IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-31469-z.html
   My bibliography  Save this article

Effectiveness and protection duration of Covid-19 vaccines and previous infection against any SARS-CoV-2 infection in young adults

Author

Listed:
  • Lior Rennert

    (Clemson University)

  • Zichen Ma

    (Clemson University)

  • Christopher S. McMahan

    (Clemson University)

  • Delphine Dean

    (Clemson University)

Abstract

Data on effectiveness and protection duration of Covid-19 vaccines and previous infection against general SARS-CoV-2 infection in general populations are limited. Here we evaluate protection from Covid-19 vaccination (primary series) and previous infection in 21,261 university students undergoing repeated surveillance testing between 8/8/2021–12/04/2021, during which B.1.617 (delta) was the dominant SARS-CoV-2 variant. Estimated mRNA-1273, BNT162b2, and AD26.COV2.S effectiveness against any SARS-CoV-2 infection is 75.4% (95% CI: 70.5-79.5), 65.7% (95% CI: 61.1-69.8), and 42.8% (95% CI: 26.1–55.8), respectively. Among previously infected individuals, protection is 72.9% when unvaccinated (95% CI: 66.1–78.4) and increased by 22.1% with full vaccination (95% CI: 15.8–28.7). Statistically significant decline in protection is observed for mRNA-1273 (P

Suggested Citation

  • Lior Rennert & Zichen Ma & Christopher S. McMahan & Delphine Dean, 2022. "Effectiveness and protection duration of Covid-19 vaccines and previous infection against any SARS-CoV-2 infection in young adults," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31469-z
    DOI: 10.1038/s41467-022-31469-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-31469-z
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-31469-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Georg Heinze & Michael Schemper, 2001. "A Solution to the Problem of Monotone Likelihood in Cox Regression," Biometrics, The International Biometric Society, vol. 57(1), pages 114-119, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rafael R. G. Machado & Jordyn L. Walker & Dionna Scharton & Grace H. Rafael & Brooke M. Mitchell & Rachel A. Reyna & William M. Souza & Jianying Liu & David H. Walker & Jessica A. Plante & Kenneth S. , 2023. "Immunogenicity and efficacy of vaccine boosters against SARS-CoV-2 Omicron subvariant BA.5 in male Syrian hamsters," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pianto, Donald M. & Cribari-Neto, Francisco, 2011. "Dealing with monotone likelihood in a model for speckled data," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1394-1409, March.
    2. Everett, Bethany G. & Wall, Melanie & Shea, Eileen & Hughes, Tonda L., 2021. "Mortality risk among a sample of sexual minority women: A focus on the role of sexual identity disclosure," Social Science & Medicine, Elsevier, vol. 272(C).
    3. Maalouf, Maher & Trafalis, Theodore B., 2011. "Robust weighted kernel logistic regression in imbalanced and rare events data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 168-183, January.
    4. Eun Ju Cho & Jeong-Hoon Lee & Yuri Cho & Yun Bin Lee & Jeong-Ju Yoo & Minjong Lee & Dong Hyeon Lee & Su Jong Yu & Yoon Jun Kim & Jung-Hwan Yoon & Hyo-Suk Lee, 2015. "Comparison of the Efficacy of Entecavir and Tenofovir in Nucleos(T)ide Analogue-Experienced Chronic Hepatitis B Patients," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-10, June.
    5. Chau, Nancy H. & Qin, Yu & Zhang, Weiwen, 2016. "Leader Networks and Transaction Costs: A Chinese Experiment in Interjurisdictional Contracting," IZA Discussion Papers 9641, Institute of Labor Economics (IZA).
    6. Negreiros, Ana Cláudia Souza Vidal de & Lins, Isis Didier & Moura, Márcio José das Chagas & Droguett, Enrique López, 2020. "Reliability data analysis of systems in the wear-out phase using a (corrected) q-Exponential likelihood," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    7. Il Do Ha & Liming Xiang & Mengjiao Peng & Jong-Hyeon Jeong & Youngjo Lee, 2020. "Frailty modelling approaches for semi-competing risks data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 109-133, January.
    8. Frederico Machado Almeida & Enrico Antônio Colosimo & Vinícius Diniz Mayrink, 2021. "Firth adjusted score function for monotone likelihood in the mixture cure fraction model," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(1), pages 131-155, January.
    9. Krüger, Jens, 2015. "Survival analysis in product life cycle investigations: An assessment of robustness for the German automobile industry," Darmstadt Discussion Papers in Economics 223, Darmstadt University of Technology, Department of Law and Economics.
    10. John E. Kolassa & Juan Zhang, 2023. "Inference in the presence of likelihood monotonicity for proportional hazards regression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(3), pages 322-339, August.
    11. Chau, Nancy H. & Qin, Yu & Zhang, Weiwen, 2015. "Networked Leaders in the Shadow of the Market – A Chinese Experiment in Allocating Land Conversion Rights," Working Papers 250022, Cornell University, Department of Applied Economics and Management.
    12. Wei Wang & Shou‐En Lu & Jerry Q. Cheng & Minge Xie & John B. Kostis, 2022. "Multivariate survival analysis in big data: A divide‐and‐combine approach," Biometrics, The International Biometric Society, vol. 78(3), pages 852-866, September.
    13. Frederico M. Almeida & Vinícius D. Mayrink & Enrico A. Colosimo, 2023. "Bayesian solution to the monotone likelihood in the standard mixture cure model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(3), pages 365-390, August.
    14. Fontana, Roberto & Vezzulli, Andrea, 2016. "Technological leadership and persistence in product innovation in the Local Area Network industry 1990–1999," Research Policy, Elsevier, vol. 45(8), pages 1604-1619.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31469-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.