Health

Comparative effectiveness of third doses of mRNA-based COVID-19 vaccines in US veterans

Published

2 years ago

January 2, 2023

Abstract

Vaccination against SARS-CoV-2 has been effective in reducing the burden of severe disease and death from COVID-19. Third doses of mRNA-based vaccines have provided a way to address waning immunity and broaden protection against emerging SARS-CoV-2 variants. However, their comparative effectiveness for a range of COVID-19 outcomes across diverse populations is unknown. We emulated a target trial using electronic health records of US veterans who received a third dose of either BNT162b2 or mRNA-1273 vaccines between 20 October 2021 and 8 February 2022, during a period that included Delta- and Omicron-variant waves. Eligible veterans had previously completed an mRNA vaccine primary series. We matched recipients of each vaccine in a 1:1 ratio according to recorded risk factors. Each vaccine group included 65,196 persons. The excess number of events over 16 weeks per 10,000 persons for BNT162b2 compared with mRNA-1273 was 45.4 (95% CI: 19.4, 84.7) for documented infection, 3.7 (2.2, 14.1) for symptomatic COVID-19, 10.6 (5.1, 19.7) for COVID-19 hospitalization, 2.0 (−3.1, 6.3) for COVID-19 intensive care unit admission and 0.2 (−2.2, 4.0) for COVID-19 death. After emulating a second target trial of veterans who received a third dose between 1 January and 1 March 2022, during a period restricted to Omicron-variant predominance, the excess number of events over 9 weeks per 10,000 persons for BNT162b2 compared with mRNA-1273 was 63.2 (95% CI: 15.2, 100.7) for documented infection. The 16-week risks of COVID-19 outcomes were low after a third dose of mRNA-1273 or BNT162b2, although risks were lower with mRNA-1273 than with BNT162b2, particularly for documented infection.

Main

Additional doses of messenger RNA (mRNA)-based vaccines are being widely deployed to counter waning immunity and broaden protection against emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)^1,2. However, head-to-head comparisons of the effectiveness of a third dose of different mRNA-based vaccines have been lacking.

In a previous head-to-head comparison of breakthrough COVID-19 outcomes after the first dose of the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines among 439,684 US veterans aged ≥18 yr, we found a low risk of documented infection and severe COVID-19 outcomes (for example, hospitalization and death) in a period marked by SARS-CoV-2 Alpha-variant predominance in both vaccine groups, but lower risk for the mRNA-1273 vaccine (with a similar pattern for documented infection in a period marked by Delta-variant predominance)³. It is unclear whether the same findings apply to third doses and a range of COVID-19 outcomes in periods marked by other SARS-CoV-2 variants, including Omicron.

A report from Spain estimated a third dose of mRNA-1273 to be 13% more effective than a third dose of BNT162b2 for the prevention of documented SARS-CoV-2 infection during a period of Omicron-variant predominance⁴. In other reports, effectiveness of mRNA-based vaccines against symptomatic COVID-19 was analysed separately for each third dose compared with no vaccination⁵ (or with the primary vaccination series⁶). These comparisons provide indirect evidence for comparative effectiveness but only if the comparators from each analysis had similar characteristics. Additional studies are needed to compare the effectiveness of a third dose of these vaccines head-to-head for severe COVID-19 outcomes to inform the choice of vaccine in coordinated public health responses. Ideally, any comparative effectiveness study should include racially diverse groups, evaluate potential differences in effectiveness according to time since the completion of the primary vaccination series and separately address time frames that include predominance of different SARS-CoV-2 variants.

Here we analysed data from the national healthcare databases of the Department of Veterans Affairs (VA), the largest integrated healthcare system in the US, to compare the effectiveness of a third dose of either the BNT162b2 or the mRNA-1273 vaccine among US veterans who had completed an mRNA vaccine primary series and received a third dose between (1) 20 October 2021 and 8 February 2022 (a period spanning Delta- and Omicron-variant predominance) or (2) 1 January and 1 March 2022 (a period restricted to Omicron-variant predominance). Recipients of each vaccine were matched in a 1:1 ratio according to their risk factors. Comparative effectiveness was estimated over 16 weeks in the combined Delta-Omicron period and over 9 weeks in the Omicron period for five COVID-19 outcomes: documented SARS-CoV-2 infection, symptomatic COVID-19 and COVID-19-related hospitalization, admission to an intensive care unit (ICU) and death.

Results

Primary analyses during a period spanning SARS-CoV-2 Delta- and Omicron-variant predominance

Study population and follow-up

Among 147,553 eligible recipients of a BNT162b2 third dose and 214,728 eligible recipients of an mRNA-1273 third dose, 65,196 BNT162b2 recipients were matched to 65,196 mRNA-1273 recipients (Fig. 1). The baseline characteristics of this matched population (Table 1) were similar to those of the eligible population (Supplementary Table 1). The median age was 70 yr (interquartile range, 62–74 yr), 96% of individuals were male and 24% were Black. The two vaccine groups had similar distributions of demographics, coexisting conditions and markers of healthcare utilization (see also Extended Data Fig. 1).

Fig. 1: Selection of persons for the emulation of a target trial evaluating the comparative effectiveness of a third dose of BNT162b2 and mRNA-1273 vaccines.

Selection was conducted during a period spanning Delta- and Omicron-variant predominance (20 October 2021 to 8 February 2022).

Full size image

Table 1 Baseline characteristics of matched persons in the target trial emulation evaluating the comparative effectiveness of a third dose of BNT162b2 and mRNA-1273 vaccines during a period spanning Delta- and Omicron-variant predominance

Full size table

The median follow-up was 77 d (interquartile range, 61 to 97 d). Over a 16-week-follow-up, 2,994 SARS-CoV-2 infections were documented, of which 200 were detected as symptomatic COVID-19 within the VA healthcare system, 194 required hospitalization, 52 required ICU admission and 22 resulted in death.

Comparative effectiveness

Over a 16-week period spanning Delta- and Omicron-variant predominance, the estimated risk of documented infection was 353.9 (95% CI: 326.7, 373.2) events per 10,000 persons for the BNT162b2 third dose and 308.5 (95% CI: 276.8, 320.9) events per 10,000 persons for the mRNA-1273 third dose (Fig. 2). As expected, we found a nearly identical risk pattern in the two vaccine groups in the evaluations of two negative outcome controls⁷: symptomatic COVID-19 during the first 7 d after the third vaccine dose (Extended Data Fig. 2) and death from causes other than COVID-19 during follow-up (Extended Data Fig. 3).

**Fig. 2: Cumulative incidence of Covid-19 outcomes during a period spanning Delta- and Omicron-variant predominance (20 October 2021 to 15 February 2022).**

The estimated 16-week risk ratios (95% CI) for recipients of a third dose of BNT162b2 as compared with mRNA-1273 were 1.15 (1.06, 1.30) for documented SARS-CoV-2 infection, 1.21 (1.12, 2.14) for symptomatic COVID-19, 1.64 (1.27, 2.79) for COVID-19 hospitalization, 1.37 (0.67, 3.14) for COVID-19 ICU admission and 1.08 (0.46, 6.39) for COVID-19 death (Table 2). The estimated risk differences (BNT162b2 minus mRNA-1273), expressed as events over 16 weeks per 10,000 persons (95% CI), were 45.4 (19.4, 84.7) for documented SARS-CoV-2 infection, 3.7 (2.2, 14.1) for symptomatic COVID-19, 10.6 (5.1, 19.7) for COVID-19 hospitalization, 2.0 (−3.1, 6.3) for COVID-19 ICU admission and 0.2 (−2.2, 4.0) for COVID-19 death.

Table 2 Estimated comparative effectiveness of a third dose of BNT162b2 and mRNA-1273 vaccines during a period spanning Delta- and Omicron-variant predominance (20 October 2021 to 15 February 2022)

Full size table

Estimates were similar across subgroups defined at baseline according to age, race, months since completion of COVID-19 vaccine primary series (Table 3) and by vaccine type of primary series (risk ratio for documented infection comparing a third dose of BNT162b2 vs mRNA-1273, 1.19 (0.98, 2.65) among recipients of a BNT162b2 primary series, 1.04 (0.84, 2.32) among recipients of an mRNA-1273 primary series). Estimates were also similar in sensitivity analyses that excluded eligible individuals with previously documented SARS-CoV-2 infection (6.3%), those who did not receive a homologous COVID-19 vaccine primary series (3.3%) and those whose third dose could not be identified as a booster dose (17.2%) (data not shown).

Table 3 Estimated comparative effectiveness of a third dose of BNT162b2 and mRNA-1273 vaccines in subgroups defined by baseline characteristics during a period spanning Delta- and Omicron-variant predominance (20 October 2021 to 15 February 2022)

Full size table

Secondary analyses during a period of SARS-CoV-2 Omicron-variant predominance

Study population and follow-up

Among 25,557 eligible recipients of a BNT162b2 third dose and 36,809 eligible recipients of an mRNA-1273 third dose, 7,894 BNT162b2 recipients were matched to 7,894 mRNA-1273 recipients. Compared with the eligible population, the matched population was generally similar with respect to baseline demographic and clinical characteristics but included a higher percentage of men, White individuals, individuals with an urban residence and individuals who had received no SARS-CoV-2 tests in the past year (Supplementary Table 1). Baseline characteristics of the matched persons are shown in Supplementary Table 2. All variables were well-balanced between the two vaccine groups (Extended Data Fig. 1).

As compared with the matched population during a period spanning Delta- and Omicron-variant predominance, the matched population during a period of Omicron-variant predominance was, on average, younger and included a higher percentage of individuals who had received no SARS-CoV-2 tests in the previous year and no influenza vaccinations in the previous 5 yr at a VA facility (Supplementary Table 1).

The median follow-up was 54 d (interquartile range, 40–60 d). Over a 9-week follow-up, 214 SARS-CoV-2 infections were documented.

Comparative effectiveness

Over a 9-week period of Omicron-variant predominance, the estimated risk of documented SARS-CoV-2 infection was also higher with a third dose of the BNT162b2 vaccine than with a third dose of the mRNA-1273 vaccine; the estimated risk ratio was 1.57 (1.12, 2.10) and the estimated risk difference, expressed as events over 9 weeks per 10,000 persons, was 63.2 (15.2, 100.7) (see also Fig. 3).

**Fig. 3: Cumulative incidence of documented SARS-CoV-2 infection during a period of Omicron-variant predominance (1 January to 8 March 2022).**

Discussion

We quantified the comparative effectiveness of a third dose of the BNT162b2 and mRNA-1273 vaccines for the prevention of COVID-19 outcomes in the largest integrated healthcare system in the United States. Although the risks of all five measured COVID-19 outcomes (documented infection, symptomatic COVID-19 and COVID-19-related hospitalization, ICU admission and death) over 16 weeks were low for both vaccines during a period spanning Delta- and Omicron-variant predominance (risks <4% for documented infection and <0.03% for death, within each vaccine group), recipients of a third dose of BNT162b2 had an excess per 10,000 persons of 45 documented infections and 11 hospitalizations compared with recipients of a third dose of mRNA-1273. We also found a higher risk of documented infection among recipients of a third dose of BNT162b2 compared with mRNA-1273 over 9 weeks of follow-up during a period of Omicron-variant predominance, although this estimate was less precise due to a smaller number of eligible persons.

Few head-to-head comparisons of a third dose of mRNA vaccines are available. A report from Spain estimated mRNA-1273 boosters to be 13% more effective than BNT162b2 boosters for the prevention of documented SARS-CoV-2 infection during a period of Omicron-variant predominance, but more severe outcomes could not be evaluated⁴. In two other reports, effectiveness against symptomatic COVID-19 was evaluated separately for each mRNA booster either compared with no vaccination (in two test-negative case-control studies in England⁵) or compared with the primary series (in two matched cohort studies in Qatar⁶). In each report, an indirect comparison of these results requires that the controls from each study had similar characteristics, and more severe outcomes could not be evaluated for both mRNA booster groups.

The differential effectiveness we report in our study might be explained by the higher mRNA content of mRNA-1273 (50 μg for booster doses, 100 μg for third primary doses) compared with of BNT162b2 (30 μg for booster and third primary doses). Our primary analysis considered any third dose of these vaccines, of which 83% were distinguished as booster doses, and results were similar in sensitivity analyses that were restricted to these.

The strengths of our study are that first, the VA healthcare databases contain rich data on demographics and medical history, which allowed us to carefully match recipients of each vaccine type according to key confounders. Second, the databases contain detailed information on laboratory test results and healthcare encounters, which allowed us to capture outcomes related to COVID-19 in both outpatient and inpatient settings. Third, the large size of the study population allowed us to evaluate less common COVID-19 outcomes (hospitalizations, ICU admissions, deaths). Fourth, the demographic composition of the US veteran population allowed us to provide evidence for a diverse cohort (24% Black, 8% Hispanic) and to conduct subgroup analyses among older persons (≥70 yr of age) and Black persons.

Our study also has several potential limitations. First, as in any observational analysis of comparative effectiveness, the vaccine groups could differ with respect to risk factors for the outcomes. However, after rigorously matching recipients of each vaccine type, the two groups had similar demographics, comorbidities, time since completion of the primary vaccination series, number of SARS-CoV-2 tests in the previous year and markers of healthcare utilization (for example, number of primary care visits and of influenza vaccinations in the previous 5 yr). Further, much less confounding is expected when comparing recipients of different third doses of vaccines than when comparing recipients of a third dose with, for example, unvaccinated persons. In addition, our two analyses involving negative-outcome controls suggested little confounding.

Second, the possibility of outcome misclassification cannot be ruled out if veterans sought testing or care outside the VA healthcare system or if testing was differential between groups. However, our use of the VA COVID-19 National Surveillance Tool allowed us to integrate laboratory data with clinical notes to capture infections documented inside and outside the system, and the SARS-CoV-2 testing frequencies over follow-up were similar in both groups (Table 2). Further, we selected regular VA users who had a known residential address and who had routinely collected information (body-mass index, smoking status) to improve outcome ascertainment. We expect any residual incomplete ascertainment to be non-differential between the vaccination groups under comparison, although absolute risks may be slightly biased downwards. Finally, our study population was mostly made up of men (96%) and older persons (95% were >50 yr old), which may limit the generalizability of our findings.

Given the high effectiveness of a third dose of both the BNT162b2 and mRNA-1273 vaccines, either vaccine is strongly recommended to any individual. This study provides evidence of clear and comparable benefits of these vaccines for the most severe outcomes (the difference in estimated 16-week risk of death between the two groups was two-thousandths of one percent). While the differences in estimated risk for less severe outcomes between the two groups were small on the absolute scale, they may be meaningful when considering the population scale at which these vaccines are deployed. However, decisions about vaccination campaigns are complex and must incorporate considerations that extend beyond the scope of the present study. Therefore, our findings need to be combined with those from previous studies to inform future decisions about choice of vaccine in coordinated public health responses.

In summary, although the absolute risks of breakthrough SARS-CoV-2 infection and more severe COVID-19 outcomes were low regardless of the third mRNA-based COVID-19 dose received, this study involving a nationwide cohort of US veterans provides evidence of a lower 16-week risk of COVID-19-related outcomes among recipients of a third dose of the mRNA-1273 vaccine compared with recipients of a third dose of the BNT162b2 vaccine, particularly for documented infection. This pattern was consistent across a period spanning Delta- and Omicron-variant predominance and a period restricted to Omicron-variant predominance. Further evaluation of the comparative effectiveness and safety of additional doses of these vaccines is needed.

Methods

Specification of the target trials

We designed an observational analysis to emulate a hypothetical pragmatic trial of a third dose of BNT162b2 compared with mRNA-1273 and risks of COVID-19 outcomes in the VA healthcare system. Supplementary Table 3 summarizes the key protocol components.

Eligibility criteria included veteran status; age ≥65 yr or 18–64 yr with high risk of severe COVID-19 between 20 October and 18 November 2021 (based on the presence of at least one coexisting condition listed in Table 1)⁸ or ≥18 yr between 19 November 2021 and 8 February 2022 (based on national guidelines for third dose deployment)^9,10; receipt of the second dose of an mRNA vaccine primary series at least 6 months earlier (based on the same guidelines); known residential address outside of a long-term care facility; and known smoking status and known body-mass index within the previous year. Individuals had to have used the VA healthcare system during the previous year (defined as receiving care at a station eligible to administer the vaccines under study and having at least one primary care visit) but not within the previous 3 d (which may indicate the start of symptomatic disease).

The interventions of interest were a third dose of either the BNT162b2 or the mRNA-1273 vaccine. To ensure balance of important characteristics across groups, eligible veterans in the target trial would be randomly assigned to one of these two vaccines within strata defined by calendar date of the third dose (5 d bins), calendar month of the second mRNA vaccine dose, age (5 yr bins), sex (male, female), race (White, Black, other, unknown), urbanicity of residence (urban, not urban), geographic location (coded as 19 categories of Veterans Integrated Services Network) and number of SARS-CoV-2 tests performed in the past 12 months (0, 1, ≥2).

The five outcomes of interest were documented SARS-CoV-2 infection, documented symptomatic COVID-19 and COVID-19-related hospital admission, ICU admission and death. For each eligible individual, follow-up started on the day the third dose of vaccine was received (baseline) and ended on the day of the outcome of interest, death, 112 d (16 weeks) after baseline, or the end of the study period (15 February 2022), whichever happened first.

Our target trial evaluates comparative effectiveness of a third dose of the vaccines during a period spanning times when SARS-CoV-2 Delta- and Omicron-variants were circulating. The Delta variant had decreased to a share of 26% of circulating variants in the United States as of 25 December 2021, as it was rapidly displaced by the Omicron variant, which rose to a 100% share as of 12 February 2022¹¹. To evaluate the comparative effectiveness during a period of Omicron-variant predominance, we considered a second target trial that was identical to the first trial except that the recruitment period was 1 January to 1 March 2022, and the only outcome of interest was documented SARS-CoV-2 infection because the period was too short to accrue a sufficient number of rarer, more severe outcomes.

Emulation of the target trials

We emulated both target trials using the VA healthcare databases³. Vaccination was identified using records from the Corporate Data Warehouse and the VA COVID-19 Shared Data Resource. SARS-CoV-2 infections were identified using the VA COVID-19 National Surveillance Tool^3,12, which integrates data on laboratory tests with natural language processing of clinical notes to capture diagnoses documented inside and outside the VA healthcare system. Symptomatic COVID-19 was defined as ≥1 of the following symptoms documented within 4 d of SARS-CoV-2 infection: fever, chills, cough, shortness of breath or difficulty breathing, sore throat, loss of taste or smell, headache, myalgia/muscle pain, diarrhoea and vomiting. COVID-19 hospitalization was defined as a hospitalization within 21 d after documented SARS-CoV-2 infection, COVID-19 ICU admission was defined as an ICU admission during a COVID-19 hospitalization, and COVID-19 death was defined as a death within 30 d after documented SARS-CoV-2 infection. Supplementary Table 4 provides detailed information on all study variables and their ascertainment.

We attempted to mimic the stratified randomization of the target trial by matching persons who received a third dose of BNT162b2 and of mRNA-1273 on the basis of the calendar date of the third dose, calendar month of the second dose, age, sex, race, urbanicity of residence, geographic location, and number of SARS-CoV-2 tests performed in the past 12 months, using the same matching algorithm described in our previous study³.

To explore the possibility of residual confounding (for example, by underlying health status or healthcare-seeking behaviour), we incorporated two negative outcome controls⁷. First, we evaluated the risk of symptomatic COVID-19 in the first 7 d after the third vaccine dose. Second, we evaluated the risk of death from causes other than COVID-19 during the follow-up period.

Statistical analyses

Covariate balance after matching was evaluated by plotting the mean differences between variable values (standardized for continuous variables) for the vaccination groups, with a difference of 0.1 or less considered to be acceptable¹³.

Cumulative incidence (risk) curves for the vaccine groups were estimated using the Kaplan-Meier estimator¹⁴. We then calculated 16-week risks of each outcome and compared them between the vaccine groups via differences and ratios. We conducted subgroup analyses by age (<70 or ≥70 yr), race (Black or White), time since completion of the COVID-19 vaccine primary series (6–7, 8, or ≥9 months) and vaccine type of the primary series (BNT162b2 or mRNA-1273). We conducted sensitivity analyses that excluded eligible individuals who (1) had previously documented SARS-CoV-2 infection, (2) did not receive a homologous third dose compared with the COVID-19 vaccine primary series and (3) had a third dose that could not be identified as a booster dose on the basis of procedural codes available in the ‘Inpatient’ and ‘Outpatient’ domains, to compare recipients of vaccines at known doses, as the dose of mRNA-1273 differs for booster doses (50 μg) vs third primary doses (100 μg).

We used a nonparametric bootstrapping procedure (including both matching and subsequent analyses) with 500 iterations to calculate percentile-based 95% confidence intervals for all estimates.

Analyses were performed using R software version 3.6.0 (R Foundation for Statistical Computing) and SAS Enterprise Guide version 8.2 (SAS Institute).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The data that support the findings of this study are available from the VA. VA data are made freely available to researchers (behind the VA firewall) with an approved VA study protocol. More information is available at https://www.virec.research.va.gov or by contacting the VA Information Resource Center (VIReC) at VIReC@va.gov. Source data are provided with this paper.

Code availability

Access to the computer code used in this research is available by request to the corresponding author.

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Acknowledgements

This research was supported by the US Department of Veterans Affairs (VA) Office of Research and Development (ORD) Cooperative Studies Program (CSP) Epidemiology Center at the VA Boston Healthcare System through CSP #2032, by resources and the use of facilities at the VA Boston Healthcare System and VA Informatics and Computing Infrastructure (VINCI) (VA HSR RES 13-457) and by the use of data from the VA COVID-19 Shared Data Resource. B.A.D., A.L.M. and M.A.H. were supported by CSP #2032. B.A.D. was supported by a grant (R00 CA248335) from the National Institutes of Health. H.G. and B.R.F. were supported by a grant (MVP000) from the VA Million Veteran Program. M.J.F.M. was supported by a grant (T32 GM140972) from the National Institute of General Medical Sciences Interdisciplinary Training Program for Biostatisticians. We thank D. C. Posner, Y.-L. (A.) Ho and K. E. Lynch for insights on COVID-19 data extraction and phenotype definitions; C. A. Hoag for management of the administrative and regulatory aspects of the project; J. M. Gaziano for advice and support; the VA COVID-19 Shared Data Resource team for their contributions and support; and the VA healthcare providers, employees and volunteers for their dedication to caring for our veterans through this pandemic.

Author information

Author notes

These authors contributed equally: Barbra A. Dickerman, Hanna Gerlovin.

Authors and Affiliations

CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA, USA

Barbra A. Dickerman, Arin L. Madenci & Miguel A. Hernán
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

Barbra A. Dickerman, Arin L. Madenci & Miguel A. Hernán
Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA

Hanna Gerlovin, Michael J. Figueroa Muñiz, Jessica K. Wise, Nimish Adhikari, Brian R. Ferolito, Katherine E. Kurgansky, David R. Gagnon, Kelly Cho & Juan P. Casas
Department of Surgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

Arin L. Madenci
Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

Michael J. Figueroa Muñiz, Nimish Adhikari & David R. Gagnon
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

Katherine E. Kurgansky
Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

Kelly Cho & Juan P. Casas
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

Miguel A. Hernán

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Contributions

B.A.D., H.G. and M.A.H. designed the study. H.G. and K.E.K. designed the data extraction and assembly workflow. H.G., B.R.F., M.J.F.M., N.A. and J.K.W. gathered the data. B.A.D., H.G. and A.L.M. designed the analytic pipeline. H.G. analysed the data. B.A.D., H.G. and M.A.H. vouch for the data and analysis. B.A.D. wrote the first draft of the manuscript. All authors critically reviewed the manuscript and decided to proceed with publication.

Corresponding author

Correspondence to
Hanna Gerlovin.

Ethics declarations

Competing interests

B.R.F. reported completing a 6-month paid internship with Moderna before joining the Department of Veterans Affairs and owning five shares of Moderna, Inc. stock purchased in February 2020 outside the submitted work. M.A.H. reported receiving personal fees from Cytel and ProPublica outside the submitted work. The other authors declare no competing interests.

Ethical compliance

This work was approved by the VA Boston Healthcare System Research & Development Committee and Human Subjects Subcommittee, and an exemption of informed consent and HIPAA authorization was granted.

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Peer review information

Nature Microbiology thanks the anonymous reviewers for their contribution to the peer review of this work.

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Disclaimer: The contents of this article do not represent the views of the US Department of Veterans Affairs or the US Government. The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Department of Health and Human Services and its agencies, including Biomedical Advanced Research and Development Authority and the Food and Drug Administration, as well as any other agency of the US Government. Assumptions made within and interpretations from the analysis do not necessarily reflect the position of any US Government entity.

Extended data

Extended Data Fig. 1 Covariate Balance (Love) Plot.

Shows the difference in means for conditions identified by the Centers for Disease Control and Prevention (CDC) as risk factors for severe COVID-19 in the matched population from the (a) primary analysis during a period spanning Delta- and Omicron-variant predominance and (b) secondary analysis during a period of Omicron-variant predominance. A strict balance cut-off was set at 0.1. An asterisk denotes the standardization of continuous variables.

Source data

Extended Data Fig. 2 Negative control 1: Cumulative Incidence of Symptomatic COVID-19 in the First 7 Days After the Third Vaccine Dose (October 20, 2021–February 15, 2022).

Solid blue line represents the risk curve for BNT162b2, dashed orange line represents the risk curve for mRNA-1273 and shaded areas represent pointwise 95% confidence intervals.

Source data

Extended Data Fig. 3 Negative control 2: Cumulative Incidence of Non-COVID-19 Death Over the Follow-up (October 20, 2021–February 15, 2022).

Solid blue line represents the risk curve for BNT162b2, dashed orange line represents the risk curve for mRNA-1273 and shaded areas represent pointwise 95% confidence intervals.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1–4.

Reporting Summary

Source data

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

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Dickerman, B.A., Gerlovin, H., Madenci, A.L. et al. Comparative effectiveness of third doses of mRNA-based COVID-19 vaccines in US veterans.
Nat Microbiol (2023). https://doi.org/10.1038/s41564-022-01272-z

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Received: 28 July 2022
Accepted: 17 October 2022
Published: 02 January 2023
DOI: https://doi.org/10.1038/s41564-022-01272-z

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Health

What’s the greatest holiday gift: lips, hair, skin? Give the gift of great skin this holiday season

Published

3 weeks ago

October 31, 2024

Press Release

Give the gift of great skin this holiday season

Skinstitut Holiday Gift Kits take the stress out of gifting

Toronto, October 31, 2024 – Beauty gifts are at the top of holiday wish lists this year, and Laser Clinics Canada, a leader in advanced beauty treatments and skincare, is taking the pressure out of seasonal shopping. Today, Laser Clincs Canada announces the arrival of its 2024 Holiday Gift Kits, courtesy of Skinstitut, the exclusive skincare line of Laser Clinics Group.

In time for the busy shopping season, the limited-edition Holiday Gifts Kits are available in Laser Clinics locations in the GTA and Ottawa. Clinics are conveniently located in popular shopping centers, including Hillcrest Mall, Square One, CF Sherway Gardens, Scarborough Town Centre, Rideau Centre, Union Station and CF Markville. These limited-edition Kits are available on a first come, first served basis.

“These kits combine our best-selling products, bundled to address the most relevant skin concerns we’re seeing among our clients,” says Christina Ho, Senior Brand & LAM Manager at Laser Clinics Canada. “With several price points available, the kits offer excellent value and suit a variety of gift-giving needs, from those new to cosmeceuticals to those looking to level up their skincare routine. What’s more, these kits are priced with a savings of up to 33 per cent so gift givers can save during the holiday season.

There are two kits to select from, each designed to address key skin concerns and each with a unique theme — Brightening Basics and Hydration Heroes.

Brightening Basics is a mix of everyday essentials for glowing skin for all skin types. The bundle comes in a sleek pink, reusable case and includes three full-sized products: 200ml gentle cleanser, 50ml Moisture Defence (normal skin) and 30ml1% Hyaluronic Complex Serum. The Brightening Basics kit is available at $129, a saving of 33 per cent.

Hydration Heroes is a mix of hydration essentials and active heroes that cater to a wide variety of clients. A perfect stocking stuffer, this bundle includes four deluxe products: Moisture 15 15 ml Defence for normal skin, 10 ml 1% Hyaluronic Complex Serum, 10 ml Retinol Serum and 50 ml Expert Squalane Cleansing Oil. The kit retails at $59.

In addition to the 2024 Holiday Gifts Kits, gift givers can easily add a Laser Clinic Canada gift card to the mix. Offering flexibility, recipients can choose from a wide range of treatments offered by Laser Clinics Canada, or they can expand their collection of exclusive Skinstitut products.

	Brightening Basics 2024 Holiday Gift Kit by Skinstitut, available exclusively at Laser Clincs Canada clinics and online at skinstitut.ca.

Hydration Heroes 2024 Holiday Gift Kit by Skinstitut – available exclusively at Laser Clincs Canada clinics and online at skinstitut.ca.

Health

Here is how to prepare your online accounts for when you die

Published

4 weeks ago

October 24, 2024

Anne Joseph

LONDON (AP) — Most people have accumulated a pile of data — selfies, emails, videos and more — on their social media and digital accounts over their lifetimes. What happens to it when we die?

It’s wise to draft a will spelling out who inherits your physical assets after you’re gone, but don’t forget to take care of your digital estate too. Friends and family might treasure files and posts you’ve left behind, but they could get lost in digital purgatory after you pass away unless you take some simple steps.

Here’s how you can prepare your digital life for your survivors:

Apple

The iPhone maker lets you nominate a “ legacy contact ” who can access your Apple account’s data after you die. The company says it’s a secure way to give trusted people access to photos, files and messages. To set it up you’ll need an Apple device with a fairly recent operating system — iPhones and iPads need iOS or iPadOS 15.2 and MacBooks needs macOS Monterey 12.1.

For iPhones, go to settings, tap Sign-in & Security and then Legacy Contact. You can name one or more people, and they don’t need an Apple ID or device.

You’ll have to share an access key with your contact. It can be a digital version sent electronically, or you can print a copy or save it as a screenshot or PDF.

Take note that there are some types of files you won’t be able to pass on — including digital rights-protected music, movies and passwords stored in Apple’s password manager. Legacy contacts can only access a deceased user’s account for three years before Apple deletes the account.

Google

Google takes a different approach with its Inactive Account Manager, which allows you to share your data with someone if it notices that you’ve stopped using your account.

When setting it up, you need to decide how long Google should wait — from three to 18 months — before considering your account inactive. Once that time is up, Google can notify up to 10 people.

You can write a message informing them you’ve stopped using the account, and, optionally, include a link to download your data. You can choose what types of data they can access — including emails, photos, calendar entries and YouTube videos.

There’s also an option to automatically delete your account after three months of inactivity, so your contacts will have to download any data before that deadline.

Facebook and Instagram

Some social media platforms can preserve accounts for people who have died so that friends and family can honor their memories.

When users of Facebook or Instagram die, parent company Meta says it can memorialize the account if it gets a “valid request” from a friend or family member. Requests can be submitted through an online form.

The social media company strongly recommends Facebook users add a legacy contact to look after their memorial accounts. Legacy contacts can do things like respond to new friend requests and update pinned posts, but they can’t read private messages or remove or alter previous posts. You can only choose one person, who also has to have a Facebook account.

You can also ask Facebook or Instagram to delete a deceased user’s account if you’re a close family member or an executor. You’ll need to send in documents like a death certificate.

TikTok

The video-sharing platform says that if a user has died, people can submit a request to memorialize the account through the settings menu. Go to the Report a Problem section, then Account and profile, then Manage account, where you can report a deceased user.

Once an account has been memorialized, it will be labeled “Remembering.” No one will be able to log into the account, which prevents anyone from editing the profile or using the account to post new content or send messages.

It’s not possible to nominate a legacy contact on Elon Musk’s social media site. But family members or an authorized person can submit a request to deactivate a deceased user’s account.

Passwords

Besides the major online services, you’ll probably have dozens if not hundreds of other digital accounts that your survivors might need to access. You could just write all your login credentials down in a notebook and put it somewhere safe. But making a physical copy presents its own vulnerabilities. What if you lose track of it? What if someone finds it?

Instead, consider a password manager that has an emergency access feature. Password managers are digital vaults that you can use to store all your credentials. Some, like Keeper,Bitwarden and NordPass, allow users to nominate one or more trusted contacts who can access their keys in case of an emergency such as a death.

But there are a few catches: Those contacts also need to use the same password manager and you might have to pay for the service.

___

Is there a tech challenge you need help figuring out? Write to us at onetechtip@ap.org with your questions.

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Health

Pediatric group says doctors should regularly screen kids for reading difficulties

Published

4 weeks ago

October 23, 2024

Anne Joseph

The Canadian Paediatric Society says doctors should regularly screen children for reading difficulties and dyslexia, calling low literacy a “serious public health concern” that can increase the risk of other problems including anxiety, low self-esteem and behavioural issues, with lifelong consequences.

New guidance issued Wednesday says family doctors, nurses, pediatricians and other medical professionals who care for school-aged kids are in a unique position to help struggling readers access educational and specialty supports, noting that identifying problems early couldhelp kids sooner — when it’s more effective — as well as reveal other possible learning or developmental issues.

The 10 recommendations include regular screening for kids aged four to seven, especially if they belong to groups at higher risk of low literacy, including newcomers to Canada, racialized Canadians and Indigenous Peoples. The society says this can be done in a two-to-three-minute office-based assessment.

Other tips encourage doctors to look for conditions often seen among poor readers such as attention-deficit hyperactivity disorder; to advocate for early literacy training for pediatric and family medicine residents; to liaise with schools on behalf of families seeking help; and to push provincial and territorial education ministries to integrate evidence-based phonics instruction into curriculums, starting in kindergarten.

Dr. Scott McLeod, one of the authors and chair of the society’s mental health and developmental disabilities committee, said a key goal is to catch kids who may be falling through the cracks and to better connect families to resources, including quicker targeted help from schools.

“Collaboration in this area is so key because we need to move away from the silos of: everything educational must exist within the educational portfolio,” McLeod said in an interview from Calgary, where he is a developmental pediatrician at Alberta Children’s Hospital.

“Reading, yes, it’s education, but it’s also health because we know that literacy impacts health. So I think that a statement like this opens the window to say: Yes, parents can come to their health-care provider to get advice, get recommendations, hopefully start a collaboration with school teachers.”

McLeod noted that pediatricians already look for signs of low literacy in young children by way of a commonly used tool known as the Rourke Baby Record, which offers a checklist of key topics, such as nutrition and developmental benchmarks, to cover in a well-child appointment.

But he said questions about reading could be “a standing item” in checkups and he hoped the society’s statement to medical professionals who care for children “enhances their confidence in being a strong advocate for the child” while spurring partnerships with others involved in a child’s life such as teachers and psychologists.

The guidance said pediatricians also play a key role in detecting and monitoring conditions that often coexist with difficulty reading such as attention-deficit hyperactivity disorder, but McLeod noted that getting such specific diagnoses typically involves a referral to a specialist, during which time a child continues to struggle.

He also acknowledged that some schools can be slow to act without a specific diagnosis from a specialist, and even then a child may end up on a wait list for school interventions.

“Evidence-based reading instruction shouldn’t have to wait for some of that access to specialized assessments to occur,” he said.

“My hope is that (by) having an existing statement or document written by the Canadian Paediatric Society … we’re able to skip a few steps or have some of the early interventions present,” he said.

McLeod added that obtaining specific assessments from medical specialists is “definitely beneficial and advantageous” to know where a child is at, “but having that sort of clear, thorough assessment shouldn’t be a barrier to intervention starting.”

McLeod said the society was partly spurred to act by 2022’s “Right to Read Inquiry Report” from the Ontario Human Rights Commission, which made 157 recommendations to address inequities related to reading instruction in that province.

He called the new guidelines “a big reminder” to pediatric providers, family doctors, school teachers and psychologists of the importance of literacy.

“Early identification of reading difficulty can truly change the trajectory of a child’s life.”

This report by The Canadian Press was first published Oct. 23, 2024.

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