Effectiveness of mRNA COVID-19 Vaccines as First Booster Doses in England: An Observational Study in OpenSAFELY-TPP

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Abstract

Background:

The UK delivered its first “booster” COVID-19 vaccine doses in September 2021, initially to individuals at high risk of severe disease, then to all adults. The BNT162b2 Pfizer-BioNTech vaccine was used initially, then also Moderna mRNA-1273.

Methods:

With the approval of the National Health Service England, we used routine clinical data to estimate the effectiveness of boosting with BNT162b2 or mRNA-1273 compared with no boosting in eligible adults who had received two primary course vaccine doses. We matched each booster recipient with an unboosted control on factors relating to booster priority status and prior COVID-19 immunization. We adjusted for additional factors in Cox models, estimating hazard ratios up to 182 days (6 months) following booster dose. We estimated hazard ratios overall and within the following periods: 1–14, 15–42, 43–69, 70–97, 98–126, 127–152, and 155–182 days. Outcomes included a positive SARS-CoV-2 test, COVID-19 hospitalization, COVID-19 death, non-COVID-19 death, and fracture.

Results:

We matched 8,198,643 booster recipients with unboosted controls. Adjusted hazard ratios over 6-month follow-up were: positive SARS-CoV-2 test 0.75 (0.74, 0.75); COVID-19 hospitalization 0.30 (0.29, 0.31); COVID-19 death 0.11 (0.10, 0.14); non-COVID-19 death 0.22 (0.21, 0.23); and fracture 0.77 (0.75, 0.78). Estimated effectiveness of booster vaccines against severe COVID-19-related outcomes peaked during the first 3 months following the booster dose. By 6 months, the cumulative incidence of positive SARS-CoV-2 test was higher in boosted than unboosted individuals.

Conclusions:

We estimate that COVID-19 booster vaccination, compared with no booster vaccination, provided substantial protection against COVID-19 hospitalization and COVID-19 death but only limited protection against positive SARS-CoV-2 test. Lower rates of fracture in boosted than unboosted individuals may suggest unmeasured confounding. Observational studies should report estimated vaccine effectiveness against nontarget and negative control outcomes.

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Most cited references 22

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BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Mass Vaccination Setting

Noa Dagan, Noam Barda, Eldad Kepten … (2021)

Abstract Background As mass vaccination campaigns against coronavirus disease 2019 (Covid-19) commence worldwide, vaccine effectiveness needs to be assessed for a range of outcomes across diverse populations in a noncontrolled setting. In this study, data from Israel’s largest health care organization were used to evaluate the effectiveness of the BNT162b2 mRNA vaccine. Methods All persons who were newly vaccinated during the period from December 20, 2020, to February 1, 2021, were matched to unvaccinated controls in a 1:1 ratio according to demographic and clinical characteristics. Study outcomes included documented infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), symptomatic Covid-19, Covid-19–related hospitalization, severe illness, and death. We estimated vaccine effectiveness for each outcome as one minus the risk ratio, using the Kaplan–Meier estimator. Results Each study group included 596,618 persons. Estimated vaccine effectiveness for the study outcomes at days 14 through 20 after the first dose and at 7 or more days after the second dose was as follows: for documented infection, 46% (95% confidence interval [CI], 40 to 51) and 92% (95% CI, 88 to 95); for symptomatic Covid-19, 57% (95% CI, 50 to 63) and 94% (95% CI, 87 to 98); for hospitalization, 74% (95% CI, 56 to 86) and 87% (95% CI, 55 to 100); and for severe disease, 62% (95% CI, 39 to 80) and 92% (95% CI, 75 to 100), respectively. Estimated effectiveness in preventing death from Covid-19 was 72% (95% CI, 19 to 100) for days 14 through 20 after the first dose. Estimated effectiveness in specific subpopulations assessed for documented infection and symptomatic Covid-19 was consistent across age groups, with potentially slightly lower effectiveness in persons with multiple coexisting conditions. Conclusions This study in a nationwide mass vaccination setting suggests that the BNT162b2 mRNA vaccine is effective for a wide range of Covid-19–related outcomes, a finding consistent with that of the randomized trial.

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Effectiveness of a third dose of the BNT162b2 mRNA COVID-19 vaccine for preventing severe outcomes in Israel: an observational study

Noam Barda, Noa Dagan, Cyrille Cohen … (2021)

Background Many countries are experiencing a resurgence of COVID-19, driven predominantly by the delta (B.1.617.2) variant of SARS-CoV-2. In response, these countries are considering the administration of a third dose of mRNA COVID-19 vaccine as a booster dose to address potential waning immunity over time and reduced effectiveness against the delta variant. We aimed to use the data repositories of Israel's largest health-care organisation to evaluate the effectiveness of a third dose of the BNT162b2 mRNA vaccine for preventing severe COVID-19 outcomes. Methods Using data from Clalit Health Services, which provides mandatory health-care coverage for over half of the Israeli population, individuals receiving a third vaccine dose between July 30, 2020, and Sept 23, 2021, were matched (1:1) to demographically and clinically similar controls who did not receive a third dose. Eligible participants had received the second vaccine dose at least 5 months before the recruitment date, had no previous documented SARS-CoV-2 infection, and had no contact with the health-care system in the 3 days before recruitment. Individuals who are health-care workers, live in long-term care facilities, or are medically confined to their homes were excluded. Primary outcomes were COVID-19-related admission to hospital, severe disease, and COVID-19-related death. The third dose effectiveness for each outcome was estimated as 1 – risk ratio using the Kaplan-Meier estimator. Findings 1 158 269 individuals were eligible to be included in the third dose group. Following matching, the third dose and control groups each included 728 321 individuals. Participants had a median age of 52 years (IQR 37–68) and 51% were female. The median follow-up time was 13 days (IQR 6–21) in both groups. Vaccine effectiveness evaluated at least 7 days after receipt of the third dose, compared with receiving only two doses at least 5 months ago, was estimated to be 93% (231 events for two doses vs 29 events for three doses; 95% CI 88–97) for admission to hospital, 92% (157 vs 17 events; 82–97) for severe disease, and 81% (44 vs seven events; 59–97) for COVID-19-related death. Interpretation Our findings suggest that a third dose of the BNT162b2 mRNA vaccine is effective in protecting individuals against severe COVID-19-related outcomes, compared with receiving only two doses at least 5 months ago. Funding The Ivan and Francesca Berkowitz Family Living Laboratory Collaboration at Harvard Medical School and Clalit Research Institute.

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Negative controls: a tool for detecting confounding and bias in observational studies.

Marc Lipsitch, Eric Tchetgen Tchetgen, Ted Cohen (2010)

Noncausal associations between exposures and outcomes are a threat to validity of causal inference in observational studies. Many techniques have been developed for study design and analysis to identify and eliminate such errors. Such problems are not expected to compromise experimental studies, where careful standardization of conditions (for laboratory work) and randomization (for population studies) should, if applied properly, eliminate most such noncausal associations. We argue, however, that a routine precaution taken in the design of biologic laboratory experiments--the use of "negative controls"--is designed to detect both suspected and unsuspected sources of spurious causal inference. In epidemiology, analogous negative controls help to identify and resolve confounding as well as other sources of error, including recall bias or analytic flaws. We distinguish 2 types of negative controls (exposure controls and outcome controls), describe examples of each type from the epidemiologic literature, and identify the conditions for the use of such negative controls to detect confounding. We conclude that negative controls should be more commonly employed in observational studies, and that additional work is needed to specify the conditions under which negative controls will be sensitive detectors of other sources of error in observational studies.

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Author and article information

Journal

Journal ID (nlm-ta): Epidemiology

Journal ID (iso-abbrev): Epidemiology

Journal ID (publisher-id): EDE

Title: Epidemiology (Cambridge, Mass.)

Publisher: Lippincott Williams & Wilkins (Hagerstown, MD )

ISSN (Print): 1044-3983

ISSN (Electronic): 1531-5487

Publication date (Electronic): 24 June 2024

Publication date (Print): July 2024

Volume: 35

Issue: 4

Pages: 568-578

Affiliations

From the [a ]Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom

[b ]National Institute of Health and Care Research Bristol Biomedical Research Centre, Bristol, United Kingdom

[c ]The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, United Kingdom

[d ]London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom

[e ]MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom

[f ]Health Data Research UK South West, United Kingdom

[g ]National Institute of Health and Care Research Applied Research Collaboration West, University Hospitals Bristol and Weston, United Kingdom

[h ]CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA

[i ]Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA

Author notes

Correspondence: Jonathan A C Sterne, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK, BS8 2BN. E-mail: Jonathan.Sterne@ 123456bristol.ac.uk .

Author information

Elsie M. F. Horne https://orcid.org/0000-0002-5545-7628

William J. Hulme https://orcid.org/0000-0002-9162-4999

Ruth H. Keogh https://orcid.org/0000-0001-6504-3253

Elizabeth J. Williamson https://orcid.org/0000-0001-6905-876X

Venexia M. Walker https://orcid.org/0000-0001-5064-446X

Tom M. Palmer https://orcid.org/0000-0003-4655-4511

Rochelle Knight https://orcid.org/0000-0002-4128-6821

Helen J. Curtis https://orcid.org/0000-0003-3429-9576

Alex J. Walker https://orcid.org/0000-0003-4932-6135

Colm D. Andrews https://orcid.org/0000-0003-2715-0562

Amir Mehrkar https://orcid.org/0000-0002-2098-1278

Jessica Morley https://orcid.org/0000-0001-5221-4770

Brian MacKenna https://orcid.org/0000-0002-3786-9063

Sebastian C. J. Bacon https://orcid.org/0000-0002-6354-3454

Ben Goldacre https://orcid.org/0000-0002-5127-4728

Miguel A. Hernán https://orcid.org/0000-0003-1619-8456

Jonathan A. C. Sterne https://orcid.org/0000-0001-8496-6053

Article

Publisher ID: EDE23-0338 Accession ID: 00018

DOI: 10.1097/EDE.0000000000001747

PMC ID: 11191555

PubMed ID: 38912714

SO-VID: fe93990c-317a-4796-a1d8-49b3828eddbb

License:

This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 22 August 2023

Date accepted : 26 March 2024

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Keywords: covid-19,electronic health records,target trial emulation,vaccine,vaccine effectiveness

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Keywords: covid-19, electronic health records, target trial emulation, vaccine, vaccine effectiveness

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Effectiveness of mRNA COVID-19 Vaccines as First Booster Doses in England: An Observational Study in OpenSAFELY-TPP

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Abstract

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Novel Coronavirus Disease COVID-19

Most cited references 22

BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Mass Vaccination Setting

Effectiveness of a third dose of the BNT162b2 mRNA COVID-19 vaccine for preventing severe outcomes in Israel: an observational study

Negative controls: a tool for detecting confounding and bias in observational studies.

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