docs/Benefit-Risk Assessment Review Memo - COMIRNATY.txt

FDA U.S. FOOD & DRUG
ADMINISTRATION
Department of Health and Human Services
Food and Drug Administration
Center for Biologics Evaluation and Research
MEMORANDUM
Date:
To:
From:
September 13, 2021
Ramachandra Naik
Hong Yang, Ph.D., Patrick Funk, Ph.D., and Osman N. Yogurtcu, Ph.D.
Analytics and Benefit-Risk Assessment Team
ОВЕ
Through:
Re:
Richard Forshee, Ph.D.
Acting Deputy Office Director
ОВЕ
ST 125742/0: review memo for benefit-risk assessment

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Review Memo on Benefit-Risk Assessment of Pfizer Vaccines for Age 16-17 yrs
Reference submission: BLA 125742/0
Reviewers: Hong Yang, Patrick Funk, and Osman Yogurtcu Date: August 20, 2021
Contents
1. Executive Summary
2. Background and regulatory questions.
3. Methods.
3.1. Model Overview
3.2. Benefits...
3.3. Risks...
4. Results..
4.1. Scenario 1: Base case.
4.2. Scenario 2: Most likely scenario.
4.3. Scenario 3: Worst case scenario.
5. Conclusions and discussion..
6. Limitations ..

7. Acknowledgements
References.
List of Tables.
List of Figures.
Supplementary Materials.
5
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1. Executive Summary
FDA conducted a benefit-risk assessment to inform the review of the Biologics License Application (BLA) for use of the Pfizer-BioNTech COVID-19 mRNA vaccine (also referred to as BNT162b2) among ages 16 vears and older. We assessed the benefits and risks per million individuals who are vaccinated with two complete doses of BNT162b2. The analysis was conducted for the groups stratified by combinations of sex and age (12-15, 16-17, 18-24, and 25-29 years). The model assesses the benefits of vaccine-preventable COVID-19 cases, hospitalizations, intensive care unit (ICUs) visits, and deaths, and the risks of vaccine-related excess myocarditis/pericarditis cases, hospitalizations, and deaths. The major sources of data include age/sex specific COVID-19 case and hospitalization incidences reported on COVID NET on July 10, 2021, the myocarditis/pericarditis case rate attributable to vaccine obtained from the OPTUM health claims database, and the vaccine related myocarditis/pericarditis deaths reported through VAERS.
We constructed scenarios for both the most likely short-term moving direction of the pandemic and the worst case, which used the most conservative assumptions for all model inputs.
The most likely scenario:
We assumed vaccine protection duration of 6-months, 10 COVID-19 case incidence and 4x COVID-19 hospitalization incidence as of July 10, 70% vaccine efficacy against COVID-19 cases, 80% vaccine efficacy against hospitalization, and no vaccine-related myocarditis death. The model results indicate that, for all age/sex groups and across all model outcomes, the benefits clearly outweigh the risks. For males 16-17 years old-the group with the highest risk of myocarditis/pericarditis-the model predicts that prevented COVID cases, hospitalizations, ICUs, and deaths are 135,771, 506, 166, and 4, respectively. The excess myocarditis/pericarditis cases, associated hospitalizations, and deaths attributable to vaccine are 196, 196, and 0, respectively.
The worst-case scenario:
We used the most conservative assumptions for all the model inputs in this scenario. We assumed 6-months vaccine protection, the COVID-19 case and hospitalization incidence as of July 10, 2021, 70% vaccine efficacy against COVID-19 case, 80% vaccine efficacy against COVID-19 hospitalization, and 0.002% myocarditis/pericarditis death rate.
For males 16-17 years old, the model predicts that prevented COVID cases, hospitalizations, ICUs, and deaths are 13,577, 127, 41, and 1, respectively. The excess myocarditis/pericarditis cases and associated hospitalizations and deaths attributable to the vaccine are 196, 196, and 0, respectively. Even with the conservative assumption on the myocarditis/pericarditis death rate, the model predicted 0 deaths associated with myocarditis/pericarditis. The model predicted a higher number of myocarditis/pericarditis related hospitalizations compared to prevented COVID-19 hospitalizations.
However, considering the differential clinical outcomes of the hospitalization from two difference causes, we consider the benefits of the vaccine still outweigh the risks for the highest risk group, males 16-17 years old, under this worst-case scenario.
Our results demonstrate that the benefits of BNT162b2 clearly outweigh its risks for all age and sex

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groups we analyzed. However, the benefit-risk estimates are highly uncertain due to the dynamics of pandemics. Other major uncertainties in benefits are vaccine efficacy and duration of protection in the face of emerging virus variants. The major risk uncertainty is the data on vaccine-related myocarditis cases and deaths.
2. Background and regulatory questions
The Pfizer-BioNTech COVID-19 mRNA vaccine (also referred to as BNT162b2) has been recommended for persons 12 years of age and older in the United States under FDA's Emergency Use Authorization (EUA).
Since authorization of mRNA COVID-19 vaccines (Pfizer-BioNTech and Moderna), real-world evidence has indicated the vaccines are effective in preventing COVID-19 cases and related hospitalizations and deaths. However, increased cases of myocarditis and pericarditis have been reported in the United States associated with mRNA COVID-19 vaccination, particularly in adolescents and young adults (Marshall et al. 2021; Shay et al. 2021; Watkins, et al., 2021). FDA conducted a benefit-risk assessment to inform regulatory decisions related to the Biologics License Application (BLA) for use of BNT162b2 vaccines among ages 16 years and older. The regulatory question to be answered is whether the benefits of vaccination outweigh the risks among various age and sex subgroups being considered for approved use of the vaccine (and in particular, males, age 16-17 years old), considering the potentially elevated myocarditis/pericarditis risk after vaccination suggested by post-authorization safety surveillance.
3. Methods
3.1. Model Overview
We assessed the benefits and risks per million individuals who are vaccinated with two complete doses of BNT162b2. The analysis was conducted for the groups stratified by combinations of sex and age (12-15, 16-17, 18-24, and 25-29 years). The model assesses the benefits of vaccine-preventable COVID-19 cases, hospitalizations, intensive care unit (ICUs) visits and deaths, and the risks of vaccine related excess myocarditis/pericarditis cases, hospitalizations, and deaths (Figure 1). The key model inputs include duration of vaccine protection, vaccine efficacy against COVID-19 cases and hospitalizations, age/sex specific COVID-19 case and hospitalization incidence rates, age/sex specific vaccine-attributable myocarditis case rate, and myocarditis death rate (Table 1). To evaluate the impact of uncertainty of these key model inputs on the benefits and risks, low and high values of these model inputs are used for sensitivity analysis.
Our model generates benefit-risk outcomes for seven scenarios (Table 2 and Supplement Table
S1) with different combinations of the input values. The three most important scenarios are presented in the main body of this report: Scenario 1, a base scenario using the COVID-19 incidence on July 10; Scenario 2, the most likely scenario; and Scenario 3, the worst-case scenario. Other scenarios are summarized in the supplementary materials of the report.

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3.2. Benefits
3.2.1. Calculation of benefits
Our benefit-risk model has four benefit endpoints (Figure 1): preventable COVID-19 cases hospitalizations, Intensive Care Unit admissions (ICUs), and deaths. To calculate the potential
COVID-19 cases preventable by vaccine (Cp), we use Equation 1
Cp =
ICID Ec
Pu
Eq. 1
where Ic is the COVID-19 case incidence rate, Pu is the proportion of the population that is at risk (i.e., unvaccinated), L is the duration of vaccine protection, D is the number of second vaccine doses administered (fixed at 1 million), and E is the vaccine efficacy against COVID-19 cases. For preventable COVID-19 hospitalizations (H), we use a similar equation (Equation 2) in which we consider the COVID-19 hospitalization incidence rate (I and vaccine efficacy against hospitalization (EH).
Hp =
브LDEn
Pu
Eq. 2
The preventable COVID-19 ICUs (Ip) and preventable COVID-19 deaths (D) are fractions of Hp,
such that Ip = fim Hp and Dp = faH Hp.
We perform these calculations over the individual age and sex groups and combined male and female groups.
3.2.2. Data and assumptions
3.2.2.1.
Duration of vaccine protection
We assume the vaccine has at the least 6 months of protection since this is the period examined by Pfizer in their ongoing study (Thomas et al., 2021). The model assesses the benefits for a period of 6 months post 2nd dose of vaccination. For the sensitivity analysis in the supplement, we use a protection period of 12 months as an upper bound. For simplicity, the model does not account for the benefits of partial vaccination (protection between the first and second dose) or the second order benefits of reducing the risk of transmission of COVID-19.
3.2.2.2.
Incidences of COVID-19 case, hospitalization, ICU, and death
We assume the incidence rates of COVID-19 case and hospitalization remain constant over the assessment period (next 6 or 12 months). The incidence rates of COVID-19 cases as of week July 10 are obtained from COVID NET for all sex/age groups. Four-week averages of incidence (6/26-7/10) are used due to the variability in rates given

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the small numbers of hospitalizations per age sex groups. The percent of hospitalizations going to ICU and the percent of hospitalized patients who die are estimated based on cumulative rates of hospitalizations, ICUs, and deaths for each sex/age groups reported on COVID NET since March 2020. All the incidence data for these factors are summarized in Table 3. Comparing the incidence from the 2nd week of August with those reported at the lowest point in the summer, we find a 10-time incidence and 4-time hospitalization increase over a 6-week period. Considering the great uncertainty in COVID-19 incidence during the pandemic, we conduct a sensitivity analysis using a 10-times multiplier for case incidence and 4-times multiplier for hospitalization incidence in the sensitivit analvsis. The multipliers were derived from the public data in COVID data tracker and COVID NET, respectively, to project the increase in COVID-19 infections/hospitalizations.
3.2.2.3.
Unvaccinated population
We estimate the unvaccinated population among each age/sex groups using US census data and "Age groups of people with at least one dose" from COVID data tracker. Data for Texas is not contained in COVID data tracker so we impute proportional vaccination counts based on population averages from the census data.
The incidence of COVID-19 cases and hospitalization, described in section 2.2.2.2
"Incidences of COVID-19 case, hospitalization, ICU and death," are converted into the incidence of COVID-19 cases and hospitalizations among unvaccinated individuals of each age sex group.
3.2.2.4.
Vaccine efficacy
We use vaccine efficacy rates of protection against COVID-19 cases of 70% and 90% and vaccine efficacy rates of protection against COVID-19 hospitalizations of 80% and 90% in different scenarios. The high efficacy of 90% represents the lower bound of the confidence interval from the clinical trial data (Oliver et al. 2020). The low efficacy of 70% for cases and 80% for hospitalization represents a conservative efficac rate given the uncertainty of the vaccine's protection against the Delta variant. Early studies on the vaccine's efficacy against cases from the Delta variant suggest 79% in Scotland (Sheikh et al., 2021), 87% in Canada (Nasreen et al., 2021), and 88% in India (Lopez Bernal et al., 2021). To remain conservative in the face of uncertainty in this rapidly changing pandemic, we use a lower bound of vaccine efficacy from these early reports.
3.3. Risks
3.3.1. Calculation of risks
Our benefit-risk model has three risk endpoints (Figure 1): excess myocarditis/pericarditis cases, hospitalizations, and deaths. Estimates of excess cases of mvocarditis/pericarditis are calculated by subtracting the background rate of myocarditis in Optum's sample population from 2019 from

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the rate of myocarditis in the study window from 12/10/2020 - 07/10/2021. We use Equation 3 to calculate excess cases of myocarditis/pericarditis (Mex) per one million fully vaccinated individuals.
MExc = (Mobs1 - MExp1 + Mobs2 - MExp2) * F
Eq. 3
Mobs1 and MExp1 are observed and expected myocarditis/pericarditis case rates post dose 1, Mobs and MExp2 are corresponding case rates post dose 2, and F is a multiplier for unit conversion.
Expected myocarditis/pericarditis case rates are the predicted background case rate unassociated with vaccine.
The number of mvocarditis hospitalization (M- and deaths (Mo) are fractions of excess
myocarditis/pericarditis cases (MExc), such that MH = MExc* Frmand MD = Mexc* fom.
3.3.2. Data and assumptions
3.3.2.1.
Myocarditis/pericarditis attributable to vaccine
We use myocarditis/pericarditis reports data provided by Acumen LLC that are derived from the Optum health claims database (Table 5). Acumen reports cases of myocarditis in 7-, 21-, and 42-day risk windows from each vaccine dose. Our analysis focuses on the 7-day risk window where most cases are found for all groups. The database contains rates of expected (MExp 1 and MExp2) and observed (Mobs1 and Mobs2) myocarditis/pericarditis in 100k person-vears for the 1st and 2nd dose of the vaccine.
Converting from 100k person-years in the risk window to one million vaccinated
individuals' daily risk, we multiply the rates by a factor F = (7*10)/365. This factor is
used to convert the rate per 100k person years to an expected case count for one million full vaccinations assuming a 7-day risk window. Confidence intervals for the myocarditis cases are calculated using the chi-square method for Poison distribution of rare events (Garwood, 1936).
3.3.2.2.
Myocarditis/pericarditis hospitalization and death rate
Almost all adolescent and young adult patients with suspected myocarditis/pericarditis cases are hospitalized and monitored for the condition. In this model, we assume all myocarditis/pericarditis cases are hospitalized, but Vaccine Adverse Events Reporting System (VAERS) data show median stay lengths of one day for observation.
A total of 1,061 myocarditis cases among US <30 ears old after vaccination with BNT162b2 are reported through VAERS. Among them, two deaths are reported. The search terms used for query and the narratives for two deaths who had vaccination with BNT162b2 are included in the supplement. Review of the available data b FDA

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and CDC indicates that both cases are unlikely to be related to the vaccine. In our model, we assume the death rate related to vaccine is most likely to be zero in the base case and most likely scenarios (Scenario 1 and 2). However, we use 2/1,061 as the death rate for the worst-case scenario (Scenario 3) to account for the very unlikely outcome of these two deaths being attributed to vaccine related myocarditis/pericarditis.

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4. Results
This section summarizes the results for three major model scenarios.
4.1. Scenario 1: Base case
Our model scenarios start with the base case that is using the most recent available incidence data on July 10, 2021 and assume a 6-month vaccine protection period, 90% vaccine efficacy against both COVID-19 case and hospitalization, and zero myocarditis/pericarditis death rate.
Figures 2, 3, and 4 summarize the results for analyses of combined male/female, male only, and female only, respectively. The results indicate that benefit-risk is more favorable for male and female combined, female only, and male >18 years old. The model predicted far more prevented
COVID-19 cases compared to excess myocarditis/pericarditis for male 12-15 and 16-17 years old, but the model predicted 142 prevented COVID-19 hospitalizations vs. 196 myocarditis/pericarditis hospitalizations for male age 16-17 years old and 122 prevented COVID-19 hospitalizations vs. 179 myocarditis/pericarditis hospitalizations for male 12-15 years old.
However, hospitalizations associated with COVID-19 have more severe clinical outcomes than those associated with myocarditis/pericarditis. For this reason, we consider that the benefits of the vaccine outweigh the risks in this scenario even for male age 12-15 and 16-17 years old. See Table 5 for details and the benefit-risk results for 16-17 year olds.
4.2. Scenario 2: Most likely scenario
We constructed a scenario that most likely represents the short-term moving direction of the pandemic. We assume 6-month vaccine protection, and 10X higher COVID-19 case incidence and 4X higher COVID-19 hospitalizations incidence compared to the incidence on July 10. We also assume lower vaccine efficacy (70% against COVID-19 case, 80% against hospitalization) against newly emerging virus variants such as Delta strain. We assumed zero myocarditis death rate based on our best knowledge on the vaccine related myocarditis.
Figures 5, 6, and 7 summarize the results for analyses of combined male/female, male only, and female only, respectively. For all age/sex groups and across all attributes, the benefits clearly outweigh the risks in this scenario. See Table 5 for details and benefit-risk results for 16-17 year olds.
4.3. Scenario 3: Worst case scenario
We also constructed the worst-case scenario using the most conservative assumptions for all the model inputs. We assumed 6-month vaccine protection, the COVID-19 incidence as of July 10, 2021, 70% vaccine efficacy against COVID-19 case, 80% vaccine efficacy against COVID-19 hospitalization, and 0.002% (2/1,061) myocarditis/pericarditis death rate.
Figures 8, 9, and 10 summarize the results for analyses of combined male/female, male only, and female only, respectively. Even with the conservative assumption on

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myocarditis/pericarditis death rate, the model predicted 0 deaths associated with myocarditis/pericarditis compared to 1 prevented COVID-19 death for both male 12-15 and 16-17 year old groups. The model predicted 127 prevented COVID-19 hospitalizations vs 196 myocarditis/pericarditis hospitalizations for male age 16-17 years old and 109 prevented COVID-19 hospitalizations vs 179 myocarditis/pericarditis hospitalizations for male 12-15 years old.
Considering the differential clinical outcomes of the hospitalization from two different causes, we consider the benefits of the vaccine still outweigh the risks in this "worst case scenario". See Table 5 for details and the benefit-risk results for 16-17 year olds.
5. Conclusions and discussion
Our results demonstrate that the benefits of BNT162b2 clearly outweigh its risks for all age and sex groups we analyzed. Under the base case scenario and the worst-case scenario (Scenario 1 and 3), we predicted a higher number of myocarditis hospitalizations than the COVID-19 hospitalizations among male 16-17 years old; however, considering the differential clinical implications of COVID-19 and myocarditis hospitalization, we consider the benefits of the vaccine still outweigh its risks. Moreover, under all other scenarios including the most likely (Scenario 2), our model predicted that preventable COVID-19 cases, hospitalizations, and deaths exceed the myocarditis cases and related hospitalizations and deaths for all age and sex groups.
We note that COVID-19 incidence highly influences the predicted benefits of the vaccine. If the disease incidence is higher, the benefits of the vaccine will be greater, and vice versa. Therefore, the benefit-risk conclusion may change if the COVID-19 incidence rate becomes very low in the future. Also, "the worst-case scenario" presented here is the worst only among the modelled scenarios. Scenarios worse than Scenario 3 could occur if the data fall outside the ranges of model inputs we used, such as lower COVID-19 incidence than those reported on July 10, lower vaccine effectiveness against COVID-19 cases (<70%) and against hospitalizations (<80%), and shorter vaccine protection duration (<6 months).

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6. Limitations
• (BENEFIT) The constant COVID-19 incidence rate assumption in our model generates high uncertainty on the estimate of benefits considering the uncertain dynamics of the pandemic. Additionally, estimated benefits of the vaccine would decrease if the vaccine becomes less effective against novel variants of COVID-19. The durability of vaccine protection is another source of uncertainty for the model. Any significant waning of vaccine-induced immunity before 6 or 12 months would reduce the benefit of the vaccine.
• RISK) There is uncertainty in the myocarditis case and death rates attributable to the vaccine. In the US, two deaths among those less than 30 years old occurred following the administration of BNT162b2 and were evaluated by FDA and CDC. Based on the review of the available clinical information, the causes of death for both cases are not thought to be related to vaccination. To estimate myocarditis/pericarditis risk attributable to the vaccine, health claims data are used, which have inherent limitations such as small sample sizes for these rare outcomes. The cases have not been validated by medical chart review. The crude myocarditis rate in our model was adjusted using myocarditis 2019 background rate, which did not account for COVID-19 infection related risk of myocarditis/pericarditis and may lead to overestimating the risk attributed to the vaccine.
• (BENEFIT-RISK BALANCE) Some benefit-risk endpoints in our assessment are difficult to compare directly, for example, hospitalizations from COVID-19 and myocarditis hospitalizations. This benefit-risk assessment does not consider the potential long-term health impacts of COVID-19 or myocarditis. Also, it does not include secondary benefits and risks, such as any potential impact on the public trust in COVID-19 vaccines and the benefit ofthe vaccine in reducing the viral transmission in the population. In this analysis, we did not investigate the benefits and risks of subpopulations with comorbidity due to limited information. The benefit-risk profile could be different depending on the individual's health condition.

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7. Acknowledgements
We thank J. Rosser Matthews, Ph.D., and Katherine Scott, M.D., for editing this Benefit-Risk review memo.

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References
1. Garwood, F. "Fiducial limits for the Poison distribution." Biometrika 28.3/4 (1936): 437-442.
2. Lopez Bernal, Jamie, et al. "Effectiveness of Covid-19 vaccines against the B. 1.617. 2 (delta) variant." New England Journal of Medicine (2021).
3. Marshall, Mayme, et al. "Symptomatic acute myocarditis in seven adolescents following Pfizer-BioNTech
COVID-19 vaccination." Pediatrics (2021): 2.
4. Nasreen, Sharifa, et al.
"Effectiveness of COVID-19 vaccines against variants of concern,
Canada." Medrxiv (2021).
5. Oliver, Sara E., et al. "The advisory committee on immunization practices' interim recommendation for use of Pfizer-BioNTech COVID-19 vaccine- United States, December 2020." Morbidity and Mortality Weekly Report
69.50 (2020): 1922.
6. "Population-Level Risk-Benefit Analysis." Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 5 May 2021, www.cdc.gov/vaccines/covid-19/info-by-product/janssen/risk-benefit-analysis.html.
7. Shay, David K., Tom T. Shimabukuro, and Frank DeStefano. "Myocarditis occurring after immunization with mRNA-based COVID-19 vaccines." JAMA cardiology (2021).
8. Sheikh, Aziz, et al. "SARS-CoV-2 Delta VOC in Scotland: demographics, risk of hospital admission, and vaccine effectiveness." The Lancet (2021).
9. Thomas, Stephen J., et al. "Six Month Safety and Efficacy of the BNT162b2 mRNA COVID-19
Vaccine." medRxiv (2021).
10. Watkins, Kevin, et al. "Myocarditis after BNT162b2 vaccination in a healthy male." The American Journal of Emergency Medicine (2021).

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List of Tables
Table 1. Low and high values for model input parameters considered in our sensitivity analysis
...... 15
Table 2. The three main model scenarios with different combinations of model input values that are shown on Table 1...
Table 3. Vaccine coverage and COVID incidences by sex and age groups
...15
..15
Table 4. Optum-reported myocarditis cases for 1 million fully vaccinated individuals by age and sex.
95% confidence intervals for the rates are shown in brackets ......
................. 15
Table 5. Model predicted benefit-risk outcomes of Scenarios 1-3 for the 16-17-year-old groups..........16
List of Figures
Figure 1. Benefits-risks value tree.
Figure 2. Results of Scenario 1 for combined male and female populations
Figure 3. Results of Scenario 1 for the male population ...
Figure 4. Results of Scenario 1 for the female population ....
Figure 5. Results of Scenario 2 for combined male and female populations....
Figure 6. Results of Scenario 2 for the male population ....
Figure 7. Results of Scenario 2 for the female population..
Figure 8. Results of Scenario 3 for combined male and female populations
Figure 9. Results of Scenario 3 for the male population.
Figure 10. Results of Scenario 3 for the female population.....
16
.....17
..18
...19
....... 20
.21
.22
.23
24
.25

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Table 1. Low and high values model input parameters considered in our sensitivity analysis
Model inputs
Vaccine protection period
Vaccine efficacy against cases
Vaccine efficacy against hospitalization
COVID-19 case incidence rate
COVID-19 hospitalization case incidence rate
Myocarditis death rate
Low
6 months
70%
80%
July 10 rate
July 10 rate
0%
High
12 months
90%
90%
10X July 10 rate
4X July 10 rate
0.002%
Table 2. The three main model scenarios with different combinations of model input values that are shown on
Table 1
Scenario
Scenario 1
Scenario 2
(Most Likelv)
Scenario 3
(Worst Case
Protection
period
Low
Efficacy against
Efficacy against
cases hospitalization
High
High
COVID-19
case incidence
Low
COVID-19 hospitalization incidence
Low
Vaccine attributable myocarditis death rate
Low
Low
Low
Low
High
High
Low
Low
Low
Low
Low
Low
High
Table 3. Vaccine coverage and COVID incidences by sex and age groups
COVID-19 Hospitalizati Percent of Percent of
Vaccinated cases/100k ons/100k hospitalized hospitalized
Sex
Female
Male
Age group
12-15
16-17
18-24
25-29
12-15
16-17
18-24
25-29
Population1 population?
persons persons3 going to ICU3 who die
8,183,216
2,886,252
4,119,686
1,985,672
14,923,948
8.033.040
11,428,122
5,918,524
8,535,307
2,815,693
4,300,731
1,826,299
15,633,953
7,217,945
12,036,982
5,592,473
37.3
47.9
64.6
68.6
33.1
42.9
53.3
57.8
0.671
23.9
1.593
19.5
2.025
8.1
2.45
5.9
0.35
31.8
0.35
32.7
0.8
22.2
0.875
22.7
0
0.7
1
0.3
0.9
0.7
0.6
1.5
Source: 1-CDC Wonder, 2-COVID Data Tracker, 3-COVID NET
Table 4. Estimated excess number of myocarditis/pericarditis cases for 1 million fully vaccinated individuals with Pfizer BNT162b2 by age and sex. 95% confidence intervals for the rates are shown in brackets
Rate of excess myocarditis/pericarditis per 1 million fully vaccinated and 95%
Sex
Male
Female
Age (years)
12-15
16-17
18-25
26-35
12-15
16-17
18-25
26-35
confidence intervals
179 [38, 332]
196 [36, 424]
131 [27, 224]
49 [0, 123]
32 [0, 235]
36 [0, 298]
57 [9, 147]
2 [0. 801
Source: Optum Database pre-adiudicated claims 12/11/2020 - 07/10/2021

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Table 5. Model predicted benefit-risk outcomes of Scenarios 1-3 for the 16-17-year-old groups
Benefits
Prevented
Prevented Prevented Prevented
COVID-19
COVID-19
COVID-19 COVID-19 Myocarditis
Scenario
Cases Hospitalizations
ICUs
Deaths
Risks
Excess
Excess
Excess
Myocarditis Myocarditis
Cases Hospitalizations
Deaths
Males & Females
Scenario 1
Scenario 2
Scenario 3
19,425
151.080
15.108
Males only
Scenario 1
Scenario 2
Scenario 3
17.456
135,771
13.577
Females only
Scenario 1
Scenario 2
Scenario 3
21,657
168,443
16.844
Figure 1. Benefits-risks value tree.
Benefits
241
855
214
142
506
127
350
1245
311
59
210
52
2
6
1
116
116
116
47
166
41
1
4
1
196
196
196
68
243
61
2
9
2
36
36
36
Preventable COVID cases
Preventable COVID hospitalizations
Preventable COVID ICUs
116
116
116
196
196
196
36
36
36
Preventable COVID deaths
0
0
o 00
O
Pfizer-BioNTech
COVID-19 Vaccine
Risks
Excess myocarditis/pericarditis cases
Excess myocarditis/pericarditis hospitalizations
Excess myocarditis/pericarditis deaths
Source : Reviewer Analysis

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Figure 2. Results of Scenario 1 for combined male and female populations
BENEFITS
12-15 yo
Preventer counstepains
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
160
12,489
Prevented COVID-19 Cases
400
300
200
100
16-17 Yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
19.425
Prevented COVID.19 Cases
400
300
200
100
106
106
200
116
116
100
200
300
18-24 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
CERO
Prevented COVID-19 Hospitalizations
27,539
Prevented COVID-19 Cases
400
200
100
100
200
300
25-29 yo
Prevented COVID-19 Deaths
Prevented COVID.19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases29,032
Source: Reviewer Analvsis
400
300
200
100
100
200
300
RISKS
400
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess MyoPericarditis Hospitalization!
Excess Myo/Pericarditis Cases
500

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Figure 3. Results of Scenario 1 for the male population
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUS
Prevented COVID-19 Hospitalizations g 581
prevented countere casas
300
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations 17.456
Prevented COVID-19 Cases
400
300
12-15 vo
122
200
100
16-17 yo
142
200
100
18-24 yo
Prevented COVID-19 Deaths
Prevented COVID.19 Hospitalizations
23,183
Prevented COVID-19 Cases
Prevented COVID-19 Deaths
Prevented COVID.19 ICUs
Prevented COVID-19 Hospitalizations
25.249
Source : Reviewer Analysis
400
382
400
300
200
100
87
25-29 yo
300
200
• 179
• 179
10
200
300
196
196
100 200
300
131
131
100
200
300
200
300
RISKS
400
400
400
400
Excess Myo/Pericarditis Deaths
Excess Mvo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500

Page 19 - Hong Yang - 125742/o
Figure 4. Results of Scenario 1 for the female population
BENEFITS
12-15 yo
Prevented COVID-19 Deaths
Prevented soneteos
Prevented COVID-19 Hospitalizations
13,479
199
Prevented COVID-19 Cases
37
200
16-17 yo
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
350
400
100
200
18-24 yo
10 I
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
1,026
Prevented COVID-19 Cases
400
200
57
100
100
70
200
25-29 vo
Prevented COVID-19 Deaths
Prevented COVID.19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 33,317
Source : Reviewer Analysis
400
200
100
200
300
300
300
RISKS
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Fycess Muo Pericarditis Case
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500

Page 20 - Hong Yang - 125742/0
Figure 5. Results of Scenario 2 for combined male and female populations
BENEFITS
12-15 yo
Prevented COVID.19 Deaths
Prevented COVID-19 ICUs
156
Prevented COVID-19 Hospitalizations
Prevented COVID.19 Cases
97,136
400
300
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
210
855
Prevented COVID-19 Hospitalizations
151,080,
400
300
200
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
298
Prevented COVID-19 Hospitalizations
214,189
400
300
200
100
16-17 yo
100
18-24 yo
21 M
100
106
106
200
116
116
100
200
94
94
100
200
300
300
25-29 yo
Prevented COVID.19 Deaths
Prevented COVID-19 ICUs
2,715
Prevented COVID-19 Hospitalizations
225,807
Prevented COVID.19 Cases
400
Source : Reviewer Analysis
■95
300
200
100
100
200
300
RISKS
400
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
EXCEsS MvoPericarditis Deaths
Excess Mo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500

Page 21 - Hong Yang - 125742/0
Figure 6. Results of Scenario 2 for the male population
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
435
89,767
Prevented COVID-19 Cases
12-15 yo
100
16-17 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
18-24 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations 1,236
Prevented COVID-19 Cases 180,31
300
200
100
25-29 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID.19 Hospitalizations
Prevented COVID-19 Cases
300
200
100
Source : Reviewer Analysis
179
196
300
137
100
200
300
RISKS
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
Dexcess mivovercarenus eacns
excess myoPericarditis Mospitalizations
400
a00
500
500
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
Excess Myo/Pericarditis Hospitalizations

Page 22 - Hong Yang - 125742/0
Figure 7. Results of Scenario 2 for the female population
BENEFITS
12-15 yo
Prevented COVID-19 Death:
Prevented COVID.19 ICI
160
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
200
100
Prevented COVID.19 Deaths
Prevented COVID-19 ICUS
Prevented COVID-19 Hospitalization:
Prevented COVID-19 Cases
1,245
400
300
243
20
16-17 yo
200
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID.19 Cases
300
200
100
100
18-24 yo
36
25-29 vo
Prevented COVID-19 Deaths
Provented on aTe enc
Prevented COVID-19 Hospitalization:
Prevented COVID-19 Cases 259,1
Source : Reviewer Analysis
300
200
100
100
200
200
200
200
300
300
300
RISKS
Excess Mvo/Pericarditis Deaths
Excess Mo/Pericarditis Hospitalizations
Excess Mvo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
400
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
400
500
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess MyoPericarditis Cases
400

Page 23 - Hong Yang - 125742/0
Figure 8. Results of Scenario 3 for combined male and female populations
BENEFITS
12-15 yo
Prevented COVID-19 Deaths
Prevented COVID-19 Hospitalizations
9,714
Prevented COVID-19 Cases
RISKS
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
300
16-17 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
15,108
Excess Myo/Pericarditis Deaths
excess myoPericarditis Mospitalizations
excess vonvercardias cases
10
100
300
18-24 yo
5 I
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
587
Prevented COVID-19 Hospitalizations
Prevented cOVID-19 cases
300
200
100
200
300
400
25-29 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 22,581
Source : Reviewer Analysis
• 26
200
100
200
300
400
500
500
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Mvo Pericarditis Cases
EXCESS MyoPericarditis Death:
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases

Page 24 - Hong Yang - 125742/0
Figure 9. Results of Scenario 3 for the male population
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUS
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 8,977 |
300
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
13,577
Prevented COVID-19 Cases
12-15 yo
109
200
100
16-17 yo
127
400
300
200
100
18-24 yo
Prevented COVID-19 Deaths
Prevented COVID.19 Hospitalizations
Prevented COVID-10 Cases 18,031
200
400
300
200
100
25-29 yo
provenred covinste pains
Prevented COVID.19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 19,638
400
Source : Reviewer Analysis
300
100
100
• 179
• 179
200
300
196
196
200
300
131
131
200
300
200
300
RISKS
400
400
400
400
Excess Myo/Pericarditis Deaths
Excess Mvo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500

Page 25 - Hong Yang - 125742/0
Figure 10. Results of Scenario 3 for the female population
BENEFITS
12-15 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
10,484
Prevented COVID-19 Cases
400
300
200
100
100
16-17 yo
Prevented COVID-19 Death‹
Prevented COVID-19 ICU‹
Prevented COVID.19 Hospitalizations
16.844
Prevented COVID-19 Cases
311
400
200
Prevented COVID-19 Deaths
Prevented COVID.19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID.19 Cas
25,451
200
Prevented COVID.19 Deaths
Prevented COVID.19 ICUs
Prevented COVID.19 Hospitalizations
Prevented COVID-19 Cases 25,913
Source : Reviewer Analvsis
300
200
100
18-24 yo
9 I
74 L
25-29 yo
62 B
100
100
100
200
200
200
300
200
300
RISKS
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
400
500
excoss ivorPericardiris earns
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
400
400
400
500
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500

Page 26 - Hong Yang - 125742/0
Supplementary Materials
Text S1. Narratives of Myocarditis Death cases and Terms Used in VAERS Search
Table S1. Additional model scenarios with different combinations of model input values that are shown on Table 1 in the main text
Figure S1: Results of Scenario 4 for combined male and female populations.
Figure S2: Results of Scenario 4 for the male population.
Figure S3: Results of Scenario 4 for the female population.
Figure S4: Results of Scenario 5 for combined male and female populations.
Figure S5: Results of Scenario 5 for the male population.
Figure S6: Results of Scenario 5 for the female population.
Figure S7: Results of Scenario 6 for combined male and female populations.
Figure S8: Results of Scenario 6 for the male population.
Figure S9: Results of Scenario 6 for the female population.
Figure S10: Results of Scenario 6 for combined male and female populations.
Figure S11: Results of Scenario 6 for the male population.
Figure S12: Results of Scenario 6 for the female population.

Page 27 - Hong Yang - 125742/0
Text S1. Narratives of Myocarditis Death cases and Terms Used in VAERS Search
Narratives of Myocarditis Death Cases
Pfizer BioNTech Vaccine
VAERS ID 1406840: 13 years old male with attention deficit hyperactivity disorder and developmental coordination disorder experienced flu-like symptoms for is days and then was found deceased; onset of symptoms 1-day post-vaccination. The preliminary autopsy report revealed cardiomegaly with biventricular dilatation, bilateral serous pulmonary effusions and serous pericardial effusion, marked pulmonary edema and congestion, and moderate degree of diffuse cerebral edema. COVID-19 and influenza A/B tests were negative. Additional testing on autopsy found this patient died of sepsis due
Clostridium septicum.
VAERS ID 1486852: 21 years old female who experienced fever, confusion, seizure, cardiac arrest days post vaccination. Autopsy revealed histology with extensive lymphocytic/plasmocytic myocarditis with rare eosinophils no granuloma. Additional review by pathologists at CDC found the patient had severe myocarditis with intravascular leukocytosis suggestive of sepsis.
Reviewer Comment: Both of these death cases had alternate etiologies likely related to non-COVID-19 infections and were not attributed to vaccine.
VAERS Search Terms
Atypical mycobacterium pericarditis, Autoimmune myocarditis, Autoimmune pericarditis, Bacterial pericarditis,
Coxsackie myocarditis,
Coxsackie pericarditis, Cytomegalovirus myocarditis,
Cytomegalovirus pericarditis, Enterovirus myocarditis, Eosinophilic myocarditis, Hypersensitivity myocarditis, Immune-mediated myocarditis, Myocarditis, Myocarditis bacterial, Myocarditis helminthic, Myocarditis infectious, Myocarditis meningococcal, Myocarditis mycotic, Myocarditis post infection, Myocarditis septic, Pericarditis, Pericarditis adhesive, Pericarditis constrictive, Pericarditis helminthic, Pericarditis infective, Pericarditis mycoplasmal, Pleuropericarditis, Purulent pericarditis, Viral myocarditis, Viral pericarditis.

Page 28 - Hong Yang - 125742/0
Table S1. Additional model scenarios with different combinations of model input values that are shown on Table 1 in the main text.
Efficacy
Scenario
4
5
6
7
Protection period
Low
High
Low
Low
against cases
High
High
Low
Low
Efficacy against hospitalization
High
High
Low
Low
Note: Additional scenarios are used to examine the impact of specific changes to model inputs
COVID-19
COVID-19 case hospitalization
incidence
incidence
High
High
Low
Low
Low
Low
High
High
Vaccine attributable myocarditis death rate
Low
Low
Low
High

Page 29 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations 639
Prevented COVID-19 Cases
124,889
400
Prevented COVID-19 Deaths
Prevented COVID-19 ICUS 962
Prevented COVID-19 Hospitalizations 194,245,
Prevented COVID.19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUS 2.639
Prevented COVID-19 Hospitalizations
335
275,386,
Prevented COVID.19 Cases
400
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
3,055
Prevented COVID-19 Hospitalizations
290.32
Prevented COVID.19 Cases
400
300
236
300
300
176
200
200
200
200
12-15 yo
100
16-17 yo
18-24 yo
24 B
o
100
25-29 yo
106
106
100
200
• 116
• 116
94
94
100
200
1 26
300
300
300
100
RISKS
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
о
100
2∞ 300
400
500
Figure S1: Results of Scenario 4 for combined male and female populations

Page 30 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 15.415
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
569
Prevented COVID-19 Hospitalizations
174 56'
Prevented COVID-19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
1,391
Prevented COVID-19 Hospitalizations
231,833
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
1.530
Prevented COVID-19 Hospitalizations
400
300
400
300
309
400
300
252.490
Prevented COVID-19 Cases
400
200
186
200
200
300
200
100
100
12-15 yo
16-17 yo
18-24 yo
25-29 vo
100
179
100
200
300
196
100
200
300
| 131
| 131
300
100 200
RISKS
400
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Figure S2: Results of Scenario 4 for the male population

Page 31 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
795
Prevented COVID-19 Hospitalizations
134,791
Prevented COVID.19 Cases
12-15 yo
400
190
200
300
273
100
0
16-17 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
1,400
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 16,570
| 36
100
100
200
300
RISKS
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
4,105
327,222
Prevented COVID.19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
4,757
Prevented COVID-19 Hospitalizations
333,171
Prevented COVID.19 Cases
333
300
400
300
200
500
200
400
18-24 yo
41 1
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
100
200
300
400
500
25-29 Yo
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizatior
Excess Myo/Pericarditis Cases
200
100
0
100
200
300
400
500
Figure S3: Results of Scenario 4 for the female population

Page 32 - Hong Yang - 125742/0
BENEFITS
Prevented COVID.19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
320
25,046
Prevented COVID.19 Cases
400
300
12-15 yo
RISKS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
38 956
Prevented COVID-19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
1.323
Prevented COVID-19 Hospitalizations
55,228
Prevented counseencase
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
1,531
Prevented COVID-19 Hospitalizations
Prevented COVID.19 Case
88
200
100
16-17 yo
118
200
18-24 yo
12 1
o
168
300
200
100
25-29 yo
181
| 106
| 106
100
• 116
• 116
94
| 94
100
200
1 26
300
300
400
300
200
100
400
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
100
2∞ 300
400
500
Figure S4: Results of Scenario 5 for combined male and female populations

Page 33 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID.19 Hospitalizations
35.00
Prevented COVID-19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID.19 Case
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
400
Prevented COVID.19 Hosnitalizations
Prevented COVID-19 Cases 50,637
400
245
300
300
200
200
155
200
174
300
200
100
100
100
12-15 yo
16-17 yo
18-24 yo
25-29 vo
12
100
179
179
100
200
300
196
100
200
300
| 131
| 131
200
300
RISKS
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
100 200
400
500
Figure S5: Results of Scenario 5 for the male population

Page 34 - Hong Yang - 125742/0
BENEFITS
Prevented COVID.19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
27,032
Prevented COVID-19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
702
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
2,058
Prevented counselecase
65,624
400
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
2,385
Prevented COVID-19 Hospitalizations
Prevented ounselecas
es 66,817
400
300
300
12-15 yo
95
200
100
100
16-17 yo
137
36
100
18-24 yo
21 B
167
200
100
200
200
200
25-29 yo
141
300
200
100
100
200
300
300
300
RISKS
400
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
400
500
Figure S6: Results of Scenario 5 for the female population

Page 35 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
9,714
Prevented COVID-19 Cases
300
142
200
200
12-15 yo
39 П
100
16-17 yo
52
RISKS
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
15,108,
Prevented COVID-19 Cases
214
| 106
| 106
100
200
• 116
• 116
300
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
300
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
587
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
21,419
74 I
100
18-24 yo
о
25-29 yo
94
|94
100
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
400
300
200
200
300
400
500
Prevented COVID-19 Deaths
Excess Myo/Pericarditis Deaths
Prevented COVID-19 ICUs
679
Prevented COVID-19 Hospitalizations
22,581
Prevented COVID.19 Cases
26
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
400
300
200
100
100
200 300
400
500
Figure S7: Results of Scenario 6 for combined male and female populations

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BENEFITS
Prevented COVID-19 Deaths
Prevented COVID.19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
400
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
13,577
Prevented COVID-19 Cases
400
300
300
200
200
109
157 1
12-15 yo
35 E
100
16-17 yo
100
179
200
300
RISKS
400
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
196
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Mo Pericarditis Cases
18-24 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 18,031,
200
200
131
| 131
200
300
400
300
400
500
500
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
25-29 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID.19 Hosnitalizations
1300
19.638
Prevented COVID-19 Cases
400
300
200
100
100 200
Figure S8: Results of Scenario 6 for the male population
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases

Page 37 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
10,484,
Prevented COVID-19 Cases
12-15 yo
300
177
200
1 32
100
RISKS
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
16,844
Prevented COVID-19 Cases
311
200
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
912
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases 25,451
100
16-17 yo
61
18-24 yo
9 I
o
74 I
100
200
300
1 36
1 36
100
Excess My/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
300
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalization
Excess Myo/Pericarditis Cases
400
300
200
100 200
300
400
500
25-29 yo
Prevented COVID-19 Deaths
Excess Myo/Pericarditis Deaths
Prevented COVID-19 ICUs
1,057
Prevented COVID-19 Hospitalizations
25,913
Prevented COVID.19 Cases
Excess Myo/Pericarditis Hospitalizatior
Excess Myo/Pericarditis Cases
400
300
200
100
100
200
300
400
500
Figure $9: Results of Scenario 6 for the female population

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BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUS s68
Prevented COVID-19 Hospitalization‹
97,136
Prevented COVID-19 Cases
12-15 yo
RISKS
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
excess ivorrencarcus cases
Prevented COVID-19 Death:
Prevented COVID-19 CUs
Prevented COVID-19 Hospitalizations
151,080
Provented COVID.19 Cases
Prevented COVID-19 Deaths
Provented COVID.19 ICI
Prevented COVID-19 Hospitalizations 3,346
214,18
Prevented COVID-19 Cases
400
Prevented COVID.19 Deaths
Prevented cOVID-19ICUS
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
225,807,
400
300
300
200
200
200
300
200
16-17 yo
18-24 yo
100
25-29 yo
106
200
300
| 116
116
100
200
94
100
200
1 26
300
300
100
100
_ 200 300
400
400
sOn
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Mo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
400
500
Figure S10: Results of Scenario 7 for combined male and female populations

Page 39 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
435
Prevented COVID-19 Cases
12-15 yo
RISKS
Excess Mvo Pericarditis Death:
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
16-17 yo
Prevented COVID-19 Deaths
Prevented COVID.19 ICUs
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Cases
506
138
166
200
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
Droventer COVID 1o Desthe
Provented COVID.19 ICIe
Prevented COVID-19 Hospitalizations
Prevented COVID-19 Case
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID-19 Hospitalizations
Drovented COvID 1O caeor
300
2774
200
309
196
100
100
200
18-24 vo
100
25-29 Yo
30
131
131
200
400
500
400
200
100
Excess Mo/Pericarditis Death:
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
300
400
500
Figure S11: Results of Scenario 7 for the male population

Page 40 - Hong Yang - 125742/0
BENEFITS
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
Prevented COVID.19 Hoenitalizations
104.837
Prevented COVID-19 Cases
12-15 vo
300
169
200
31
100
200
300
16-17 yo
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
1.245
Prevented COVID.19 Heenitalizations
Prevented COVID-19 Cases
400
Prevented COVID-19 Deaths
Prevented COVID-19 ICUs
3,649
Prevented COVID-19 Hospitalizations
Prevented COVID.19 Cases
300
296
300
200
100
200
300
18-24 yo
о
RISKS
400
400
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
sOC
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
500
Excess Myo/Pericarditis Deaths
Excess My/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
400
200
100
200
300
400
25-29 yo
Prevented COVID.19 Deaths
Prevented COVID-19 ICUs
Prevented COVID.19 Hospitalizations
Prevented COVID-19 Cases 259,13.
Excess Myo/Pericarditis Deaths
Excess Myo/Pericarditis Hospitalizations
Excess Myo/Pericarditis Cases
200
100
100
400
500
Figure S12: Results of Scenario 7 for the female population