodies associates with clearance of SARS-CoV-2 during HIV-mediated immunosuppressionPreprint
Karim, F., Bernstein, M. P., Jule, Z., Lustig, G., Upton, J., Ganga, Y., Khan, K., Reedoy, K., Mazibuko, M., Govender, K., et al. (2023) · medRxiv · doi:10.1101/2023.08.18.23293746 · Cited by 2
Vaccine-induced SARS-CoV-2 antibody response: the comparability of S1-specific binding assays depends on epitope and isotype discrimination
Schest, S., Langer, C., Stiegler, Y., Karnuth, B., Arends, J. P., Stiegler, H., Masetto, T., Peter, C., & Grimmler, M. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1257265 · Cited by 1
Predictors of Long COVID Among Symptomatic US Adults Testing Positive for SARS-CoV-2 at a National Retail Pharmacy
Sun, X., Fusco, M. D., Lupton, L. L., Yehoshua, A., Alvarez, M. B., Allen, K. E., Puzniak, L., Lopez, S. M. C., & Cappelleri, J. C. (2024) · Healthcare · doi:10.3390/healthcare12232321 · Cited by 3
Antibody Levels From High-Throughput Variant-Specific SARS-CoV-2 Anti-Spike Immunoglobulin G and Angiotensin-Converting Enzyme 2 Neutralization Assays Correlate With COVID-19 Infection Risk in a Large Population
Jacobs, M. B., Clark, A. E., Goldhaber, N. H., Valentine, H. D., Rivera, A., Ngo, T., Barber, T., Holmes, J., Manfredi, B., Garretson, A. F., et al. (2024) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiae622 · Cited by 2
Personalized prediction of SARS-CoV-2 vaccine-induced immunity after boost: a longitudinal analysis using joint modeling
Papadopoulos, I., Diep, A. N., Schyns, J., Gourzonès, C., Minner, F., Bonhomme, G., Paridans, M., Gillain, N., Husson, E., Garigliany, M., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1619631 · Cited by 1
Dysregulated inflammation in solid tumor malignancy patients shapes polyfunctional antibody responses to COVID-19 vaccination
Purcell, R. A., Koutsakos, M., Kedzierski, Ł., Allen, L. F., Williams, O., Wang, J.-W. D., Cavic, G., Wheatley, A. K., Lee, W. S., Wines, B. D., et al. (2025) · npj Vaccines · doi:10.1038/s41541-025-01268-w · Cited by 5
Self-citation
Longitudinal monitoring of cellular immunity by the ex vivo activation of genes in leukocytes (EAGL) assay highlights potential markers of mRNA COVID-19 vaccine efficacy against breakthrough symptoms
Saito, T., Couzinet, A., Suzuki, T., Shimomura, M., Ryo, A., Miyakawa, K., Katayama, Y., & Nakatsura, T. (2025) · Vaccine · doi:10.1016/j.vaccine.2025.127942 · Cited by 2
Antibody responses following COVID-19 vaccination and breakthrough infections in naïve and convalescent individuals suggest imprinting to the ancestral strain of SARS-CoV-2
Mahanty, S., Eriksson, E. M., Edler, P., Mordant, F. L., Kiernan‐Walker, N., Price, D. J., Braat, S., Conway, E. J., Bryant, V. L., Ding, H., et al. (2025) · mBio · doi:10.1128/mbio.03221-25 · Cited by 1
Humoral and cellular immunogenicity of sequential heterogeneous bivalent SARS-CoV-2 vaccinations in long-term care and retirement home residents
Breznik, J. A., Ang, J. C., Bhakta, H., Liu, L.-M., Bilaver, L., Kennedy, A. E., Cowbrough, B., Rahim, A., Clare, R., Bramson, J. L., et al. (2025) · Vaccine · doi:10.1016/j.vaccine.2025.128160 · Cited by 1
Predictive biomarkers and specific immune responses of COVID-19 mRNA vaccine in patients with cancer: prospective results from the CACOV-VAC trial
Spehner, L., Orillard, É., Falcoz, A., Lepiller, Q., Bouard, A., Almotlak, H., Kim, S. C. H., Curtit, E., Meynard, G., Jary, M., et al. (2023) · BMJ Oncology · doi:10.1136/bmjonc-2023-000054 · Cited by 1
Design, synthesis, and biological evaluation of novel 2′-deoxy-2′-spirooxetane-7-deazapurine nucleoside analogs as anti-SARS-CoV-2 agents
Gao, M., Zhang, Z., Yao, G., Zhang, L., Duan, A., Zhang, Y., Wang, Y., Zhao, J., & Zhang, J. (2024) · Antiviral Research · doi:10.1016/j.antiviral.2024.106060 · Cited by 1
SARS-CoV-2 neutralizing antibody determination after vaccination using spectrophotometric measurement of lateral flow immunochromatography
Ma, J., Kaniper, S., Vabishchevich, Y., Nyantakyi, N., Lynch, D., Chun, F., Dai, H., & Gerhard, G. S. (2025) · Scientific Reports · doi:10.1038/s41598-025-90730-9 · Cited by 1
Mental health and psychosocial factors predicting concerns about the COVID-19 vaccine among refugee background and Australian-born women
Lupton, D. A., Whitten, T., Tay, A. K., Beek, K., Green, M. J., Hassoun, F., Moussa, B., Silove, D. M., & Rees, S. J. (2025) · Vaccine · doi:10.1016/j.vaccine.2025.127251 · Cited by 1
National- and State-level SARS-CoV-2 Immunity Trends From January 2020 to December 2023: a Mathematical Modeling Analysis
Klaassen, F., Swartwood, N. A., Chitwood, M. H., Lopes, R., Haraguchi, M., Salomon, J. A., Cohen, T., & Menzies, N. A. (2025) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiaf532 · Cited by 2

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: Cromer, Deborah
Steain, Megan
Reynaldi, Arnold
Schlub, Timothy E
Sasson, Sarah C
Kent, Stephen J
Khoury, David S
Davenport, Miles Philip
Venue: Nature Communications
Publisher: openRxiv
Published: 2022-06-14
Volume: 14
Issue: 1
Pages: 1633-1633
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1101/2022.06.09.22275942
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

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

Neutralising antibodies predict protection from severe COVID-19

Abstract

Overview

Integrity signals

Figures

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks