The DOI matches its Crossref record; 5 of the 6 references it cites were found in a registry or an index; none of the 2 sources its claims cite is checked for support yet.
Antibody Persistence through 6 Months after the Second Dose of mRNA-1273 Vaccine for Covid-19
Open accessAbstract
Persistence of Antibody after mRNA-1273 Vaccination A total of 33 participants who received both doses of the Moderna mRNA-1273 vaccine against SARS-CoV-2 had blood drawn over a period of 6 months ...
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
23 Own result · 2 Not checked yet · 1 Own interpretation
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and 109 days (95% CI, 92 to 136) calculated with the use of a power-law model (at day 119)”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The power-law model assumes that antibody decay rates decrease over time.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and 66 days (95% CI, 59 to 72) and 182 days (95% CI, 153 to 254) for live-virus neutralization.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The power-law model assumes that antibody decay rates decrease over time.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The estimated half-life of binding antibodies after day 43 for all the participants was 52 days (95% CI, 46 to 58) calculated with the use of an exponential decay model”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The exponential decay model assumes a constant antibody decay rate over time.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The neutralizing antibody half-life estimates in the two models were 69 days (95% CI, 61 to 76) and 173 days (95% CI, 144 to 225) for pseudovirus neutralization”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The exponential decay model assumes a constant antibody decay rate over time.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“with 50% inhibitory dilution (ID50) GMTs of 80 (95% CI, 40 to 135), 57 (95% CI, 30 to 106), and 59 (95% CI, 29 to 121), respectively.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“49,373 (95% CI, 25,171 to 96,849) in those 71 years of age or older.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As measured by ΔAICc (change in Akaike information criterion, corrected for small sample size), the best fit for binding and neutralization were the power-law and exponential decay models, respectively”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The exponential decay model assumes a constant antibody decay rate over time.
- The authors state this as an assumption: The power-law model assumes that antibody decay rates decrease over time.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“62,424 (95% CI, 36,765 to 105,990) in those 56 to 70 years of age”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The neutralizing antibody half-life estimates in the two models were 69 days (95% CI, 61 to 76) and 173 days (95% CI, 144 to 225) for pseudovirus neutralization”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The power-law model assumes that antibody decay rates decrease over time.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“these GMTs were lower in participants 56 to 70 years of age (P=0.03) and in those 71 years of age or older (P=0.005) than in those 18 to 55 years of age”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 2
In the paper
“Interim results from a phase 3 trial of the Moderna mRNA-1273 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine indicated 94% efficacy in preventing coronavirus disease 2019 (Covid-19).1”
What the sources say
- Not checked yetcites [1] Baden LR, El Sahly HM, Essink B, et al. Efficacy and safety of the mRNA-1273 SARS-CoV-2 vaccine. N Engl J Med 2021; 384: 403- 416. 33378609 PMC7787219 source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“These results are consistent with published observations of convalescent patients with Covid-19 through 8 months after symptom onset.5”
What the sources say
- Not checked yetcites [5] Dan JM, Mateus J, Kato Y, et al. Immunological memory to SARS-CoV-2 assessed for up to 8 months after infection. Science 2021; 371(6529): eabf4063- eabf4063. 33408181 PMC7919858 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
The durability of protection from the mRNA-1273 vaccine is currently unknown.
“The durability of protection is currently unknown.”
The authors state this as an assumption.
The exponential decay model assumes a constant antibody decay rate over time.
“which assumes a steady decay rate over time”
The authors state this as an assumption.
The power-law model assumes that antibody decay rates decrease over time.
“which assumes that decay rates decrease over time”
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?
In the citing paper
“Current evidence suggests that circulating antibodies persist for at least 6 months postvaccination (7), although there is some decay from the peak levels achieved after the second dose.”
From mRNA vaccines induce durable immune memory to SARS-CoV-2 and variants of concern (2021) · cites this paper as [7]
In the citing paper
“We previously showed that vaccination with mRNA-1273 elicited antibodies to SARS-CoV-2 WA1 in subjects aged 56 to 70 and 71 and older that are as potent (15) and durable (13) as those elicited in adults aged 18 to 55, with a slight decrease in potency for the oldest subjects in live-virus neutralization (13).”
From Durability of mRNA-1273 vaccine–induced antibodies against SARS-CoV-2 variants (2021) · cites this paper as [13]
In the citing paper
“In the pseudovirus neutralization assay, consistent with our previous study (13), 25% of sera neutralized WA1 after one dose (day 29).”
From Durability of mRNA-1273 vaccine–induced antibodies against SARS-CoV-2 variants (2021) · cites this paper as [13]
In the citing paper
“In clinical trials, two doses of mRNA-1273 also elicited durable antibody responses over a period of 6 months. Although antibody titres declined slightly over the duration of the study, high neutralizing ability was retained across all age groups205.”
From mRNA vaccines for infectious diseases: principles, delivery and clinical translation (2021) · cites this paper as [205]
In the citing paper
“Several reports have measured the decay of neutralizing antibody responses raised by mRNA COVID-19 vaccines with a half-life of 69-173 days (Doria-Rose et al., 2021; Levin et al., 2021).”
From mRNA-based COVID-19 vaccine boosters induce neutralizing immunity against SARS-CoV-2 Omicron variant (2022) · cites this paper as Doria-Rose et al., 2021
Citations
Cites
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
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
Self-citationImmunological 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
Safety and Immunogenicity of SARS-CoV-2 mRNA-1273 Vaccine in Older Adults
Anderson, E. J., Rouphael, N. G., Widge, A. T., Jackson, L. A., Roberts, P. C., Makhene, M., Chappell, J. D., Denison, M. R., Stevens, L. J., Pruijssers, A. J., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2028436 · Cited by 1,523
Self-citationDurability of Responses after SARS-CoV-2 mRNA-1273 Vaccination
Widge, A. T., Rouphael, N. G., Jackson, L. A., Anderson, E. J., Roberts, P. C., Makhene, M., Chappell, J. D., Denison, M. R., Stevens, L. J., Pruijssers, A. J., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmc2032195 · Cited by 722
Self-citation
Cited by
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Parry, H., McIlroy, G., Bruton, R. K., Damery, S., Tyson, G. B., Logan, N. A., Davis, C., Willett, B. J., Zuo, J., Ali, M., et al. (2022) · Figshare · doi:10.6084/m9.figshare.18094377
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Akhtar, M., Islam, M. R., Khan, Z. H., Akter, A., Tauheed, I., Ahmed, T., Khan, I. I., Amin, M. A., Khaton, F., Khanam, F., et al. (2026) · Vaccines · doi:10.3390/vaccines14060531
Grobben, M., Kerster, G., Rijnstra, E. S.-V., Brinkkemper, M., Poniman, M., Burger, J. A., Tejjani, K., van Rijswijk, J., Iddouch, W. A., Oomen, M., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.23.733553
Li, Q., Tang, B., & Xiao, Y. (2026) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2026.112548
China, A., Rahman, A., Hani, L., Kumamoto, M., Surénaud, M., Tchérakian, C., Godot, V., Nogimori, T., Lelièvre, J., Lévy, Y., et al. (2026) · Journal of Immunology Research · doi:10.1155/jimr/2293380
Uwamino, Y., Nagashima, K., Tanaka, S., Kurafuji, T., Fujimori, Y., Tanabe, A., Ohno, A., Arai, T., Shibata, A., Wakui, M., et al. (2026) · Vaccine X · doi:10.1016/j.jvacx.2026.100882
Lu, L., Deng, D., Sun, J., Geng, Y., Wang, R., Deng, Z., Liu, L., Shi, X., Lovell, J. F., Yang, M., et al. (2026) · Advanced Materials · doi:10.1002/adma.74905
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Crotty, S., Sette, A., & Weiskopf, D. (2023) · ImmPort · doi:10.21430/m3cppwclw4
Metadata
- Authors
- Doria-Rose, N., Suthar, M. S., Makowski, M., O’Connell, S., McDermott, A. B., Flach, B., Ledgerwood, J. E., Mascola, J. R., Graham, B. S., Lin, B. C., O’Dell, S., Schmidt, S. D., Widge, A. T., Edara, V.-V., Anderson, E. J., Lai, L., Floyd, K., Rouphael, N. G., Zarnitsyna, V., Roberts, P. C., Makhene, M., Buchanan, W., Luke, C. J., Beigel, J. H., Jackson, L. A., Neuzil, K. M., Bennett, H., Leav, B., Albert, J., & Kunwar, P.
- Affiliations
- National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, MD
- Emory University (US)
- Emmes (United States) (US)
- National Institutes of Health (US)
- NIAID, Bethesda, MD
- Kaiser Permanente Washington Health Research Institute (US)
- University of Maryland, Baltimore (US)
- Moderna Therapeutics (United States) (US)
- Corresponding author
- Suthar, Mehul S.
- ORCID
- Doria-Rose, Nicole
- Suthar, Mehul S.
- Makowski, Mat
- O’Connell, Sarah
- McDermott, Adrian B.
- Ledgerwood, Julie E.
- Mascola, John R.
- Graham, Barney S.
- Lin, Bob C.
- Schmidt, Stephen D.
- Widge, Alicia T.
- Edara, Venkata-Viswanadh
- Anderson, Evan J.
- Lai, Lilin
- Floyd, Katharine
- Rouphael, Nadine G.
- Zarnitsyna, Veronika
- Roberts, Paul C.
- Beigel, John H.
- Jackson, Lisa A.
- Neuzil, Kathleen M.
- Bennett, Hamilton
- Leav, Brett
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2021-06-10
- Volume
- 384
- Issue
- 23
- Pages
- 2259-2261
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- PMC
- PMC8524784
- OpenAlex
- W3142193311
- Cited by
- 673
- References
- 6
- Citations by year
- 2026: 17 · 2025: 25 · 2024: 40 · 2023: 104 · 2022: 287 · 2021: 199
- FWCI
- 49.96
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Covid-Catalyst-I3 Funds from the Woodruff Health Sciences Center and Emory School of Medicine
- North Carolina Policy Collaboratory at the University of North Carolina at Chapel Hill
- North Carolina Coronavirus Relief Fund
- Coalition for Epidemic Preparedness Innovations
- Georgia Research Alliance
- National Institute of Allergy and Infectious Diseases (AI149644, HHSN272201500002C, P51 OD011132, UM1AI148373, UM1AI148576, UM1AI148684, UM1Al148684-01S1)
- National Center for Advancing Translational Sciences (UL1 TR002243)
- Dolly Parton COVID-19 Research Fund
- Emory Executive Vice President for Health Affairs Synergy Fund award
- Center for Childhood Infections and Vaccines
- Children’s Healthcare of Atlanta
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Life Sciences › Immunology and Microbiology › Immunology › Immune responses and vaccinations
- Keywords
- mRNA-1273 vaccine, SARS-CoV-2, COVID-19 vaccination, antibody persistence, humoral immune response, Moderna vaccine, booster vaccination, SARS-CoV-2 antibodies
- MeSH terms
- COVID-19, SARS-CoV-2, COVID-19 Vaccines, 2019-nCoV Vaccine mRNA-1273, Adult, Aged, Antibodies, Viral, Half-Life, Humans, Middle Aged, 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.
A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
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.
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