The DOI matches its Crossref record; 63 of the 65 references it cites were found in a registry or an index.
Efficacy of SARS-CoV-2 vaccines and the dose–response relationship with three major antibodies: a systematic review and meta-analysis of randomised controlled trials
Open accessAbstract
BACKGROUND: The efficacy of SARS-CoV-2 vaccines in preventing severe COVID-19 illness and death is uncertain due to the rarity of data in individual trials. How well the antibody concentrations can predict the efficacy is also uncertain. We aimed to assess the efficacy of these vaccines in preventing SARS-CoV-2 infections of different severities and the dose-response relationship between the antibody concentrations and efficacy. METHODS: We did a systematic review and meta-analysis of randomised controlled trials (RCTs). We searched PubMed, Embase, Scopus, Web of Science, Cochrane Library, WHO, bioRxiv, and medRxiv for papers published between Jan 1, 2020 and Sep 12, 2022. RCTs on the efficacy of SARS-CoV-2 vaccines were eligible. Risk of bias was assessed using the Cochrane tool. A frequentist, random-effects model was used to combine efficacy for common outcomes (ie, symptomatic and asymptomatic infections) and a Bayesian random-effects model was used for rare outcomes (ie, hospital admission, severe infection, and death). Potential sources of heterogeneity were investigated. The dose-response relationships of neutralising, spike-specific IgG and receptor binding domain-specific IgG antibody titres with efficacy in preventing SARS-CoV-2 symptomatic and severe infections were examined by meta-regression. This systematic review is registered with PROSPERO, CRD42021287238. FINDINGS: 28 RCTs (n=286 915 in vaccination groups and n=233 236 in placebo groups; median follow-up 1-6 months after last vaccination) across 32 publications were included in this review. The combined efficacy of full vaccination was 44·5% (95% CI 27·8-57·4) for preventing asymptomatic infections, 76·5% (69·8-81·7) for preventing symptomatic infections, 95·4% (95% credible interval 88·0-98·7) for preventing hospitalisation, 90·8% (85·5-95·1) for preventing severe infection, and 85·8% (68·7-94·6) for preventing death. There was heterogeneity in the efficacy of SARS-CoV-2 vaccines against asymptomatic and symptomatic infections but insufficient evidence to suggest whether the efficacy could differ according to the type of vaccine, age of the vaccinated individual, and between-dose interval (p>0·05 for all). Vaccine efficacy against symptomatic infection waned over time after full vaccination, with an average decrease of 13·6% (95% CI 5·5-22·3; p=0·0007) per month but can be enhanced by a booster. We found a significant non-linear relationship between each type of antibody and efficacy against symptomatic and severe infections (p<0·0001 for all), but there remained considerable heterogeneity in the efficacy, which cannot be explained by antibody concentrations. The risk of bias was low in most studies. INTERPRETATION: The efficacy of SARS-CoV-2 vaccines is higher for preventing severe infection and death than for preventing milder infection. Vaccine efficacy wanes over time but can be enhanced by a booster. Higher antibody titres are associated with higher estimates of efficacy but precise predictions are difficult due to large unexplained heterogeneity. These findings provide an important knowledge base for interpretation and application of future studies on these issues. FUNDING: Shenzhen Science and Technology Programs.
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 cited source says what the claim attributes to it.
In the citing paper
“In our review, we found a pooled VE of 71% against SARS-CoV-2 infection, whereas systematic reviews of randomised clinical trials reported higher pooled vaccine efficacy of 83% [26] and 77% [27].”
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
GRADE: an emerging consensus on rating quality of evidence and strength of recommendations
Guyatt, G. H., Oxman, A. D., Vist, G. E., Kunz, R., Falck-Ytter, Y., Alonso-Coello, P., & Schünemann, H. J. (2008) · BMJ · doi:10.1136/bmj.39489.470347.ad · Cited by 23,305
Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n160 · Cited by 13,262
Gelman, A. (2006) · Bayesian Analysis · doi:10.1214/06-ba117a · Cited by 4,050
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
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 Single-Dose Ad26.COV2.S Vaccine against Covid-19
Sadoff, J., Gray, G., Vandebosch, A., Cárdenas, V., Shukarev, G., Grinsztejn, B., Goepfert, P. A., Truyers, C., Fennema, H., Spiessens, B., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2101544 · Cited by 2,397
Logunov, D. Y., Dolzhikova, I. V., Shcheblyakov, D. V., Tukhvatulin, A. I., Zubkova, O. V., Dzharullaeva, A. S., Kovyrshina, A. V., Lubenets, N. L., Grousova, D. M., Erokhova, A. S., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)00234-8 · Cited by 1,747
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
Efficacy of the ChAdOx1 nCoV-19 Covid-19 Vaccine against the B.1.351 Variant
Madhi, S. A., Baillie, V., Cutland, C. L., Voysey, M., Koen, A. L., Fairlie, L., Padayachee, S. D., Dheda, K., Barnabas, S. L., Bhorat, Q. E., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2102214 · Cited by 1,257
Feikin, D. R., Higdon, M. M., Abu-Raddad, L. J., Andrews, N., Araos, R., Goldberg, Y., Groome, M. J., Huppert, A., O'Brien, K. L., Smith, P. G., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(22)00152-0 · Cited by 1,237
Research works printed but not linked: 1
- Andrews, 2022, COVID-19 vaccine effectiveness against the omicron (B.1.1.529) variant, N Engl J Med, 386, 1532, 10.1056/NEJMoa2119451 · DOI · Paper page
Cited by
Sorted by citations
Items 101–138 of 138
Perspectives regarding COVID-19 vaccination among unvaccinated persons with mental illness
Shankarappa, A. C. S., Gopalakrishanan, R., Thangadurai, P., & Kuruvilla, A. (2024) · Industrial Psychiatry Journal · doi:10.4103/ipj.ipj_7_24
The Omicron Paradox: Is It Omicron or Is It What Happened During the Omicron Period?*
Kawano-Dourado, L. B., & Zeraatkar, D. (2024) · Critical Care Medicine · doi:10.1097/ccm.0000000000006295
Vaccination against COVID-19 in a post-pandemic era
Neto, F. L., Ceccato, A., & Ranzani, O. (2024) · European Respiratory Society eBooks · doi:10.1183/2312508x.10020223
Ariawan, I. M. D., Sawitri, A. A. S., Yuliyatni, P. C. D., Widyanthini, D. N., & Sutarsa, I. N. (2024) · Australian Journal of Primary Health · doi:10.1071/py24014
Paula, N. M., Joucoski, E., Baura, V. A., de Souza, E. M., Pedrosa, F. O., Gonçalves, A. G., & Huergo, L. F. (2024) · Vaccines · doi:10.3390/vaccines12101149
On the Nature of the Interactions That Govern COV-2 Mutants Escape from Neutralizing Antibodies
Sussman, F., & Villaverde, D. S. (2024) · Molecules · doi:10.3390/molecules29215206
Syed, A. A., Eqbal, F., Shamsi, H. R., Syed, A. R. S., Zakir, S. J., Fawzy, M., & Khan, K. S. (2024) · Medicina de Familia SEMERGEN · doi:10.1016/j.semerg.2024.102343
Sheehan, J., Trauth, A. J., Hagensee, M. E., & Ramsay, A. J. (2025) · Pathogens · doi:10.3390/pathogens14010044
Kansal, V., & Pandey, P. K. (2025) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2025.3552579
La vacunación como estrategia para el control de la pandemia por SARS-CoV-2
Navarro-Alonso, J.-A. (2025) · Vacunas · doi:10.1016/j.vacun.2025.500429
Soeorg, H., Päll, T., Abroi, A., Avi, R., Sadikova, O., Härma, M.-A., Reisberg, T., Lutsar, I., & Huik, K. (2025) · PLoS ONE · doi:10.1371/journal.pone.0327719
Soubgui, A. F. M., Foko, L. P. K., Lemouchele, I. N., Enyegue, E. L. E., & Mogtomo, M. L. K. (2025) · Health Science Reports · doi:10.1002/hsr2.71068
Vaccination as a strategy to control SARS-CoV-2 pandemic
Navarro-Alonso, J.-A. (2025) · Vacunas (English Edition) · doi:10.1016/j.vacune.2025.500429
Dhayfule, D., Wu, Y.-H., Ashyani, A., Li, M.-C., Tsai, C.-S., Chen, P., & Nordling, T. E. M. (2025) · BMC Infectious Diseases · doi:10.1186/s12879-025-11289-4
A systematic review and meta-analysis of risk factors for long COVIDPreprint
Nakagawara, K., Otake, S., Horita, N., Namkoong, H., Terai, H., Takemura, R., Nagashima, K., Chubachi, S., & Fukunaga, K. (2025) · Research Square · doi:10.21203/rs.3.rs-7667974/v1
Nikoloudis, D., Konstantinakou, K. E., Konstantinidis, A. D., Spyrou, N. I., Vasileiou, I. V., Tsakris, A., & Pitiriga, V. C. (2025) · Vaccines · doi:10.3390/vaccines13111123
Som, A., & Patel, N. J. (2025) · The Journal of Rheumatology · doi:10.3899/jrheum.2025-1016
Long-term Associations of COVID-19 Severity with Cognition and Mental Health in an Indian CohortPreprint
Biswas, A., Pamnani, V., Srivastava, P., & Sreekumar, V. (2025) · medRxiv · doi:10.1101/2025.11.17.25340384
Otake, S., Tanabe, N., Chubachi, S., Maetani, T., Shiraishi, Y., Asakura, T., Namkoong, H., Tanaka, H., Shimada, T., Azekawa, S., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-26187-7
Goodfellow, L., van Leeuwen, E., & Eggo, R. M. (2024) · Figshare · doi:10.6084/m9.figshare.25602541
Gim, H., Lee, S., 서, 해., Park, Y., & Chun, B. C. (2025) · Bulletin of pioneering researches of medical and clinical science · doi:10.51847/3hfgcnxhof
Nakagawara, K., Tanabe, N., Chubachi, S., Maetani, T., Shiraishi, Y., Asakura, T., Namkoong, H., Tanaka, H., Shimada, T., Azekawa, S., et al. (2025) · European Radiology · doi:10.1007/s00330-025-12078-y
Kerai, T., WOOLHOUSE, M. E. J., Nyazema, N. Z., & Mutapi, F. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1761547
The Feasibility of Developing a Universal SARS-CoV-2 Vaccine
Asaad, M., Mustafa, M. O., Al-Haneedi, Y., Shalaby, L., Eldin, R. S., Mohamedahmed, Y., Yassine, H. M., Abdallah, A., & Emara, M. M. (2026) · Vaccines · doi:10.3390/vaccines14030259
Truong, L. V., Nguyen, T. V., Trang, V. T. T., Le, T. T. T., Thum, C. C., Nguyen, D., Wong, Y. J., Jain, N., Binh, M. N. L. T., Anh, D. H., et al. (2026) · Vaccine · doi:10.1016/j.vaccine.2026.128196
Increased risk of pulmonary embolism following SARS-CoV-2 activity in Ontario, Canada
Lee, E., Wilson, N. J., & Fisman, D. N. (2026) · Public Health · doi:10.1016/j.puhe.2026.106463
The Tetrahydroisoquinoline Derivative SP9 Exhibits Antiviral Activity Against PEDV and MHV
Zhu, J., Jiang, Y., Yang, K. W., Gao, F., Qi, W., Huang, L., & Wang, Y. (2026) · Transboundary and Emerging Diseases · doi:10.1155/tbed/5863464
Self-citationAlmeida, N. D. C., van Tilburg, M. F., da Silva, B. B., Neto, J. X. D. S., Moura, L. F. W. G., Canabrava, N. D. V., Cavalcante, D. I. M., Wong, D. V. T., Lima, R. C. P., Pinheiro, D. P., et al. (2026) · Journal of Immunology Research · doi:10.1155/jimr/9309800
Rebhun, U. (2026) · Contemporary Jewry · doi:10.1007/s12397-026-09732-y
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
Lopes-Ribeiro, Á., Marques-Ferreira, G., Araújo, F. P., Oliveira, P. D. M., Lourenço, A. A., Corrêa-Dias, L. C., Santos, T. A. P., Teixeira, C. W., de Pontes, L. G., Rocha, V. D. M., et al. (2026) · Journal of Leukocyte Biology · doi:10.1093/jleuko/qiag050
Ma, Y., Ning, Y., Guo, J., Xu, S., Luo, Y., Li, J., Lei, L., He, L., Wang, T., Yu, H., et al. (2026) · BMC Public Health · doi:10.1186/s12889-026-27891-3
A dual-critic network architecture for personalized tumor treatment under a dynamical tumor model
Wang, W., Ma, R.-R., Luo, D., Chen, J., Wang, X., Wu, J., & Gao, Z. (2026) · Physica Scripta · doi:10.1088/1402-4896/ae766b
Kontou, E., Detsika, M. G., Salamaliki, C., Bletsa, A., Ampelakiotou, K., Zoulas, D., Athanasiou, N., Totsikas, C., Tzavara, C., Dimopoulou, I., et al. (2026) · Vaccine X · doi:10.1016/j.jvacx.2026.100862
Clinical trials in travel medicine: Building evidence, expanding equity, and shaping the future
Rodriguez-Morales, A. J., & Bambague-Trujillo, L. F. (2026) · Travel Medicine and Infectious Disease · doi:10.1016/j.tmaid.2026.103025
Váncsa, S., Szakolczai, A., Molontay, R., Miklós, E., Szentesi, A., Ocskay, K., Hegyi, P. J., Hegyi, J., Hegyi, A., Hegyi, E., et al. (2026) · GeroScience · doi:10.1007/s11357-026-02585-1
Estimating SARS-CoV-2 reinfection frequency and infection incidence: A modeling study
Qiao, J., Okada, Y., & Nishiura, H. (2026) · Epidemics · doi:10.1016/j.epidem.2026.100956
Metadata
- Authors
- Yang, Z.-R., Jiang, Y.-W., Li, F.-X., Liu, D., Lin, T.-F., Zhao, Z.-Y., Wei, C., Jin, Q.-Y., Li, X.-M., Jia, Y.-X., Zhu, F.-C., Yang, Z.-Y., Sha, F., Feng, Z.-J., & Tang, J.-L.
- Affiliations
- Chinese Academy of Sciences (CN)
- Sun Yat-sen University (CN)
- Chinese University of Hong Kong (HK)
- Corresponding author
- Yang, Zu-Yao
- Sha, Feng
- Venue
- The Lancet Microbe
- Publisher
- Elsevier BV
- Published
- 2023-04
- Volume
- 4
- Issue
- 4
- Pages
- e236-e246
- ISSN
- 2666-5247 (ISSN-L)
- PMC
- PMC9974155
- OpenAlex
- W4322603953
- Cited by
- 138
- References
- 65
- Citations by year
- 2026: 20 · 2025: 36 · 2024: 48 · 2023: 34
- FWCI
- 6.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Microbe (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- COVID-19 vaccines, COVID-19 vaccine efficacy, dose-response relationship, neutralizing antibodies, anti-spike IgG, asymptomatic infection, symptomatic infection, hospitalization prevention, vaccine-induced immunity, SARS-CoV-2, COVID-19 mortality, SARS-CoV-2 variants
- MeSH terms
- COVID-19, SARS-CoV-2, COVID-19 Vaccines, Humans, Immunoglobulin G, Randomized Controlled Trials as Topic, Asymptomatic Infections
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