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. 2023 Jun 7;20(6):e1004245. doi: 10.1371/journal.pmed.1004245

Risk of myocarditis and pericarditis after a COVID-19 mRNA vaccine booster and after COVID-19 in those with and without prior SARS-CoV-2 infection: A self-controlled case series analysis in England

Julia Stowe 1, Elizabeth Miller 2,*, Nick Andrews 1, Heather J Whitaker 1
PMCID: PMC10286992  PMID: 37285378

Abstract

Background

An increased risk of myocarditis or pericarditis after priming with mRNA Coronavirus Disease 2019 (COVID-19) vaccines has been shown but information on the risk post-booster is limited. With the now high prevalence of prior Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, we assessed the effect of prior infection on the vaccine risk and the risk from COVID-19 reinfection.

Methods and findings

We conducted a self-controlled case series analysis of hospital admissions for myocarditis or pericarditis in England between 22 February 2021 and 6 February 2022 in the 50 million individuals eligible to receive the adenovirus-vectored vaccine (ChAdOx1-S) for priming or an mRNA vaccine (BNT162b2 or mRNA-1273) for priming or boosting. Myocarditis and pericarditis admissions were extracted from the Secondary Uses Service (SUS) database in England and vaccination histories from the National Immunisation Management System (NIMS); prior infections were obtained from the UK Health Security Agency’s Second-Generation Surveillance Systems. The relative incidence (RI) of admission within 0 to 6 and 7 to 14 days of vaccination compared with periods outside these risk windows stratified by age, dose, and prior SARS-CoV-2 infection for individuals aged 12 to 101 years was estimated. The RI within 27 days of an infection was assessed in the same model. There were 2,284 admissions for myocarditis and 1,651 for pericarditis in the study period. Elevated RIs were only observed in 16- to 39-year-olds 0 to 6 days postvaccination, mainly in males for myocarditis. Both mRNA vaccines showed elevated RIs after first, second, and third doses with the highest RIs after a second dose 5.34 (95% confidence interval (CI) [3.81, 7.48]; p < 0.001) for BNT162b2 and 56.48 (95% CI [33.95, 93.97]; p < 0.001) for mRNA-1273 compared with 4.38 (95% CI [2.59, 7.38]; p < 0.001) and 7.88 (95% CI [4.02, 15.44]; p < 0.001), respectively, after a third dose. For ChAdOx1-S, an elevated RI was only observed after a first dose, RI 5.23 (95% CI [2.48, 11.01]; p < 0.001). An elevated risk of admission for pericarditis was only observed 0 to 6 days after a second dose of mRNA-1273 vaccine in 16 to 39 year olds, RI 4.84 (95% CI [1.62, 14.01]; p = 0.004). RIs were lower in those with a prior SARS-CoV-2 infection than in those without, 2.47 (95% CI [1.32,4.63]; p = 0.005) versus 4.45 (95% [3.12, 6.34]; p = 0.001) after a second BNT162b2 dose, and 19.07 (95% CI [8.62, 42.19]; p < 0.001) versus 37.2 (95% CI [22.18, 62.38]; p < 0.001) for mRNA-1273 (myocarditis and pericarditis outcomes combined). RIs 1 to 27 days postinfection were elevated in all ages and were marginally lower for breakthrough infections, 2.33 (95% CI [1.96, 2.76]; p < 0.001) compared with 3.32 (95% CI [2.54, 4.33]; p < 0.001) in vaccine-naïve individuals respectively.

Conclusions

We observed an increased risk of myocarditis within the first week after priming and booster doses of mRNA vaccines, predominantly in males under 40 years with the highest risks after a second dose. The risk difference between the second and the third doses was particularly marked for the mRNA-1273 vaccine that contains half the amount of mRNA when used for boosting than priming. The lower risk in those with prior SARS-CoV-2 infection, and lack of an enhanced effect post-booster, does not suggest a spike-directed immune mechanism. Research to understand the mechanism of vaccine-associated myocarditis and to document the risk with bivalent mRNA vaccines is warranted.


In a nationwide, self-controlled case series analysis conducted in England, Julia Stowe and colleagues investigate the effect of prior SARS CoV-2 infection on the risk of hospital admission for myocarditis or pericarditis after primary or booster vaccination and after a confirmed SARS-CoV-2 infection.

Author summary

Why was this study done?

  • Primary and booster immunisation with mRNA Coronavirus Disease 2019 (COVID-19) vaccine have been associated with an increased risk of acute myocarditis.

  • Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection may itself cause myocarditis or pericarditis.

  • However, the effect of prior vaccination on this risk, and on the risk after a reinfection, has not been investigated.

What did the researchers do and find?

  • We conducted a nationwide study in England to assess the risk of hospital admission for myocarditis or pericarditis after primary or booster and the risk after a confirmed SARS-CoV-2 infection in those with and without a prior confirmed SARS-CoV-2 infection.

  • Elevated risks of myocarditis were found up to 6 days after each of priming dose of the available mRNA vaccines (BNT162b2 and mRNA-1723) and after mRNA booster doses following a mRNA priming course but not after a priming course of the adenovirus-vectored vaccine ChAdOx1-S. The only elevated seen after the ChAdOx1-S vaccine was after the dose in 16 to 39 year olds.

  • For both mRNA vaccines, elevated risks were found in those under 40 years old, predominantly in males, were highest after the second priming dose and were generally lower in those vaccinated after a prior SARS-CoV-2 infection.

  • There was an elevated risk of myocarditis and pericarditis in the 27 days after a SARS-CoV-2 infection which was higher in ≥40 year olds than 16 to 39 year olds and was still present in those with a reinfection or who had been vaccinated before infection.

What do these findings mean?

  • This study provides information for policy makers and those recommended to receive booster mRNA vaccines on the associated rare risk of myocarditis or pericarditis in a population with a high prevalence of prior SARS-CoV-2 infection.

  • The lower risk after a booster than primary course, and the lower risk in vaccinees with a prior SARS-CoV-2 infection, does not suggest an immune-mediated mechanism directed at the spike protein.

  • The greater risk associated with mRNA-1273 vaccines, which have a higher mRNA dose than BNT162b2 vaccines, and the substantially lower risk after the mRNA-booster which has half the mRNA content than used for priming, may be suggestive an mRNA dose-related mechanism but further work is required to determine this.

Introduction

The rapid development and global deployment of Coronavirus Disease 2019 (COVID-19) vaccines based on mRNA technology has been one of the outstanding successes of the response to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Licensed for human use for the first time in the pandemic, mRNA vaccines have proven highly effective at preventing severe morbidity and mortality from SARS-CoV-2 infection not only against the original Wuhan strain but subsequent variants of concern [1,2]. Overall, their safety profile has been good with no serious adverse events (SAEs) detected until the reports from Israel of temporally associated cases of acute myocarditis and pericarditis after primary vaccination with the BNT162b2 vaccine [3]. Reported cases were predominantly in younger males after the second dose, with onset clustering in the first week after vaccination.

Subsequent epidemiological studies in Israel and other countries using BNT162b2 and the mRNA-1273 vaccine confirmed an increased risk of myocarditis, largely after the second dose [48]. However, limited use of adenovirus-vectored vaccines such as ChAdOx1-S in these settings precluded a comparison of the risk by type of vaccine platform. Furthermore, these studies were conducted before the introduction of booster doses of COVID-19 vaccines, now recommended in many high-income settings where mRNA and adenovirus-vectored vaccines have been deployed. While there are case reports of acute myocarditis after booster doses of BNT162b2 vaccine, there is a paucity of epidemiological studies evaluating the risk after a booster dose of mRNA vaccines [911].

In the United Kingdom, there has been widespread use of the 2 mRNA vaccines and ChAdOx1-S vaccine with high population coverage both for the primary 2 dose course and the booster dose, the latter restricted to mRNA vaccines. A self-controlled case series (SCCS) analysis of the risk of hospital admission for myocarditis or pericarditis in England in those aged 16 years and older found an elevated risk within 28 days of a first dose of ChAdOx1-S and mRNA-1273 vaccines and after the second dose for each of the 2 mRNA vaccines [12]. This analysis was subsequently updated to mid-December 2021 to capture early data from the booster programme that began in mid-September 2021 with the BNT162b2 vaccine and was targeted at older age adults. While there was evidence of an elevated risk within 28 days of a booster dose of BNT162b2 vaccine, there was inadequate power to assess the risk by age and sex, nor for the mRNA-1273 vaccine [13]. We estimate the risk of myocarditis or pericarditis after a booster dose of BNT162b2 or mRNA-1273 vaccines in England by age and sex. We stratify post-booster outcomes according to the vaccine platform used for priming and assess the effect of prior SARS-CoV-2 infection on the vaccine-associated risk. We also assess the risk after a first or subsequent SARS-CoV-2 infection and the risk after a breakthrough infection in vaccinees.

Methods

Study population and study period

The study population comprised the resident population of 50 million individuals in England aged 12 years and older on the 31 August 2021. Age was defined as of 31 August 2021 as this best reflected eligibility for vaccination in the paediatric programme for 12 to 15 year olds that started after this date. Dates of admission for myocarditis or pericarditis were from 22 February 2021 to 6 February 2022.

Study design

Given the generally mild nature of vaccine-associated myocarditis [14], we analysed cases presenting in emergency care settings as well as those admitted to hospital. Two analytic methods were used, an SCCS analysis [15] supplemented by a retrospective cohort analysis. Both analyses assessed whether there was an increased risk of presentation to emergency care or admission to hospital with myocarditis and/or pericarditis in prespecified risk periods after any of the 3 COVID-19 vaccines used in England; ChAdOx1-S, BNT162b2, or mRNA-1273 vaccines. The SCCS analysis assessed the risk separately for myocarditis and pericarditis. The risk of acute myocarditis and/or pericarditis after a confirmed SARS-CoV-2 infection was also assessed in the SCCS analysis. All analyses used date of admission/attendance as the index date.

Vaccination database

Immunisation data was obtained from the National Immunisation Management System (NIMS), an individual level centralised register for the management of both seasonal influenza and COVID-19 vaccination records across England. It comprises the demographic characteristics for all residents in England eligible to receive COVID-19 vaccination (approximately 50 million individuals) including whether the person is in a priority group for COVID-19 vaccination because of comorbidities considered to render the individual clinically extremely vulnerable (CEV) [16]. A wider group of individuals with other comorbidities were flagged in the NIMS database retrospectively in mid-February 2021, hence the restriction of the start of the study period to late February 2021.

Emergency Care Data Set (ECDS)

Emergency care hospital attendances for myocarditis and/or pericarditis from the Emergency Care Data Set (ECDS), which is the National Health Service (NHS) dataset for urgent and emergency care in England. The attendances were identified using SNOMED CT (Systematized Nomenclature of Medicine–Clinical Terms) codes 50920009 myocarditis or 3238004 pericarditis. Only the first ECDS consultation during the study period was included in those without a prior ECDS consultation since 1 December 2019. The extracted ECDS attendances with the outcomes of interest that did not link with an NIMS record were excluded from the analysis; these comprised 0.8% of the extracted ECDS attendances.

Hospital admissions database (SUS)

The Secondary Uses Service (SUS) dataset, a database of timely completed hospital admissions for all NHS hospitals in England, was used to identify an individual’s first admission due to myocarditis and/or pericarditis in the study period (with no prior admission since 1 December 2019) using ICD10 codes I30 acute pericarditis, I40 acute myocarditis, and I51.4 myocarditis, unspecified in the first 3 diagnosis fields. The extracted SUS admissions with the outcomes of interest that did not link with an NIMS record were excluded from the analysis; these comprised 0.6% of the extracted SUS admissions.

SARS-CoV-2 infection dataset

The results of PCR and LFT tests carried out in the community in England, and PCR tests conducted in hospital patients, are collated in the UKHSA Second Generation Surveillance System (SGSS) that was used to identify confirmed SARS-CoV-2 infections in the study population. Repeat infections were defined as those in individuals with a second or subsequent positive test ≥90 days after a previous positive test.

Data linkage

Emergency care attendances, hospital admission records, and SGSS SARS-CoV-2 cases were linked to the NIMS dataset using NHS number. In all datasets used in the analysis, the NHS numbers were checked as valid using the final digit checksum that detects erroneous NHS numbers, which could lead to invalid linkage.

Construction of the self-controlled case series dataset (SCCS)

The SCCS dataset comprised of individuals aged 12 years and above with an ECDS consultation or hospital admission for myocarditis and/or pericarditis in the study period and who had received at least 1 dose of COVID-19 vaccine or had 1 or more confirmed SARS-CoV-2 infections at least 90 days apart. Vaccinated individuals who had received a mixed primary schedule, first and second doses <19 days apart, or second and third doses <56 days apart, or a third ChAdOx1-S dose, or a third dose before 1 September 2021 (before the booster programme started), or a first dose before 8 December 2020 (before the national vaccination programme started) were excluded as were any recipients of other COVID-19 vaccines that may have been given as part of a vaccine trial.

Construction of the cohort study dataset

NIMS monthly denominator and daily vaccination data were used to construct the cumulative vaccination status of the population eligible to receive COVID-19 vaccination by day stratified by age, gender, vaccine type, postvaccination intervals, CEV and other clinical risk group, ethnic group and English region. Postvaccination intervals were stratified by 0 to 6, 7 to 13, 14+ days after a first, second dose or third dose, and separately for ChAdOx1-S, BNT162b2, and mRNA-1273 vaccines (and for these primary schedules combined with the BNT162b2 and mRNA 1273 boosters), or unvaccinated. The same exclusions were applied to mixed or other nonstandard schedules as in the SCCS dataset. Age was stratified into 12 to 15, 16 to 17, 18 to 19, then 5-year bands. Ethnic group was collapsed into 5 main groups: White, Mixed or Multiple ethnic groups, Asian or Asian British, Black, African, Caribbean or Black British, and an unknown group.

Myocarditis and pericarditis events were stratified by the same factors and were merged with the NIMS data to obtain a stratified dataset of event counts and population denominators by day during the study period. Individuals who were initially unvaccinated but then received a vaccine in the study period, contributed to the unvaccinated person time. As outcome events were rare, for computational simplicity and to allow more rapid delivery of results for policy makers person time was censored at 6 February 2022 not at event date. Individuals who died were removed from the cohort at the end of the month in which they died using information on deaths in the NIMS denominator files.

Statistical analysis plan

A statistical analysis plan was drawn up in advance as part of the protocol (S1 Protocol) for which the key elements are summarised below.

SCCS analysis

The relative incidence (RI) of myocarditis and/or pericarditis in specified risk periods after vaccination and SARS-CoV-2 infection were estimated in the same model. A key assumption of the SCCS method is that the exposure and event are independent—an assumption which is violated if vaccination is deferred after an event until recovery (short-term event dependence), or subsequent doses are contraindicated after an event (long-term event dependence). The model accounted for short-term dependence, with the appropriate length of the preexposure period investigated; long-term event dependence was also investigated (S1 Appendix). These analyses indicated a pre-vaccination period of 21 days would be adequate to account for short-term event dependence and that there was no major concerns regarding longer-term dependence.

For the vaccination effect, the incidence in the 0 to 6 and 7 to 13 days after any dose of COVID-19 vaccine was compared to the incidence periods in vaccinated individuals outside this window using a dataset restricted to vaccinated individuals with myocarditis or pericarditis. Period adjustment in 4 weekly intervals was included in the model. Analyses comprised (i) all ages 12+; (ii) restricting to ages 16 to 39; (iii) ages 40+; (iv) ages 12 to 15; (v) males only; and (vi) females only. The analyses in ages 12+, 16 to 39, and 40+ in SUS using the SCCS method and with myocarditis and pericarditis combined were the primary analyses. As there were 16 vaccine dose and post vaccine interval combinations for each of these, this gave a total of 48 tests. All other analyses were secondary or exploratory. To account for this large number of primary and secondary assessments, the prespecified significance level was set at p < 0.001. RI was not estimated for risk periods with <2 cases. P-values were calculated using the Z test. In an exploratory analysis, vaccinated individuals were restricted to those with a prior confirmed SARS-CoV-2 infection to investigate whether preexisting immunity affected the vaccine risk. To assess the potential for ascertainment bias when the association between mRNA vaccination and myocarditis was publicised by the Medical and Healthcare products Agency (MHRA), a sensitivity analysis restricting cases to those presenting by 23 August 2021 was also conducted. At the request of reviewers further stratification of myocarditis results for those aged 16 to 39 years by age and gender were conducted.

For assessing the risk of SARS-CoV-2 infection, the exposure date was the first positive test date for that individual in the study period plus any subsequent new positive tests separated by ≥90 days. A postinfection risk period of 1 to 27 days was specified with those tested on the day they present to hospital or emergency care (day 0) analysed separately. A 14-day preinfection window was included. Two datasets were analysed, one restricted to vaccinated individuals and the other including in addition unvaccinated individuals with a confirmed SARS-CoV-2 infection.

In ad hoc analyses, the infection risk was stratified by first infection or reinfection, vaccine status (unvaccinated or at least 1 dose), and by variant using date of infection as a proxy for infecting variant (Delta replacing Alpha on 17 May and Omicron replacing Delta on 13 December).

Cohort analysis

Poisson regression was used to estimate the RI of events in the prespecified postvaccination risk periods compared with the unvaccinated period with an offset for population at risk (person days). The model adjusted for age group (12 to 15, 16 to 17, 18 to 19, then 5-year bands), gender, ethnic group, region, CEV, other clinical risk group, and 4-week interval. The core model had an age stratification of 12 to 15, 16 to 39, 40+, as well as all ages combined, with additional analyses showing stratification by gender (all ages).

Attributable risk estimates

Attributable cases in the risk intervals with RIs p < 0.001 were estimated from the attributable fraction AF = (RI-1)/RI multiplied by the number of cases in that interval. Attributable risk was then calculated from the attributable cases divided by either the number of doses administered (for vaccine risk) or the number of SARS-CoV-2 infections or reinfections (for SARS-CoV-2 infection risk).

STROBE guidelines

The study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 STROBE Checklist).

Results

There was a total of 3,124 hospital admissions in England with a diagnosis of myocarditis or pericarditis and 7,933 emergency care consultations between 22 February 2021 and 6 February 2022 (Table 1). Admission rates for myocarditis were generally higher than for pericarditis, whereas ECDS consultation rates were higher for pericarditis than myocarditis, particularly among those aged under 40 years. Confirmed SARS-CoV-2 infections in those admitted with myocarditis or pericarditis reflected the changing incidence of COVID-19 over the study period with a drop in the last 4 weeks due to delays in diagnostic coding and admissions not completed by the time of the data extract on 4 April 2022 (Fig 1). At least 1 dose of a COVID-19 vaccine had been received by 6,672 (84.1%) of those attending emergency care and 3,382 (86.2%) of those admitted to hospital. In both the ECDS and SUS datasets, admission rates per 100,000 person years in males were about double those in females and increased sharply with age between 12 and 19 years, remaining fairly constant thereafter. ECDS consultation and SUS admission rates were higher among black British, African, or Caribbean than other ethnic groups and higher among those with a CEV or other “at risk” flag than in those without.

Table 1. Demographic and clinical features of the individuals with a hospital admission in SUS or an emergency care consultation in the ECDS dataset for myocarditis and pericarditis: data from entire eligible population in England.

person years SUS pericarditis case count = 1,651* SUS pericarditis risk per 100,000 SUS myocarditis case count = 2,284* SUS myocarditis risk per 100,000 ECDS pericarditis case count = 6,461 ECDS pericarditis risk per 100,000 ECDS myocarditis case count = 1,472 ECDS myocarditis risk per 100,000
Age group 12 to 15 2,742,347 8 0.29 28 1.02 111 4.05 42 1.53
16 to 17 1,305,334 30 2.30 73 5.59 151 11.57 71 5.44
18 to 19 1,296,676 54 4.16 119 9.18 241 18.59 118 9.10
20 to 24 3,730,389 119 3.19 233 6.25 757 20.29 241 6.46
25 to 29 4,196,722 117 2.79 199 4.74 754 17.97 184 4.38
30 to 34 4,513,956 127 2.81 200 4.43 715 15.84 163 3.61
35 to 39 4,297,665 106 2.47 166 3.86 705 16.40 144 3.35
40 to 44 3,956,356 126 3.18 153 3.87 565 14.28 91 2.30
45 to 49 3,768,292 131 3.48 155 4.11 517 13.72 84 2.23
50 to 54 4,013,470 140 3.49 157 3.91 486 12.11 61 1.52
55 to 59 3,903,178 139 3.56 166 4.25 431 11.04 74 1.90
60 to 64 3,320,364 124 3.73 145 4.37 293 8.82 57 1.72
65 to 69 2,773,874 111 4.00 113 4.07 242 8.72 45 1.62
70 to 74 2,732,488 125 4.57 122 4.46 191 6.99 36 1.32
75 to 79 2,069,915 82 3.96 101 4.88 146 7.05 31 1.50
80 to 84 1,390,802 61 4.39 91 6.54 83 5.97 17 1.22
85 to 89 868,675 39 4.49 44 5.07 55 6.33 10 1.15
90+ 504,934 12 2.38 19 3.76 18 3.56 3 0.59
Sex Male 25,717,812 1,132 4.40 1,456 5.66 4,634 18.02 1,001 3.89
Female 25,667,624 519 2.02 828 3.23 1,827 7.12 471 1.83
Region East of England 5,910,664 175 2.96 335 5.67 703 11.89 165 2.79
London 8,807,901 249 2.83 420 4.77 973 11.05 239 2.71
Midlands 9,496,410 220 2.32 321 3.38 986 10.38 248 2.61
North East and Yorkshire 7,641,777 217 2.84 273 3.57 938 12.27 186 2.43
North West 6,393,140 215 3.36 278 4.35 713 11.15 199 3.11
South East 8,025,838 365 4.55 445 5.54 1,230 15.33 267 3.33
South West 5,109,705 210 4.11 212 4.15 859 16.81 153 2.99
Ethnicity Asian 4,398,660 94 2.14 155 3.52 513 11.66 103 2.34
Black, African, Caribbean 1,756,382 108 6.15 133 7.57 468 26.65 95 5.41
Mixed, Multiple 820,496 22 2.68 45 5.48 145 17.67 38 4.63
NK 6,752,624 95 1.41 182 2.70 448 6.63 101 1.50
Other 1,173,462 42 3.58 69 5.88 165 14.06 48 4.09
White 36,483,810 1,290 3.54 1,700 4.66 4,722 12.94 1,087 2.98
Clinically vulnerable No 47,787,906 1,387 2.90 1,943 4.07 5,830 12.20 1,333 2.79
Yes 3,597,530 264 7.34 341 9.48 631 17.54 139 3.86
In an “at risk” group No 43,400,928 1,107 2.55 1,446 3.33 4,545 10.47 1,010 2.33
Yes 7,984,508 544 6.81 838 10.50 1,916 24.00 462 5.79
Unvaccinated 16,751,085 206 1.23 340 2.03 1,036 6.18 225 1.34
Primary course ChAdOx1 18,381,521 728 3.96 859 4.67 2,332 12.69 439 2.39
BNT162b2 15,459,412 670 4.33 972 6.29 2,833 18.33 728 4.71
mRNA-1273 793,417 47 5.92 112 14.12 259 32.64 79 9.96

*Eleven SUS cases had a diagnosis of both myocarditis and pericarditis.

ECDS, Emergency Care Data Set; SUS, Secondary Uses Service.

Fig 1. Number of SARS-CoV-2 positive tests among individuals admitted to hospital with myocarditis or pericarditis by test week: data from entire eligible population in England.

Fig 1

SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2.

Postvaccination analyses

Elevated RI estimates (p < 0.01 or <0.001) for hospital admission with myocarditis after vaccination were found in the SCCS analysis in those aged under 40 years in the 0 to 6 day postvaccination period after each of the mRNA vaccines and also after the first dose of ChAdOx1-S vaccine (Table 2). RIs were highest after the second mRNA dose and generally higher after the mRNA-1273 than the BNT162b2 vaccine, though more similar when given as a booster. Stratification of the results by sex showed elevated RIs only in males with the exception of 0 to 6 days after a second dose of mRNA-1273 vaccine for which the RI was 58.28 (95% confidence interval (CI) [34.78, 97.52], p < 0.001) in males and 23.26 (95% CI [6.68, 82.07], p < 0.001) in females (Table 2).

Table 2. Adjusted RI with 95% CIs of admissions with myocarditis in SUS using the SCCS analysis (adjusted for time period (4 weekly period)) in risk intervals after a COVID-19 vaccine or after a positive SARS-CoV-2 test stratified by age group and gender.

Admissions (SUS dataset)
Ages 16–39, n = 765 Ages 40+, n = 1,134
Vaccination status Interval (days) Case count Person years RI (95% CI) p-Value Case count Person years RI (95% CI) p-Value
Baseline 486 544 823 801.3
ChAdOx1-S Dose 1 0 to 6 9 2.2 5.23 (2.48, 11.01) <0.001 11 7.8 1.45 (0.78, 2.71) 0.238
7 to 13 n < 2 2.4 9 8.9 0.98 (0.5, 1.93) 0.955
Dose 2 0 to 6 2 2.6 1.01 (0.25, 4.13) 0.991 7 12.5 0.53 (0.25, 1.12) 0.097
7 to 13 6 2.6 2.88 (1.25, 6.65) 0.013 7 12.4 0.53 (0.25, 1.13) 0.101
BNT162b2 Dose 1 0 to 6 18 9 2.23 (1.37, 3.63) 0.001 5 2.3 2.01 (0.78, 5.2) 0.151
7 to 13 14 9.2 1.62 (0.94, 2.79) 0.084 3 2.8 1.03 (0.32, 3.3) 0.965
Dose 2 0 to 6 40 8 5.34 (3.81, 7.48) <0.001 6 7.2 0.79 (0.35, 1.8) 0.578
7 to 13 17 7.9 2.25 (1.37, 3.68) 0.001 5 7.2 0.67 (0.27, 1.62) 0.37
Booster 0 to 6 17 3.5 4.38 (2.59, 7.38) <0.001 22 13.2 1.5 (0.97, 2.33) 0.07
7 to 13 6 3.3 1.65 (0.72, 3.78) 0.237 24 13.1 1.62 (1.06, 2.47) 0.025
mRNA-1273 Dose 1 0 to 6 8 1.8 8.69 (4.01, 18.81) <0.001 2 0.3 7.02 (1.53, 32.23) 0.012
7 to 13 n < 2 1.8 n < 2 0.3
Dose 2 0 to 6 38 1.4 56.48 (33.95, 93.97) <0.001 n < 2 0.2
7 to 13 n < 2 1.4 n < 2 0.2
Booster 0 to 6 11 1.4 7.88 (4.02, 15.44) <0.001 3 2.8 0.88 (0.28, 2.8) 0.827
7 to 13 n < 2 1.4 5 2.8 1.49 (0.6, 3.69) 0.39
COVID infection test day 0 10 1.1 8.23 (4.34, 15.6) <0.001 20 0.9 25.6 (16.09, 40.73) <0.001
Post COVID infection: 1–27d 49 28.7 1.67 (1.22, 2.28) <0.001 72 24 3.64 (2.76, 4.81) <0.001
All 16+ year olds: males, n = 1,194 All 16+ year olds: females, n = 721
Vaccination status Interval (days) Case count Person years RI (95% CI) p-Value Case count Person years RI (95% CI) p-Value
Baseline 792 844.7 523 513.2
ChAdOx1-S Dose 1 0 to 6 11 6.3 2.01 (1.08, 3.76) 0.028 9 3.7 2.75 (1.35, 5.62) 0.006
7 to 13 6 6.9 0.97 (0.43, 2.21) 0.941 4 4.4 1.05 (0.38, 2.89) 0.92
Dose 2 0 to 6 6 8.9 0.79 (0.35, 1.78) 0.563 3 6.2 0.5 (0.16, 1.58) 0.239
7 to 13 10 8.9 1.32 (0.7, 2.49) 0.398 3 6.2 0.49 (0.16, 1.54) 0.221
BNT162b2 Dose 1 0 to 6 16 8.5 2.04 (1.22, 3.42) 0.006 8 3.2 2.62 (1.28, 5.36) 0.009
7 to 13 13 8.9 1.59 (0.91, 2.78) 0.105 7 3.4 1.9 (0.88, 4.1) 0.103
Dose 2 0 to 6 40 9.7 4.42 (3.18, 6.14) <0.001 8 5.6 1.6 (0.78, 3.27) 0.196
7 to 13 16 9.6 1.78 (1.08, 2.94) 0.025 6 5.6 1.18 (0.52, 2.68) 0.685
Booster 0 to 6 22 9.4 2.01 (1.29, 3.11) 0.002 17 7.3 2 (1.21, 3.3) 0.007
7 to 13 18 9.2 1.64 (1.01, 2.65) 0.044 12 7.2 1.45 (0.8, 2.61) 0.219
mRNA-1273 Dose 1 0 to 6 9 1.7 10.48 (5.02, 21.87) <0.001 n < 2 0.4
7 to 13 n < 2 1.7 n < 2 0.4
Dose 2 0 to 6 35 1.3 58.24 (34.78, 97.52) <0.001 4 0.2 23.26 (6.68, 81.06) <0.001
7 to 13 n < 2 1.3 n < 2 0.2
Booster 0 to 6 12 2.7 3.8 (2.06, 7.01) <0.001 2 1.5 1.11 (0.27, 4.61) 0.882
7 to 13 3 2.7 0.99 (0.31, 3.15) 0.99 3 1.4 1.72 (0.53, 5.56) 0.363
COVID infection test day 0 21 1.3 17.19 (10.98, 26.89) <0.001 10 0.8 13.31 (6.99, 25.32) <0.001
Post COVID infection: 1–27d 76 32.8 2.5 (1.93, 3.24) <0.001 47 20.6 2.47 (1.77, 3.45) <0.001

CI, confidence interval; COVID-19, Coronavirus Disease 2019; RI, relative incidence; SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2; SCCS, self-controlled case series; SUS, Secondary Uses Service.

Further age stratification within 16 to 39 year olds showed higher risks in 16 to 24 than 25 to 39 year olds, RI 102.3 (95% CI [49.88, 209.6], p < 0.001) compared with 29.67 (95% CI [14.58, 60.4], p < 0.001), respectively, with the elevated risk predominantly seen in males (Table A in S2 Appendix).

There was less evidence of a vaccine-associated risk for pericarditis admissions apart from 0 to 6 days after a second dose of mRNA-1273 vaccine in 16 to 39 year olds, RI 4.82 (95% CI [1.82, 14.01], p = 0.004 (Table B in S2 Appendix)). However, ECDS visits for both pericarditis and myocarditis showed elevated risks in 16 to 39 year olds that paralleled those seen in the myocarditis admissions (Table C in S2 Appendix).

When stratified by the vaccine given for priming, both mRNA vaccines showed evidence of an elevated risk (myocarditis and pericarditis combined) in the 0- to 6-day period when given as a booster after 2 priming doses of the BNT162b2 vaccine in 16 to 39 year olds—RI 3.23 (95% CI [1.85, 5.64], p < 0.001) for a BNT162b2 booster and 6.06 (95% CI [2.95, 5.14], p < 0.001); there was insufficient data to evaluate the risk after 3 doses of the mRNA-1273. RIs were not significantly elevated when BNT162b2 or mRNA-1273 booster doses were given after a priming course of ChAdOx1-S vaccine (Table D in S2 Appendix).

The results of the cohort analysis of hospital admissions were similar to those obtained in the SCCS analysis when stratified by age and, for the booster effect, when stratified by the vaccine given for priming (Table E in S2 Appendix). For the 40+ age group RIs from 14+ days after a booster dose were below one when an mRNA vaccine was given after ChAdOx1-S or BNT162b2 priming.

Results were similar in the sensitivity analysis in which the study period ended on 23 August 2021 prior to the MHRA advice about the risk of myocarditis with mRNA vaccines, though with generally lower RI estimates (Fig 2, Table F in S2 Appendix).

Fig 2. Comparing the RI estimates from the SCCS analysis of myocarditis or pericarditis using hospital admissions for whole study period (6 February 2022) with the truncated 23 August 2021 period.

Fig 2

All ages, by vaccine type. RI, relative incidence; SCCS, self-controlled case series.

When restricted to individuals with a prior confirmed SARS-CoV-2 infection RI estimates in 16 to 39 year olds were generally lower than in those who were infection naïve though elevated RIs were still evident after a second dose of BNT162b2 and mRNA-1273 vaccines in those with prior infection—RI 2.47 (95% CI [1.32, 4.63], p = 0.005) and 19.07 (95% CI [8.62, 42.19], p < 0.001), respectively, and also after booster doses of these vaccines (Table G in S2 Appendix). For ChAdOx1-S, all the cases after a first dose were in those who were infection naïve, RI 4.21 (2.04, 8.72).

Vaccination of 12 to 15 year olds only began on 13 September 2021 and was restricted to the use of the mRNA vaccines, predominantly BNT162b2 in the study period. The results of the cohort and SCCS analysis for emergency care consultations for this age group showed an elevated risk of an ECDS attendance in the 0 to 6 day and 7 to 13 days after BNT162b2 vaccine for myocarditis or pericarditis with similar risks after the first and second doses (Table H in S2 Appendix). For hospital admissions, there were few cases in this age group (Table 1) and only the cohort analysis was conducted for which an elevated RI of 12.16 (95% CI [2.21, 66.7], p = 0.004), 0 to 6 days after a second dose was found.

Postinfection analyses

An elevated RI of admission for myocarditis 1 to 27 days after a confirmed SARS-CoV-2 infection was evident (Table 2); RI estimates were higher in ≥40 than 16 to 39 year olds and higher in those tested on the day of hospital admission (day 0). The post SARS-CoV-2 infection risk was similar between genders. Pericarditis admissions also showed elevated risks within the month after a SARS-CoV-2 infection (Table B in S2 Appendix).

Stratification of the postinfection risk of myocarditis or pericarditis by first versus second or subsequent infections, by vaccination status and by variant showed no significant differences between RIs for the day 1 to 27 risk period, though point estimates were lower for breakthrough infections and for Omicron than earlier variants (Table 3).

Table 3. RI of infection by the SCCS method (adjusted for time period (4 weekly period)) for hospital admitted patients with myocarditis or pericarditis aged 12+ years who tested positive for SARS-CoV-2 infection.

Interval from test to admission Type of infection Vaccination status Variant
First Reinfection Unvaccinated^ Vaccinated ≥1 dose Alpha Delta Omicron
Day 0
 Number cases 50 4 19 35 3 29 22
 Person years 3.1 0.9 1 3.1 0.3 2.3 1.4
 RI (95% CIs) 17.29 4.75 24.66 11.98 13.96 13.18 16.79
(12.96, 23.00) (1.77, 12.80) (15.42, 39.44) (8.39, 16.59) (4.37, 46.64) (9.06, 19.17) (10.83, 26.01)
p < 0.001 p = 0.002 p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001
Days 1–27
 Number cases 193 50 71 172 27 150 66
 Person years 82.4 22.5 27 77.8 10.8 62.1 32
 RI (95% CIs) 2.57 2.49 3.32 2.33 3.13 2.58 2.34
(2.19, 3.01) (1.82, 3.41) (2.54, 4.33) (1.96, 2.76) (2.02, 4.84) (2.15, 3.1) (1.77, 3.1)
p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001

^ Includes infections before the first dose.

CI, confidence interval; RI, relative incidence; SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2; SCCS, self-controlled case series.

Attributable risk

The attributable risk estimates from the SCCS analysis for hospital admissions for myocarditis or pericarditis after vaccination and after a SARS-CoV-2 infection are shown in Table 4 for exposures with p < 0.001 for an elevated RI estimate. Attributable risk estimates for admission for myocarditis or pericarditis within 0 to 27 days of a laboratory-confirmed were 10.2 and 18.1 per million in 16 to 39 and ≥40 year olds, respectively.

Table 4. Attributable risk estimates with 95% CIs for an admission for myocarditis; exposures with elevated RIs with p < 0.001 0–6 days post-vaccine and 0 to 27 days post a laboratory confirmed SARS-CoV-2 in the SCCS analysis using the dataset that includes infections in unvaccinated individuals.

Vaccine exposure Admissions in risk period RI Attributable fraction Attributable cases Doses Attributable risk per million vaccinations (95% CI)
0 to 6 days before admission 16 to 39 year olds
Dose 1 ChAdOx1 9 5.23 0.809 7.3 2,099,584 3.5 (2.6,3.9)
Dose 1 BNT162b2 18 2.23 0.552 9.9 9,705,976 1.02 (0.5,1.3)
Dose 2 BNT162b2 40 5.34 0.813 32.5 9,519,878 3.4 (3.1,3.6)
Booster BNT 162b2 17 4.38 0.772 13.1 5,319,875 2.5 (2.0,2.8)
Dose 1 mRNA 1273 8 8.69 0.885 7.1 1,023,825 6.9 (5.9,7.4)
Dose 2 mRNA 1273 38 56.48 0.982 37.3 881,058 42.4 (41.9,42.7)
Booster mRNA 1273 11 7.88 0.873 9.6 2,144,219 4.5 (3.9,4.8)
Vaccine exposure Admissions in risk period RI Attributable fraction Attributable cases Doses Attributable risk per million vaccinations (95% CI)
0 to 6 days before admission all 16+ year olds
Dose 2 BNT162b2: males 40 4.42 0.774 31.0 8,734,711 3.5 (3.1,3.8)
Dose 1 mRNA 1273: males 9 10.48 0.905 8.1 747,072 10.9 (9.6,11.5)
Dose 2 mRNA 1273: males 35 58.24 0.983 34.4 625,871 55.0 (54.3,55.3)
Booster mRNA 1273: males 12 3.8 0.737 8.8 3,539,697 2.5 (1.7,2.9)
Dose 2 mRNA 1273: females 4 23.26 0.957 3.8 498,121 7.7 (6.8,7.9)
SARS-CoV-2 infection 0–27 days before admission Admissions in risk period RI Attributable fraction Attributable cases Cases Attributable risk per million infections
16 to 39 year olds day 0 15 6.98 0.857 12.9 8,398,257 1.5 (1.4–1.6)
≥40 year olds day 0 37 23.56 0.958 35.4 6,570,699 5.4 (5.6, 5.5)
16–39 year olds days 1–27 113 2.09 0.522 58.9 8,398,257 7.0 (5.5, 8.3)
≥40 year olds days 1–27 124 3.07 0.674 83.6 6,570,699 12.7 (11.3, 13.9)

CI, confidence interval; RI, relative incidence; SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2; SCCS, self-controlled case series.

For 12 to 15 year olds, the attributable risk for an admission 0 to 6 days after a second dose based on a total of 2 cases was 3.0 (95% CI [2.1, 3.7]) per million.

Discussion

Our study showed an increased risk of hospital admission with myocarditis 0 to 6 days after an mRNA vaccine, predominantly in males aged 16 to 39 years with the highest risk in those aged 16 to 24 years. An elevated risk was evident after each of the priming doses with higher risks after a second dose of the mRNA-1273 than the BNT162b2 vaccine. There was also evidence of an increased risk after a booster dose of each of the mRNA vaccines when given after a priming course of BNT162b2 but not after a primary course of ChAdOx1-S vaccine. The only elevated risk seen after the ChAdOx1-S vaccine was post-first dose in 16 to 39 year olds. An elevated risk of hospital admission after a second or booster dose of the mRNA vaccines was still present in individuals vaccinated after a confirmed SARS-CoV-2 infection, though RIs were lower than in those without a prior infection. Our study also showed an increased RI of myocarditis and pericarditis after a SARS-CoV-2 infection which was not abrogated by prior vaccination or previous infection and was evident after each infecting variant.

While there was little evidence of an elevated risk of hospital admission for pericarditis after primary or booster vaccination, emergency care consultations showed elevated risks for pericarditis in 16 to 39 year olds 0 to 6 days after a first dose of ChAdOx1-S and after primary and booster doses of the mRNA vaccines. Hospital admission for pericarditis, particularly a first attack in an otherwise healthy young adult, is usually not indicated [17]. This is reflected in Table 1 that shows 3,401 emergency care consultations in <40 year olds for pericarditis but only 561 admissions. As a consequence, many of the postvaccination risk periods in the hospital admissions analysis for pericarditis had less than 2 cases for which RIs were not estimated. Emergency care consultations for pericarditis and myocarditis showed a similar pattern of elevated risks post-vaccine as admissions for myocarditis in adults aged 16 to 39 years which is supportive of the specificity of the diagnoses in the ECDS dataset.

Our results confirm the findings of earlier studies of the risk of myocarditis or pericarditis following primary immunisation with mRNA vaccines [48,12] and in addition show that while there is an elevated risk when mRNA vaccines are given as a booster dose, this is lower than after the second dose as suggested by other recent studies [13,1820]. The difference in risk between the second and booster dose was particularly marked for the mRNA-1273 vaccine. The quantity of mRNA in mRNA-1273 when used for boosting is 50 micrograms, half the amount when used for priming [21], compared with 30 micrograms in BNT162b2 vaccine when used for priming or boosting. This suggests that the risk of myocarditis after mRNA vaccines may in part be determined by mRNA dose, possibly the amount of double-stranded RNA (dsRNA) that can generate a dose-related innate immune activation and can be present in low quantities in the mRNA vaccines [22]. The rapid onset after vaccination, even after a first dose, would be consistent with such a direct effect. Based on case reports suggesting an increased risk in those vaccinated after infection, together with the increased risk after the second dose, an immune-mediated mechanism involving antibodies to some component of the spike protein has been proposed [2325]. However, our study showed that the vaccine risk was not exacerbated in those who had a prior SARS-CoV-2 infection, nor was the risk increased after a booster dose—scenarios which result in high levels of anti-spike IgG antibodies, particularly in younger adults [26].

The risk after ChAdOx1-S was confined to the first dose and may therefore involve a different mechanism to that induced by mRNA vaccines. Other systemic effects such as fever, headache, and malaise are also more common after a first than second dose of this vaccine [27], unlike the 2 mRNA vaccines for which systemic symptoms are more common after a second dose [28,29]. The complication of thrombosis with thrombocytopenia after ChAdOx1-S vaccine also occurs predominantly after a first dose but has a longer onset after vaccination than myocarditis suggesting an unrelated causal mechanism [16].

There was little power for assessment of the vaccine-associated risk in 12 to 15 year olds as the background rate of hospital admissions in this age group for myocarditis and pericarditis was low, around 1.1 per 100,000 person years with only 10 admissions at any time after a first or second dose of BNT162b2 vaccine. Nevertheless, the estimated attributable risk 0 to 6 days after a second dose (3 per million) was similar to that in 16 to 39 year olds (3.5 per million).

While we did not assess severity in vaccine-associated compared with unvaccinated cases, there were 20 deaths during admission or within a week of discharge among the 906 unvaccinated cases with myocarditis or pericarditis (2.2%) compared with 3 deaths during admission or within a week of discharge among the 265 cases (1.1%) with onset within 0 to 6 days of a dose of vaccine all with a diagnosis of myocarditis. Of these, 2 were after a first dose of ChAdOx1-S vaccine and a third after a booster dose of BNT162b2 given after ChAdOx1-S priming; all 3 individuals had underlying comorbidities and in addition 2 were aged 80 years or over, consistent with the early use of the ChAdOx1-S vaccine in high risk and elderly groups. The absence of fatal cases among healthy young adults with vaccine-associated myocarditis or pericarditis is reassuring and consistent with case reports of a benign outcome [14].

The post-vaccine attributable risk estimates for myocarditis or pericarditis were lower than reported in studies in some other settings. For example, in Israel, an excess risk of myocarditis in males (all ages) of 1 in 26,000 second doses of BNT162b2 vaccine (38.5 per million) was estimated. However, in Israel, clinicians were alerted to the risk of vaccine-associated myocarditis and were requested to actively report cases and, unlike England, almost all cases are admitted to hospital in Israel [3]. Differences in attributable risk are not just dependent on relative risks in the postvaccination period but also on the background rate of ascertainment of cases of myocarditis and pericarditis, which will reflect diagnostic and admission practices in the study population. It is difficult to directly compare RI estimates across studies due to differences in the postvaccination risk periods and age/sex stratification used in the analysis, but the same RI estimates will generate higher attributable risk estimates for populations with a higher background incidence of the outcome.

Unlike the vaccine-associated risk, the risk of myocarditis or pericarditis after a confirmed SARS-CoV-2 infection was greater in older adults than those under 40 years of age and was similar for each cardiac outcome. Our RI estimates are lower than reported in earlier Israeli and English studies [4,12], both of which covered periods when the predominant variant was Alpha and prior to the emergence of Omicron which is associated with an increased risk of reinfection and breakthrough infections in vaccinated individuals [30]. The English study also restricted the analysis to first recorded SARS-CoV-2 infection. We therefore conducted an ad hoc analysis to assess the effect of variant and of prior infection or vaccination on the risk of myocarditis/pericarditis following SARS-CoV-2 infection. Although not significantly different from each other, the direction of the differences in RIs is consistent with a higher risk in the earlier period when a greater proportion of SARS-CoV-2 cases were primary infections in unvaccinated individuals before the emergence of Omicron.

Day 0 was not included in the main postinfection risk period risk because case ascertainment will be enhanced compared to other risk periods by the practice of testing patients for SARS-CoV-2 infection on admission as part of infection control procedures. In addition, while some of the day 0 cases will be causally related to infection, in others, infection may be coincidental rather than causal and only detected because of the testing policy. The high RIs observed in our study on day 0 are therefore expected and are consistent with findings in other studies of hospital admission for COVID-19 complications [31]. The RI for admission in the 21 days before a positive test was generally around 1 and not elevated as found in an SCCS analysis of thrombotic conditions associated with SARS-CoV-2 infection in Sweden that was attributed to testing delays or nosocomial infection [31].

Ours is an observational study and so has inherent limitations. There is the potential for enhanced ascertainment of cases occurring shortly after vaccination due to vaccinees’ knowledge of the warnings issued by the MHRA about the risk of myocarditis with mRNA vaccines. While the postvaccination RI estimates were generally lower when the analysis was restricted to admissions before 23 August 2021 when the MHRA warning was first issued, the overall pattern of results was similar (Fig 2). However, it was not possible to make this comparison for 12 to 15 year olds, as vaccination for this age group was only routinely recommended after this date and it is possible that biased ascertainment contributed to the elevated RIs found in the age group. Another limitation is that ours was a database study without case note review so outcomes were reliant on routinely coded diagnoses in patients’ notes. The effect of this is difficult to assess as outcome misclassification usually results in an underestimate of the true RI but if it differs by vaccination status (for example, a greater tendency to assign a myocarditis code in unproven vaccinated cases once the adverse event was publicised by the MHRA), then the RI would be overestimated. The RIs for myocarditis from the ECDS analysis were generally lower than for the hospital admitted cases which would suggest that despite the higher incidence of outcome events, capture of true myocarditis or pericarditis cases is less accurate. It is also possible that by restricting our myocarditis and pericarditis codes to those occurring in the first 3 diagnosis fields, we may have missed some SARS-CoV-2–associated cases who were admitted for respiratory or other non-cardiac reasons which may have led to an underestimate of the frequency with which myocarditis or pericarditis occurs in COVID-19 patients. Also, the attributable risk estimates for COVID-19 used laboratory confirmed cases as the denominator and will be affected by the proportion of all SARS-CoV-2 infections captured by testing, precluding a direct comparison with vaccine-associated attributable risks.

While the SCCS method we used for the main analysis adjusts for potential time-invariant confounders such as comorbidities more reliably than the cohort method, the latter is better able to adjust for event-dependent exposures such as contraindication of further doses on the occurrence of an event after an earlier dose. However, as shown in S1 Appendix, there was little evidence of such a bias in our dataset. The similarity in results between the SCCS and cohort analysis suggests that the latter adequately adjusted for confounders. The lower RIs in the cohort analysis from 14 days postvaccination in those aged 40 years and older may reflect a true vaccine effect through prevention of COVID-19 and its associated risk of myocarditis which would not be detectable using the SCCS method.

In conclusion, our study provides estimates of the excess risk of an episode of a hospital admitted episode of myocarditis after a third dose of an mRNA vaccine in England which in 16 to 39 year olds was 2.5 and 4.5 per million for the BNT162b2 and mRNA-1273 vaccines, respectively. The comparable risk estimates after a second dose were 3.4 and 42.4 per million, respectively, with higher risks in males. The absence of acute fatal outcomes in healthy adults with vaccine-associated myocarditis in our study, and the lower risk of death or cardiac failure within 3 months compared with other causes of myocarditis demonstrated by others, is reassuring [32].

Supporting information

S1 STROBE Checklist. STROBE Checklist.

(XLSX)

S1 Protocol. Analysis of hospital admissions and emergency care consultations for acute myocarditis and pericarditis after COVID-19 vaccines in England.

(PDF)

S1 Appendix. Supplementary material.

Checking the self-controlled case series assumption of no long-term event-dependence. Figure A. Plots of preexposure and postexposure relative incidence, by preexposure period length, SUS data to 6 February 2022. Figure B. Plots of preexposure and postexposure relative incidence, by preexposure period length, ECDS data to 6 February 2022. Table A. Relative incidence estimates from the standard SCCS model and the event-dependent exposures SCCS model, SUS first cases in individuals with no recorded positive SARS-CoV-2 test before the end of the observation period (6 February 2022), N = 1,977. Table B. Relative incidence estimates from the standard SCCS model and the event-dependent exposures SCCS model, ECDS first cases in individuals with no recorded positive SARS-CoV-2 test before the end of the observation period (6 February 2022), N = 3,553.

(DOCX)

S2 Appendix. Supplementary tables.

Table A. Adjusted (adjusted for time period (4 weekly period)) RI of admissions with myocarditis after a COVID-19 vaccine by postvaccination risk interval in 16–24 and 25–39 year olds and 16–39 year olds by gender in SUS using the SCCS analysis—whole study period to 6 February 2022. Table B. Adjusted (for time period (4 weekly period)) RI of admissions with pericarditis after a COVID-19 vaccine by postvaccination risk interval by age group in SUS using the SCCS analysis—whole study period to 6 February 2022. Table C. Adjusted (for time period (4 weekly period)) RI of attendances with myocarditis or pericarditis after a COVID-19 vaccine by postvaccination risk interval by age group in ECDS using the SCCS analysis—whole study period to 6 February 22. Table D. Adjusted (for time period (4 weekly period)) RI of admissions with myocarditis or pericarditis in SUS using the SCCS analysis in risk periods after a COVID-19 vaccine or a SARS-CoV-2 infection with booster doses stratified by vaccine given for priming. Table E. Adjusted (for time period (4 weekly period)) relative risk (aRR) of attendances with myocarditis or pericarditis in SUS using a cohort analysis after a COVID-19 vaccine by postvaccination risk interval. Adjusted for time period, age group, gender, region, ethnic group, CEV, and other clinical risk group. Table F. Adjusted (for time period (4 weekly period)) RI of admissions with myocarditis or pericarditis after a COVID-19 vaccine by postvaccination risk interval in SUS using the SCCS analysis with data up to 23 August 2021. Table G. Adjusted (for time period (4 weekly period)) RI of hospital admission in SUS with myocarditis or pericarditis after a COVID-19 vaccine by postvaccination risk interval in 16–39 year olds with or without a prior SARS-CoV-2 infection using the SCCS analysis—whole study period to 6 February 22. Table H. Relative incidence (adjusted for time period (4 weekly period)) using the SCCS analysis and aRR of attendances in 12–15 year olds with myocarditis or pericarditis in ECDS after a BNT162b2 COVID-19 vaccine by postvaccination risk interval.

(DOCX)

Abbreviations

CEV

clinically extremely vulnerable

CI

confidence interval

COVID-19

Coronavirus Disease 2019

dsRNA

double-stranded RNA

ECDS

Emergency Care Data Set

NHS

National Health Service

NIMS

National Immunisation Management System

RI

relative incidence

SAE

serious adverse event

SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus 2

SCCS

self-controlled case series

SGSS

Second Generation Surveillance System

SUS

Secondary Uses Service

Data Availability

The raw study data are protected and are not freely available due to data privacy laws. This work is carried out under Regulation 3 of The Health Service (Control of Patient Information) (Secretary of State for Health, 2002))(3) using patient identification information without individual patient consent. Data cannot be made publicly available for ethical and legal reasons, i.e. public availability would compromise patient confidentiality as data tables list single counts of individuals rather than aggregated data. Requests for the underlying data should be made via the UKHSA office for data release: https://www.gov.uk/government/publications/accessing-ukhsa-protected-data.

Funding Statement

This work was supported by the UK Health Security Agency for authors NA, JS HJW via their employment. EM receives support from the National Institute for Health Research Health Protection Research Unit in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with UKHSA (Grant Reference NIHR200929). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Philippa Dodd

21 Sep 2022

Dear Dr Miller,

Thank you for submitting your manuscript entitled "Risk of myocarditis after a COVID-19 mRNA vaccine booster following homologous or heterologous priming in those with and without prior SARS-CoV-2 infection; an observational database study in England" for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by Sep 23 2022 11:59PM.

Login to Editorial Manager here: https://www.editorialmanager.com/pmedicine

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Feel free to email us at plosmedicine@plos.org if you have any queries relating to your submission.

Kind regards,

Philippa Dodd, MBBS MRCP PhD

PLOS Medicine

Decision Letter 1

Philippa Dodd

2 Feb 2023

Dear Dr. Miller,

Thank you very much for submitting your manuscript "Risk of myocarditis after a COVID-19 mRNA vaccine booster following homologous or heterologous priming in those with and without prior SARS-CoV-2 infection; an observational database study in England" (PMEDICINE-D-22-03092R1) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Feb 23 2023 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

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Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Philippa Dodd, MBBS MRCP PhD

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

GENERAL

Please respond to all editor and reviewer comments detailed below, in full.

DATA AVAILABILITY STATEMENT

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and FAQs at

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PLOS defines the “minimal data set” to consist of the data set used to reach the conclusions drawn in the manuscript with related metadata and methods, and any additional data required to replicate the reported study findings in their entirety. Authors do not need to submit their entire data set, or the raw data collected during an investigation. Please submit the following data:

The values behind the means, standard deviations and other measures reported;

The values used to build graphs;

The points extracted from images for analysis.

The Data Availability Statement (DAS) requires revision. For each data source used in your study:

a) If the data are freely or publicly available, note this and state the location of the data: within the paper, in Supporting Information files, or in a public repository (include the DOI or accession number).

b) If the data are owned by a third party but freely available upon request, please note this and state the owner of the data set and contact information for data requests (web or email address). Note that a study author cannot be the contact person for the data.

c) If the data are not freely available, please describe briefly the ethical, legal, or contractual restriction that prevents you from sharing it. Please also include an appropriate contact (web or email address) for inquiries (again, this cannot be a study author).

TITLE

Suggest “Risk of myocarditis after a COVID-19 mRNA vaccine booster following homologous or heterologous priming in those with and without prior SARS-CoV-2 infection: a self-controlled case series analysis in England” or something similar. You may wish to make further revisions in accordance with reviewer comments – please see below.

ABSTRACT

Abstract Background:

It may be helpful to expand this section further outlining why the study is important. Please ensure that the final sentence clearly states the study question.

Abstract methods and findings:

Line 33-34: is the word “days” missing after 1-27?

Please include the timeframe over which the data were collected and the main outcome measures.

Please include the number of participants (of the 50 million eligible to receive the vaccine) that were diagnosed with myocarditis and/or pericarditis (7929 individuals as per the results section of the main manuscript)

Please detail where data were extracted from (i.e. which databases)

Please quantify the main results with p values as well as 95% CIs. When reporting p values please report as p<0.001 (not .001) or where higher, the exact p value as p=0.002 (not .002), for example. Suggest modifying statistical reporting to read as follows: 3.23 (95% CI [1.85,5.64]; p= 0.0… or p<0.001…) and 6.06 (95% CI [2.95,12.47], p=0.00 or p<0.001)

Please include any important dependent variables that are adjusted for in the analyses.

Apart from the possibility of overestimation of the RIs, were there any other limitations of the study's methodology?

Abstract Conclusions:

Line 41: Please address the study implications without overreaching what can be concluded from the data; the phrase "In this study, we observed ..." may be useful. This sentence is rather long and as result not very accessible to the reader, please revise.

Line 43: suggest “…which contains less mRNA...” perhaps

Line 46: Suggest “…behind this phenomenon…” perhaps

Please interpret the study based on the results presented in the abstract, emphasizing what is new without overstating your conclusions.

AUTHOR SUMMARY

Thank you for including an author summary. Please ensure that each bullet point is succinct, and that the language used is accessible to the general reader. It may be helpful for you to visit the journal's homepage here: https://journals.plos.org/plosmedicine/ for published examples.

Why was this study done?

Line 49 Please add the heading “Author Summary” before the sub-headings

Please ensure under each sub-heading, individual statements follow bullet-points.

What did the researchers do and find?

This section is rather long. Please trim to no more than 4 individual bullet points

Line 80: please revise the sub-heading to read “What do these findings mean?”

INTRODUCTION

Lines 101 and 102: please only include non-proprietary names for vaccines

Line 119: Sentence beginning “Given…” suggest moving to an appropriate part of the methods section

METHODS and RESULTS

Lines 192: see statistical reviewer comments also, which we agree with, please provide brief details of your statistical methods here. For all observational studies, we ask that in the manuscript text you indicate:

(1) the specific hypotheses you intended to test,

(2) the analytical methods by which you planned to test them,

(3) the analyses you actually performed, and

(4) when reported analyses differ from those that were planned, transparent explanations for differences that affect the reliability of the study's results. If a reported analysis was performed based on an interesting but unanticipated pattern in the data, please be clear that the analysis was data-driven.

Lines 124: please include the number of residents (50 million as per the abstract)

Line 125: please define “outcomes of interest”

Line 159 onwards: please define PCR, LFT, UKHSA at first use

Line 166: please define NHS at first use

Please remove governance, funding, data availability and conflicts of interest statements and include only in the relevant sections of the manuscript submission form. In the event of publication they will be complied as metadata

As for the abstract, please quantify the main results with p values as well as 95% CIs. When reporting p values please report as p<0.001 (not .001) or where higher, the exact p value as p=0.002 (not .002), for example. Suggest modifying statistical reporting to read as follows: 3.23 (95% CI [1.85,5.64]; p= 0.0… or p<0.001…) and 6.06 (95% CI [2.95,12.47], p=0.00 or p<0.001). Please detail the statistical test (s) used to drive p values.

FIGURES

Please define all abbreviations including those used in the titles/captions in an appropriate footnote

Figure 1: in the caption please define “wk”

Figure 2: in an appropriate footnote, please indicate the meaning of the dots and lines

Figure 3: please include the year in the legend depicting the August date

TABLES

Please also see statistical reviewer comments which we agree with

As above, please define all abbreviations including those used in statistical reporting such as CI, for example

To help facilitate transparent data reporting where adjusted analyses are presented, please also include unadjusted analyses for comparison. In a caption/footnote please state which variables are adjusted for.

Throughout where relevant please include a column for reporting p values instead of asterisks.

Please report p values as p <0.001 and where higher the exact p value. In an appropriate footnote, please detail the tests used to determine p values

Table 1: please see statistical reviewer comments (to include 95% CIs) which we agree with

Table 3: please use commas to separate upper and lower confidence limits instead of hyphens as these can be confused with the presentation of negative values, and to ensure consistency in statistical reporting. Please check and amend where necessary including supplementary files

SUPPLEMENTARY FILES

Throughout where relevant please include a column in the tables for reporting p values (instead of asterisks). Please indicate in a footnote the statistical test(s) used to determine them

Please ensure all abbreviations used for statistical reporting are appropriately defined including CI

Figure S3A – suggest full terms instead of myo- or peri-

REFERENCES

For in-text reference callouts please ensure citations are separated by commas without spaces. For example, line 364, “…proposed [21, 22, 23].” Should read “…proposed [21,22,23].”

Comments from the reviewers:

Reviewer #2: Thank you for the opportunity to review this manuscript. It was easy to read and the analysis appears to be appropriate. The question of myocarditis risk after booster doses is important. Reassuring to see that while there still is an effect, it appears to be attenuated. The addition of infection including breakthrough infections and re-infections adds valuable perspective to our current situation.

1) The main issue is the overlap with the Patone paper1, which is also an SCCS analysis of booster vaccination/infection in the same data. The Patone paper has follow-up among 13+ years of age from December 1, 2020, to December 15, 2021 compared to the this study which has follow-up among 12+ years of age from February 22, 2021 to February 6, 2022. But otherwise, it appears to be very similar with respect to data and analysis. It needs to be clarified in the manuscript what the key differences are and how this adds significantly to the Patone analysis.

2) Another main issue is the combination of myocarditis and pericarditis into one outcome. Myocarditis and pericarditis background rates differ by age and sex, which means that it is difficult to advice public health policy from numbers based on a combined outcome. I suggest that they are analysed separately throughout - myocarditis results could be presented in text and pericarditis in supplementary.

3) Abstract could be shortened (and made more readable) by reducing the number of results presented here - identify and focus on the key findings.

4) The introduction/discussion is outdated. Should be updated to include the newest studies on booster vaccination and myocarditis risk. (1-3)

5) I would not include emergency care outcomes at all. I expect them to have poor validity. I would restrict the main analysis to hospital in-patients. Maybe place the emergency care outcomes in supplementary only?

6) Lines 189-190: Please elaborate on why follow-up was not censored at event.

7) The figures are difficult to review due to poor quality.

8) The attributable risk results should ideally also be presented with 95% CIs to reflect the statistical precision of the estimates.

9) Can you comment on the impact of the testing policy / capture of infections in England? E.g. attributable risks will be dependent on background rates of infections. How many infections do you estimate that you have captured by tests in England?

1. Patone M, Mei XW, Handunnetthi L, et al. Risk of Myocarditis After Sequential Doses of COVID-19 Vaccine and SARS-CoV-2 Infection by Age and Sex. Circulation. 2022;146:743-754. doi:10.1161/circulationaha.122.059970

2. Naveed Z, Li J, Spencer M, et al. Observed versus expected rates of myocarditis after SARS-CoV-2 vaccination: a population-based cohort study. CMAJ. 2022;194(45):E1529-E1536. doi:10.1503/CMAJ.220676

3. Stéphane Le Vu A, Bertrand M, Jabagi MJ, et al. Risk of Myocarditis after Covid-19 mRNA Vaccination: Impact of Booster Dose and Dosing Interval. medRxiv. Published online August 1, 2022:2022.07.31.22278064. doi:10.1101/2022.07.31.22278064

Reviewer #3:

This is a very well written paper on an important topic. Also, the statistical analyses used are adequate. However, there are some concerns. My main concern is the combination of myocarditis and pericarditis combined. Apart from, maybe, diluting, the effect of vaccination on risk of vaccination in young males it also raised the question whether the data sources actually capture all cases?

The Title is misleading as the presented comparison is actually on myocarditis and pericarditis combined.

Page 9, 197 exposure and short-term event independency. You did assess this by inclusion of a pre-exposure period. Would be nice to just see a plot of number of days since myocarditis patients were vaccinated? I would guess very few cases would actually be vaccinated within 1-3 weeks after an event?

Page 10, 209. A bit strange and uncommon in epidemiology to define "strong" evidence based on the p-value. :-)

Results

Page 12, 253/ Table 1. Myocarditis and pericarditis are different diseases and their incidence vary by age. Myocarditis is more common in younger ages and pericarditis in older. Most studies on myo/peri risk after vaccination have done separate analyses on these two conditions. Why was that not done here? Presentation of incidence rates by age as in table1 for these conditions combined is not informative. Suggest to present incidence by age and sex for myo and peri separately (and peri can be in supplement). And subsequently all analyses separately for myo/peri ( I.e., suggest S3C and D as main tables).

Also, is there any information on the validity of these diagnoses in the registers used? This in regards to the (much) lower incidence found in your data compared to others.

Also, the risk has been shown to be highest in 16-24 (rather than in 25-39). Would suggest to also present this age group, (16-24, 25-39).

Death. Is it only possible to assess death within the first week (0-6 days) and not for eg after 28 days? Also, presentation of deaths (as all results!) should be separately for myo and peri. Do you not find any death in young (below 40) after "vaccine-induced" myocarditis in your data?

Page 17, 387 paragraph comparing with other studies. Would suggest to compare effect estimates for the most important groups ( i.e., myocarditis in young men). As stated now you appear to find one fourth of the overall incidence of myo and peri as found in the Nordic study. To better understand the validity of your data I would suggest presenting numbers for young men and myocarditis only (not combined with pericarditis).

Conclusion.

Page19, 449. Would avoid mentioning the comparison of outcome after vaccination with outcome after a positive covid test as the latter, as you also mention, is (highly) dependent on testing strategy (eg. When admitted to hospital). The fewer less severe tested the "higher" the risk of outcome after covid. The benefit-risk analyses is not based on comparing risk of myo after vaccination with that after covid. Hence, would avoid supporting such comparisons.

Tables. Would suggest removing the "two-star" "three-star" significance throughout :-)

Table 5. I guess, column heading should be " attributable… per million vaccinations" for the data regarding the vaccinees.

Another recent reference that might be of interest:

Booster Vaccination with SARS-CoV-2 mRNA Vaccines and Myocarditis Risk in Adolescents and Young Adults: A Nordic Cohort Study of 8.9 Million Residents | medRxiv

Any attachments provided with reviews can be seen via the following link:

[LINK]

Attachment

Submitted filename: Review_22-03092R1.docx

Decision Letter 2

Philippa Dodd

5 Apr 2023

Dear Dr. Miller,

Thank you very much for re-submitting your manuscript "Risk of myocarditis after a COVID-19 mRNA vaccine booster and after COVID-19 in those with and without prior SARS-CoV-2 infection; a self-controlled case series analysis in England" (PMEDICINE-D-22-03092R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by 3 reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

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We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

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We look forward to receiving the revised manuscript by Apr 12 2023 11:59PM.   

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PLOS Medicine

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Requests from Editors:

GENERAL

Thank you for your very detailed and considered responses to previous editor and reviewer comments, please see below for further comments which we require you address prior to publication.

Please ensure that the study is reported according to the STROBE guideline, and include the completed STROBE checklist as Supporting Information. Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

The STROBE guideline can be found here: http://www.equator-network.org/reporting-guidelines/strobe/

When completing the checklist, please use section and paragraph numbers, rather than page or line numbers as these often change at publication.

*** Please see statistical reviewer comments regarding the primary objectives and analyses which we agree with and require that you address in full ***

DATA AVAILABILITY STATEMENT

Thank you for updating your statement as follows:

“The raw study data are protected and are not freely available due to data privacy laws. This work is carried out under Regulation 3 of The Health Service (Control of Patient Information) (Secretary of State for Health, 2002))(3) using patient identification information without individual patient consent. Data cannot be made publicly available for ethical and legal reasons, i.e. public availability would compromise patient confidentiality as data tables list single counts of individuals rather than aggregated data. Requests for the underlying data should be made via the UKHSA office for data release: https://www.gov.uk/government/publications/accessingukhsa-protected-data”

Please include this updated statement in the manuscript submission form when you re-submit your manuscript.

TITLE

Thank you for revising your title. We suggest that the title should read as follows:

“Risk of myocarditis and pericarditis after a COVID-19 mRNA vaccine booster and after COVID-19 in those with and without prior SARS-CoV-2 infection: A self-controlled case series analysis in England”

we understand that (most) data pertaining to pericarditis has been transferred to the appendix, but pericarditis is mentioned throughout the abstract, author summary and included in the main analyses. See comments below re: abstract.

ABSTRACT

Pericarditis is not mentioned in the background section (or the title) but is throughout the rest of the abstract. Suggest introducing it in the “Background” section and (as above) including “pericarditis” in the title

Line 45: “…[22.18,62.38];p=<0.001…” should it be = or < please amend as necessary

Pericarditis is also not mentioned in the conclusions. Should it be?

Line 53: “…half the amount of mRNA…” is it exactly half? If not then perhaps “…substantially less…” or similar instead

AUTHOR SUMMARY

Thank you for making revisions to the author summary.

In your discussion you state the following “While there was little evidence of an elevated risk of hospital admission for pericarditis after primary or booster vaccination, emergency care consultations showed elevated risks for pericarditis in 16-39 year olds 0-6 days after a first dose of ChAdOx1-S and after primary and booster doses of the mRNA vaccines” However, your summary implicates mRNA vaccines only which could be misleading, please revise.

Finally, line 92 (2nd bullet point what do these findings mean) – can this statement be made based on these data/this study design? We suggest that you consider removing this statement as it might be a bit of an over statement. Please see below for further suggested revisions.

Why the study was done?

* Primary and booster immunisation with mRNA COVID-19 vaccine have been associated with an increased risk of acute myocarditis.

* SARS-CoV-2 infection may itself cause myocarditis or pericarditis.

* However, the effect of prior vaccination on this risk, and on the risk after a reinfection, has not been investigated.

What did the researchers do and find?

* We conducted a nationwide study in England to assess the risk of hospital admission for myocarditis or pericarditis after primary or booster vaccination, and the risk after a confirmed SARS-CoV-2 infection in those with and without confirmed previous infection.

* Elevated risks of myocarditis were found up to 6 days after each priming dose of the available mRNA vaccines (BNT162b2 and mRNA-1723) and after mRNA booster doses following a mRNA priming course but not after a priming course of the adenovirus-vectored vaccine ChAdOx1-S.

* For both mRNA vaccines, elevated risks were found in those under 40 years old, predominantly in males, were highest after the second priming dose and were generally lower in those vaccinated after a prior SARS-CoV-2 infection.

*There was an elevated risk of myocarditis and pericarditis in the 27 days after a SARS-CoV-2 infection which was higher in ≥ 40 year olds than 16-39 year olds and was still present in those with a re-infection or who had been vaccinated before infection

What do these findings mean?

* This study provides information for policy makers and those recommended to receive booster mRNA vaccines on the associated risk of myocarditis or pericarditis in a population with a high prevalence of prior SARS-CoV-2 infection.

* The greater risk associated with mRNA-1273 vaccines, which have a higher mRNA dose than BNT162b2 vaccines and, the substantially lower risk after the mRNA-booster which has half the mRNA content than used for priming, may be suggestive of a mRNA dose related mechanism but further work is required to determine this.

METHODS

Line 142: “…for the myocarditis…” please revise for improved grammar

Line 194: please revise to “Construction of the Self-Controlled Case-Series dataset (SCCS)”

TABLES

Table 1: numerical values are not well aligned to the column headers, please revise to improve clarity

Table 2:

Title “: Adjusted*…” what does this single asterisk denote?

Thank you for including p values. You responded, “we retained asterisks to aid the reader identify outcomes that meet our pre-specified p values and which we draw attention to in the text”

Please remove the asterisks used to denote p-values. These are redundant in view of the column of p values and there is no mention of pre-specified values in the table caption so it doesn’t really help the reader. All information pertaining to the contents of the tables (and figures) should be detailed in a caption without the need to refer to the text.

To improve accessibility to the reader, please ensure upper and lower bounds of 95% CIs are on a single line not split across two lines

Table 3: throughout, please use lowercase p. please add “p=” to “reinfection day 0”

Table 4:

“elevated RIs (p<0.001)…” what does this p value refer to in the table?

Please define numerical values contained within parentheses (end column – attributable risk per million vaccinations)

Table S3A: as above, please remove asterisks and please ensure upper and lower bounds of 95% CIs are on a single line

SOCIAL MEDIA

To help us extend the reach of your research, please provide any Twitter handle(s) that would be appropriate to tag, including your own, your coauthors’, your institution, funder, or lab. Please detail any handles you wish to be included when we tweet this paper, in the manuscript submission form when you re-submit the manuscript.

Comments from Reviewers:

Reviewer #2: Thank you for taking my comments carefully into account. Good luck with the paper!

Reviewer #3: Table 1: please see statistical reviewer comments (to include 95% CIs) which we agree with Author response: We have added CIs to all tables apart from table 1. Since the data in table 1 is from the whole population of England and are not estimates from a sample of the population it is not appropriate to show CIs. We have pointed this out to other journals in which data from the entire population in England has been shown and for which a request for RIs was made and it has been accepted (see for example table 1 Characteristics of Persons Tested for SARS-CoV-2 in England, According to Test Positivity or Negativity and Variant in Covid-19 Vaccine Effectiveness against the Omicron (B.1.1.529) Variant | NEJM

[Minor comment: I agree with the authors. But, sometimes CI can be motivated by seeing national data as a sample in time ( i.e. it is not a sample of the population, but the population differs by years, hence it could sometimes be useful with CI)]

Page 9, 197 exposure and short-term event independency. You did assess this by inclusion of a pre-exposure period. Would be nice to just see a plot of number of days since myocarditis patients were vaccinated? I would guess very few cases would actually be vaccinated within 1-3 weeks after an event?

Thank you for this comment - the plot is shown below. However plots of the interval between vaccination and events can be misleading because they take no account of person-time, hence we will not include this in the paper or supplementary material. Relative incidences with varying pre exposure windows are plotted in Appendix S2, with explanation and findings; RIs change very little with pre-exposure intervals longer than 21 days which was the justification we cited for using the 21 day pre-exposure window.

Comment: It is clear from the plot that individuals are not at all that likely to be vaccinated within 14 days of a myocarditis event. (Do not understand the comment on person-time. The study, as I understand, does not really take individual person-time into account e.g. persons are not censured after an event of at time of a vaccine-schedule that is not studied?)

Page 10, 209. A bit strange and uncommon in epidemiology to define "strong" evidence based on the p-value. :-)

Yes this was badly worded. We have now changed this to "strong statistical evidence of an association" which was the intention behind the wording as indicated in section 4f of the protocol.

Minor Comment: my comment was more on that "strong evidence" should more be based on the magnitude of the association, dose-response etc than on a p-value. But, it is apparent the Journal wants p-values.

Also, is there any information on the validity of these diagnoses in the registers used? This in regards to the (much) lower incidence found in your data compared to others.

Author response: The diagnoses coded as myocarditis in the SUS data set that we used were not validated against case note review (which we acknowledge in the limitations paragraph) nor were they in the Nordic study by Karlstad et al. However despite the differences in background rates in admissions for myocarditis and pericarditis between the Nordic study and our own, the findings in terms of elevated risk by vaccine product and dose in the primary series between our studies are similar. In relation to differences in background rates between the English and Nordic studies the latter used outpatient contacts for myocarditis as well as inpatient admissions. We were unable to find a breakdown in the Nordic study of the incidence rates by outpatient consultation and hospital admission so could not compare directly with the inpatient rates in our study. In Israel the Mevorach et al study only used hospital admitted cases but stated that any patient with a diagnosis of myocarditis would be admitted. Also the Israeli study used active surveillance methods in which clinicians were alerted to the potential association with vaccination and were requested to report such cases. The paragraph dealing with differences in incidence rates between studies is now expanded to provide this additional information. We do not consider that differences in background rates in different settings raises questions about the validity of the diagnoses in our study.

Comment:

Danish ICD codes of myocarditis, as part of the Nordic study, have been validated (Ref Sundbøll J, Adelborg K, Munch T, et al. Positive predictive value of cardiovascular diagnoses in the Danish National Patient Registry: a validation study. BMJ Open. 2016;6(11):e012832. doi:10.1136/bmjopen-2016-012832). Also, the Nordic study did not include outpatient cases: "We defined incident outcome events as the date of first hospital admission for myocarditis or pericarditis from December 27, 2020, onward. The primary outcome was a main or secondary diagnosis of myocarditis at discharge from inpatient hospital care. SARS-CoV-2 Vaccination and Myocarditis in a Nordic Cohort Study of 23 Million Residents | Cardiology | JAMA Cardiology | JAMA Network "

If the authors see no problem in large differences in background rates do they have an explanation why rates of myocarditis are much lower compared to e.g., the Nordic countries?

I agree that it is of less importance when discussion relative measures. But, measures of absolute risk, incidence rate, excess risk are dependent on background risks. The authors do acknowledge this is the discussion. But, their explanation why they find lower rates in not really reassuring.

Methods page 7 line 141:

"The study population comprised the resident population of 50 million individuals in England aged 12 years and older on the 31st August 2021. Dates of admission for the myocarditis or

pericarditis were from 22nd February 2021 to 6th February 2022." Is 31 Aug 2021 the correct date? Cannot see how you can have the study pop on a later date than first outcome (22 Feb 2021)?

Page 7, line 146:

"Given the generally mild nature of vaccine-associated myocarditis [14] we analysed cases presenting in emergency care settings as well as those admitted to hospital."

Well, if the authors want to state anything on the severity of vaccine-associated myo compared to myo of other causes I would suggest reading of some more detailed references:

Witberg G, Barda N, Hoss S, Richter I, Wiessman M, Aviv Y, et al. Myocarditis after Covid-19 vaccination in a large health care organization. N Engl J Med 2021;385: 2132-2139. 2.

Mevorach D, Anis E, Cedar N, Bromberg M, Haas EJ, Nadir E, et al. Myocarditis after BNT162b2 mRNA vaccine against Covid-19 in Israel. N Engl J Med 2021;385: 2140-2149

Clinical outcomes of myocarditis after SARS-CoV-2 mRNA vaccination in four Nordic countries: population based cohort study | BMJ Medicine https://bmjmedicine.bmj.com/content/2/1/e000373

Page 19, line 444

"This may be attributable in part to study design as outpatient and inpatient myocarditis cases were included in the Nordic study"

This is not true. The Nordic study states: "We defined incident outcome events as the date of first hospital admission for myocarditis or pericarditis from December 27, 2020, onward. The primary outcome was a main or secondary diagnosis of myocarditis at discharge from inpatient hospital care. SARS-CoV-2 Vaccination and Myocarditis in a Nordic Cohort Study of 23 Million Residents | Cardiology | JAMA Cardiology | JAMA Network "

Page 23, line 518. Last sentence in conclusion. "The rarity and benign outcome of vaccine attributable cases is reassuring."

Well, here the authors discuss their detected incidence rates, which are (much) lower than other studies, and also discuss the severity of the outcome of which they have no supporting data except case fatality within one week. Is this sentence really needed?

Happy to see the stratification by age and sex (e.g., males 16-24) now being presented. In general, all studies on myo/peri should be stratified by sex and age as the incidence varies substantially.

Any attachments provided with reviews can be seen via the following link:

[LINK]

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Submitted filename: Re-review_22-03092R1.docx

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Submitted filename: rev plos med.docx

Decision Letter 3

Philippa Dodd

22 May 2023

Dear Dr Miller, 

On behalf of my colleagues and the Academic Editor, Professor Rickard Ljung, I am pleased to inform you that we have agreed to publish your manuscript "Risk of myocarditis and pericarditis after a COVID-19 mRNA vaccine booster and after COVID-19 in those with and without prior SARS-CoV-2 infection; a self-controlled case series analysis in England" (PMEDICINE-D-22-03092R3) in PLOS Medicine.

Prior to publication, please remove the redundant opening parenthesis in S3 Table '(1.24, (6.85)' from the penultimate column, row 5.

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To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper. 

Best wishes, 

Pippa

Philippa Dodd, MBBS MRCP PhD 

PLOS Medicine

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 STROBE Checklist. STROBE Checklist.

    (XLSX)

    S1 Protocol. Analysis of hospital admissions and emergency care consultations for acute myocarditis and pericarditis after COVID-19 vaccines in England.

    (PDF)

    S1 Appendix. Supplementary material.

    Checking the self-controlled case series assumption of no long-term event-dependence. Figure A. Plots of preexposure and postexposure relative incidence, by preexposure period length, SUS data to 6 February 2022. Figure B. Plots of preexposure and postexposure relative incidence, by preexposure period length, ECDS data to 6 February 2022. Table A. Relative incidence estimates from the standard SCCS model and the event-dependent exposures SCCS model, SUS first cases in individuals with no recorded positive SARS-CoV-2 test before the end of the observation period (6 February 2022), N = 1,977. Table B. Relative incidence estimates from the standard SCCS model and the event-dependent exposures SCCS model, ECDS first cases in individuals with no recorded positive SARS-CoV-2 test before the end of the observation period (6 February 2022), N = 3,553.

    (DOCX)

    S2 Appendix. Supplementary tables.

    Table A. Adjusted (adjusted for time period (4 weekly period)) RI of admissions with myocarditis after a COVID-19 vaccine by postvaccination risk interval in 16–24 and 25–39 year olds and 16–39 year olds by gender in SUS using the SCCS analysis—whole study period to 6 February 2022. Table B. Adjusted (for time period (4 weekly period)) RI of admissions with pericarditis after a COVID-19 vaccine by postvaccination risk interval by age group in SUS using the SCCS analysis—whole study period to 6 February 2022. Table C. Adjusted (for time period (4 weekly period)) RI of attendances with myocarditis or pericarditis after a COVID-19 vaccine by postvaccination risk interval by age group in ECDS using the SCCS analysis—whole study period to 6 February 22. Table D. Adjusted (for time period (4 weekly period)) RI of admissions with myocarditis or pericarditis in SUS using the SCCS analysis in risk periods after a COVID-19 vaccine or a SARS-CoV-2 infection with booster doses stratified by vaccine given for priming. Table E. Adjusted (for time period (4 weekly period)) relative risk (aRR) of attendances with myocarditis or pericarditis in SUS using a cohort analysis after a COVID-19 vaccine by postvaccination risk interval. Adjusted for time period, age group, gender, region, ethnic group, CEV, and other clinical risk group. Table F. Adjusted (for time period (4 weekly period)) RI of admissions with myocarditis or pericarditis after a COVID-19 vaccine by postvaccination risk interval in SUS using the SCCS analysis with data up to 23 August 2021. Table G. Adjusted (for time period (4 weekly period)) RI of hospital admission in SUS with myocarditis or pericarditis after a COVID-19 vaccine by postvaccination risk interval in 16–39 year olds with or without a prior SARS-CoV-2 infection using the SCCS analysis—whole study period to 6 February 22. Table H. Relative incidence (adjusted for time period (4 weekly period)) using the SCCS analysis and aRR of attendances in 12–15 year olds with myocarditis or pericarditis in ECDS after a BNT162b2 COVID-19 vaccine by postvaccination risk interval.

    (DOCX)

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    Submitted filename: response to second set of reviews.docx

    Data Availability Statement

    The raw study data are protected and are not freely available due to data privacy laws. This work is carried out under Regulation 3 of The Health Service (Control of Patient Information) (Secretary of State for Health, 2002))(3) using patient identification information without individual patient consent. Data cannot be made publicly available for ethical and legal reasons, i.e. public availability would compromise patient confidentiality as data tables list single counts of individuals rather than aggregated data. Requests for the underlying data should be made via the UKHSA office for data release: https://www.gov.uk/government/publications/accessing-ukhsa-protected-data.


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