key: cord-0291571-gofmwb91 authors: Pillay, J.; Bialy, L.; Gaudet, L.; Wingert, A.; Mackie, A.; Paterson, D. I.; Hartling, L. title: Myocarditis and Pericarditis following COVID-19 Vaccination: Rapid Systematic Review of Incidence, Risk Factors, and Clinical Course date: 2021-11-21 journal: nan DOI: 10.1101/2021.11.19.21266605 sha: 2217fe4a950c2ee7947469eb23d72455428ce21d doc_id: 291571 cord_uid: gofmwb91 Objectives: Myocarditis and pericarditis are adverse events of special interest after vaccination with mRNA vaccines. This rapid systematic review examined incidence rates of myocarditis and pericarditis after COVID-19 vaccination, and the presentation and clinical course of cases. Design: Rapid systematic review Data sources: Medline, Embase and the Cochrane Library were searched from October 2020 to October 6, 2021; reference lists and grey literature (to Oct 21, 2021). Review methods: Randomized controlled trials (RCTs) and large population-based/multisite observational studies and surveillance data reporting on myocarditis or pericarditis in people of any age after receiving any COVID-19 vaccine; systematic reviews of case series. A single reviewer completed screening and another verified 50% of exclusions, using a machine-learning program to prioritize records. A second reviewer verified all exclusions at full text, data extractions, and (for incidence) risk of bias assessments using Cochrane Risk of Bias 2.0 and Joanna Briggs Institute tools. Certainty of evidence ratings for incidence were based on team consensus using GRADE. Patient partners provided key messages from their interpretations of the findings. Results: 3457 titles/abstracts and 159 full texts were screened. For incidence rates we included 7 RCTs (n=3732 to 44,325) and 22 large observational studies/data sources using passive (n=10) and active (n=12) surveillance; for case presentation, we included 11 case series published as articles and three based on publicly available websites (n=12,636 cases). Mainly due to imprecision, the RCTs provided very low certainty evidence for incidence of myocarditis or pericarditis. From observational data, the incidence of myocarditis following mRNA vaccines is low but probably highest in males 12-17 years (55 [7-day risk] to 134 [30-day risk] cases per million; specific to Pfizer) and 18-29 years (40 [7-day risk] to 99 [21-30 day risk]) cases per million) (Moderate certainty evidence). Incidence is lower (<20 per million) or little-to-none in older ages and across all ages of females (Low certainty). Evidence for pericarditis was of very low certainty. Among adult males under 40 years, Moderna compared with Pfizer vaccine may be associated with a small increase (<20 per million) in risk for myocarditis or (one of) myocarditis or pericarditis following vaccination (Low certainty); the evidence for youth under 18 years was very uncertain. No study examined differences in incidence based on pre-existing condition(s) or risk factors apart from age and sex. The majority of myocarditis cases involved males (often >90%) in their 20s, with a short symptom onset of 2 to 4 days after a second dose (71-100%). The majority of cases presented with chest pain/pressure and troponin elevation; a minority (<30%) had left ventricular dysfunction. Most were hospitalized ([≥]84%), without stays in intensive care units, for a short duration (2-4 d) and treated with anti-inflammatory and/or other supportive therapies. Almost all reports of death are from unverified cases and of unclear cause. Most cases of pericarditis were unconfirmed; for this outcome there appears to be more variation in age, sex, onset timing and rate of hospitalization. Conclusions: Incidence of myocarditis following mRNA vaccines is low but probably highest in males 12-29 years old. Existing evidence does not strongly support preference of one mRNA vaccine, even in young males. Continued active surveillance of myocarditis incidence out to 30 days from dosing is recommended with respect to i) new populations (i.e., children <12y), ii) third and subsequent doses, and iii) affected individuals receiving subsequent mRNA vaccine doses. Future research is needed to examine other risk factors and long-term effects. Case reports and surveillance signals [1] [2] [3] [4] pericarditis after COVID-19 vaccination appeared as early as April 2021. This led to the surveillance of adverse events of special interest following vaccination with messenger RNA (mRNA) vaccines manufactured by Pfizer/BioNTech and Moderna. Estimated rates of myocarditis in the United Kingdom (UK) 5 and the United States (US) 6 are 11 and 1.3 cases per 100,000 person-years, respectively, regardless of age. Estimated background/expected rates of myocarditis and pericarditis following COVID-19 vaccination in the US, adjusted for a 7-day risk period where most cases appear, are 0.2 and 1.4 per 1 million people, respectively. 6 Historically, myocarditis has been more prevalent in males than females, from childhood through young adulthood; 7 this trend has been evident in early case series of post-COVID-19 vaccinations. 8 9 Symptoms indicative of myocarditis or pericarditis typically include new onset and persisting chest pain, shortness of breath, and/or palpitations. 10 Diagnosis of a probable case of myocarditis usually requires elevated troponin levels and/or findings from imaging (e.g., echocardiography, magnetic resonance imaging) or other testing (e.g., ECG); histopathology to provide definitive diagnosis is not usually performed. 11 Differential diagnoses, including COVID-19 infection and community-acquired myocarditis, should be considered and ruled out. 11 12 Most people experiencing these conditions will fully recover, however, in rare cases, myocarditis can lead to heart failure or asymptomatic left ventricular dysfunction. Long-term consequences associated with pericarditis include one or more recurrences and, rarely, thickening of the pericardium and constrictive heart filling. 13 This rapid systematic review aimed to provide estimates of the incidence rates for these harms after vaccination for COVID -19, including whether these vary by patient and/or vaccine characteristics, and to describe the clinical course of myocarditis and pericarditis after COVID-19 vaccination. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint 1 . What is the incidence of myocarditis and pericarditis following COVID-19 vaccination, and does the incidence vary by patient (e.g., age, sex, race/ethnicity, pre-existing conditions [e.g. cardiac diseases] or infections [e.g., ) and vaccine factors (e.g. vaccine type, dose, interval)? 2. What are the characteristics and short-term clinical course in patients with myocarditis and pericarditis after COVID-19 vaccination? We conducted this rapid systematic review following a protocol developed before starting to screen the literature. Due to the rapid development and conduct of this review we did not register the protocol. We followed guidance for systematic reviews when conducting 14 and reporting 15 this review. We worked with an experienced medical information specialist to develop the search strategy, which was peer-reviewed 16 (Appendix 1). Searches combined concepts for COVID-19, vaccines, and myocarditis/ pericarditis/cardiovascular manifestations/adverse events/surveillance. We limited our search to articles published since October 2020. We did not add limits for language, country, or study design, but had limits for human (not animal only) studies and commentaries. Using the multifile option as well as the deduping tool in Ovid, we searched Ovid MEDLINE(R) and Epub Ahead of Print, In-Process, In-Data-Review & Other Non-Indexed Citations and Daily <1946 to October 05, 2021> and Embase <1974 to 2021 October 05>. We also searched the Cochrane Library and medRxiv (last 2 months). These searches were run on October 6, 2021. We searched grey literature by scanning 20 key national websites (e.g., Public Health Agency of Canada, UK's Medicines & Healthcare Products Regulatory Agency, Centers for Disease Control and Prevention) to identify unpublished data. We also scanned reference lists of included studies. Our inclusion criteria are outlined in Table 1. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint All reviewers undertaking screening conducted a pilot round in Excel using 300 records. We then conducted screening and selection in DistillerSR (Evidence Partners) using structured forms. For title and abstract review, we applied the machine learning program Daisy AI which continually reprioritizes records during screening. 17 A single reviewer screened all titles/abstracts and another reviewer verified exclusions for the first 50% of records. For full text selection, a single reviewer reviewed all records, with all exclusions verified by another reviewer. Studies were further verified for inclusion during data extraction. For research question 1, when reports collected data from similar/overlapping populations (e.g., US national surveillance data), we first included the study with the most recent data and then included additional studies if they differed in their methods (e.g., of verifying cases, differing risk intervals [period after the vaccine where case are counted]), differing age and/or sex stratification, use of unvaccinated or similar controls). For randomized controlled trials (RCTs), we used the report of the largest population as the primary (included) publication and cited associated papers used for data extraction; sub-studies within RCTs, for example of different ages, were considered different studies. For research question 2, we mapped the case series and case reports contained within the relevant reviews. This served as a baseline for identifying the most recent and comprehensive data source for each geographic region (i.e., US, Canada, UK, Europe, and Israel). When more recent data were reported in studies included in research question 1, these were included in place of studies identified through the reviews. For regions with multiple reports, we prioritized data that was most recent, most comprehensive (largest numbers), and that verified cases. Our goal was to avoid overlap in data, i.e., the same cases reported in different sources. However, we did include sources that reported on specific sub-groups (e.g., 12 to 17 year-olds) to present more details on these groups of interest. We have noted in the evidence tables where there may be overlap in cases between reports. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint We extracted all data into structured Word forms and conducted a pilot exercise with two studies. Thereafter, one reviewer extracted all data and another verified eligibility and all data. Discrepancies were resolved by discussion or by a review lead. For research question 1, extracted data related to all elements of the eligibility criteria (Table 1) and data used for risk of bias assessment, focusing on methods for identifying cases (i.e., passive surveillance versus active surveillance/registry data), outcome ascertainment and confirmation/adjudication (including criteria for case definitions and classification), as well as the risk interval for which the events were captured. We distinguished between estimates of incidence compared with an unexposed group (excess incidence/risk differences) versus without a control, and extracted data on incident rates per person-years and per doses of vaccine/people vaccinated (after either dose, dose 1, or dose 2). As available, we extracted data on any stratified or subgroup analyses based on age, sex, preexisting conditions, race/ethnicity, different vaccine types or doses (events captured after any dose, dose 1, or dose 2), and different risk intervals (0-7d vs. 8-28d vs. longer). Effect measures included: incidence rate/cumulative risk (including excess risk [risk difference] when using a control group) and relative effects between groups (e.g., incidence rate ratio (IRR)), adjusted for key confounders (i.e., age, sex, infection status, cardiac and immunodeficiency/autoimmune conditions) when reported. For research question 2, we planned to rely on data from the relevant systematic reviews identified through our search. We used the evidence table presented in an existing review 8 as the foundation for data extraction and presentation of findings as it covered most of the items specified under our outcomes in Table 1 . We added the following items: criteria for confirmation of cases, breakdown of cases by diagnosis (myocarditis, pericarditis, myopericarditis), case source, age included, percent with pre-existing conditions, percent admitted to an intensive care unit (ICU), percent hospitalized, number of fatalities. Most of the studies included in the existing reviews were superseded by more recent publications/data; therefore, we extracted data directly from the relevant case series/data sources. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint For research question 1, all reviewers involved in the risk of bias assessments piloted each risk of bias tool with two papers. We used the Cochrane Collaboration ROB 2.0 tool 18 for RCTs, and the JBI (formally Joanna Briggs Institute) checklist for cohort studies 19 for observational studies/surveillance data. We focused on valid and reliable case finding and outcome ascertainment methods and, in observational studies, accounting for key confounders including age, sex, existing cardiac diseases/conditions, and prior COVID-19 exposure. We used the findings of the risk of bias assessments when undertaking Grading of Recommendations, Assessment, Development and Evaluation (GRADE) assessments of the certainty of the evidence. 20 21 Assessments were completed by one reviewer and verified by another. Discrepancies were resolved by discussion or by a review lead. For research question 2, we did not assess the risk of bias of the included systematic reviews because we did not rely on their reporting or synthesis in any way. We also did not rate the case series data, either published or derived from grey literature or publicly available data sources (e.g., Yellow Card, UK). The intent of question 2 was to characterize these patients and their clinical course without providing quantitative estimates, e.g., of incidence or effectiveness. The main differentiating feature between case series was whether they only reported on cases verified by clinicians; we extracted this information and considered this factor when summarizing the results. For research question 1, we did not pool results due to heterogeneity in case finding (passive vs. active surveillance), dosing and risk intervals, case ascertainment, populations (age and sex), and the large amount of overlap in some study populations. We tabulated all results and compared and contrasted findings between studies based on the major differentiating population, vaccine and methodologic variables. We reached consensus on a best estimate of the incidence (or a range/upper limit based on different risk intervals or other variables), relying when possible on studies that verified cases and used active surveillance. Based on clinical input we developed primary age categories (12-17y, 18-29y, 30-39y, ≥40y) to rely on when possible. If a study contributed more than one result within these (e.g., 20-24y . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint and 25-29y, results for each mRNA vaccine) we took the average of the incident rates. When a study reported an incidence rate (or data to calculate this) and an IRR compared with a control/background rate, but not the difference in incidence (excess incidence over background rate), we calculated the excess incidence (i.e., crude incidence -[crude incidence/IRR]). We assessed the certainty for each of our conclusion statements using GRADE. 20 21 RCTs started at high certainty (i.e., indicating we are very confident that the true effect lies close to that of the estimate of the effect) and observational studies started at low certainty (i.e., our confidence in the effect estimate is limited; the true effect may be substantially different from the estimate of the effect). We rated down based on serious concerns about risk of bias, inconsistency, indirectness, imprecision, and/or reporting biases. We did not apply a threshold for an important effect, but in general considered 10-20 or fewer cases per million doses to be less meaningful for decision-making. We downrated for risk of bias when studies using passive surveillance (assuming some under ascertainment) and unverified cases contributed to a synthesis, and for indirectness for comparisons across all ages and both sexes, due to the large heterogeneity in incidence rates across ages (for males) and sexes. We considered uprating for observational studies due to large incidence rates when no other major limitations were evident. For research question 2, we present the details for each case series in an evidence table and provide a descriptive summary. Two patient/public partners joined the research team for this review (see Acknowledgements). They were not involved in decisions about the research questions or outcomes, which were determined by the funders. The research leads met with these partners to present and discuss the findings and their implications. The partners co-developed with the leads key messages from their perspective. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. After deduplication, our database searches retrieved 3439 citations and other sources identified 18 citations (Appendix 2). After title/abstract screening, we retrieved and screened at full text 159 citations. For question 1 we included 29 studies reported in 32 publications, and for question 2 we included data for 14 case series (9 were reported in studies included in question 1). Appendix 3 contains descriptions of the various national surveillance systems from which reports were collated or data collected. Tables of study characteristics, with all data on results, and risk of bias ratings for question 1 are in Appendix 4. We included seven RCTs (n=3732 to 44,325) 22-28 reported in 10 papers 29-31 , and 22 large observational studies/data sources (reported in publications, presentations, online reports, accessible data; all are considered here as "studies" for simplicity), with identification of cases based on passive surveillance systems (n=10) 9 32-40 or on active surveillance/registry data (n=12). 41-52 Observational data came from the US, Canada, the UK, Israel, and the European Economic Area (EEA). Several data sources were used in multiple studies (e.g., 5 relied on data from the US VAERS) with different methods (e.g., risk interval used, whether cases were confirmed/verified). Nine of the 12 studies using active surveillance included a comparator group to estimate excess incidence. Eleven studies examined age and/or sex subgroups and seven provided data by specific vaccine. None assessed differences in incidence based on pre-existing condition(s), or race/ethnicity. Overall, risk of bias for adverse events from the RCTs was low to "some concerns". Risk of bias was low to "some concerns" for data from active surveillance systems and high for passive surveillance data. Tables 2 and 3 include the Summary of Findings tables for evidence from the observational data, including the GRADE certainty assessments. We refer to studies by their source of adverse event data and the date of data collection; references for each studies using this format are in Appendix 3. Appendix 4 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint We included 11 case series reported in articles (either published, pre-proofs, or pre-prints) 9 Most case series focused on myocarditis (10 reports, n=5,955). The majority of cases (often >90%) involved males with reported median age most often between 20 and 29 years; confirmed cases ranged from 12 to 56 years. Time between last vaccine and symptom onset was on average 2 to 4 days, and the majority (71-100%) presented after a second dose. Most cases presented with chest pain or pressure, and troponin elevation; a minority (<30%) showed left ventricular dysfunction (i.e., LVEF<50%). The majority of myocarditis cases were hospitalized (≥84%) with few admitted to ICU; average length of hospital stay was 2-4 days. NSAIDs were most often used as treatment; other interventions included bisoprolol, ramipril, colchicine, famotidine, steroids (for myocarditis) and intravenous immune globulin (for myopericarditis). Among the series of confirmed cases of myocarditis that reported on . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint fatalities (N=220), one fatality was reported in Israel in a 22-year-old with fulminant myocarditis. The unconfirmed series from the EEA reported 84 fatalities among 5,611 cases (1.5%), though cause of death was not confirmed. Three reports provided data for pericarditis (n=4,309; almost 99% unconfirmed). The majority involved males; however, there was variation across reports (54 to 91%). Median age (59 years) was only reported in one small series (n=37). The same series reported a median interval of 20 days between last vaccine and symptom onset, with 60% presenting after the second vaccination. Hospitalization varied (35% and 73% reported in two series with a total of 59 cases); one series (n=37) reported 3% admitted to ICU and 1 day for median length of stay. One series (n=37) reported 0 fatalities, and a larger series of unconfirmed cases (n=4,250) reported 15 deaths (0.4%). Four reports (n=2,372) included a mix of diagnoses. The majority of patients were males. Median age was 27 years in the report that included all ages (n=956). Time between last vaccine and symptom onset was median 2 days (based on 323 cases). The majority presented after second vaccination (based on 56 cases). The majority were hospitalized (based on 379 cases), with a minority admitted to ICU (13% of n=56). Length of stay was ≤2 days in 75% of patients hospitalized (based on 56 cases). No fatalities were reported in two series (total 379 cases); a third report identified 5 fatalities among 1,037 unconfirmed cases (0.5%). The incidence of myocarditis following mRNA vaccines is low but probably highest in males 12-29 years old, with lower incidences in older ages. In females, the incidence may be very low (12-29 y) or little-to-none (≥30 y). The incidence of either myocarditis or pericarditis may be highest in adolescent males; among adults under 40 years there may be few cases but the broad age range may not have detected any variation by age. Among adult males under 40 years, Moderna compared with Pfizer may be associated with a small increase (<20 cases per million) in risk for myocarditis or (one of) myocarditis or pericarditis following vaccination; the evidence for youth under 18 years was very uncertain. This . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint evidence does not strongly support that one mRNA vaccine should be preferred over the other, even in young males. Although not systematically reviewed in this report, the incidence of myocarditis after vaccination appears to be much lower than that reported after becoming infected with COVID-19 (450 57 to 1,200 58 per million in young males). From the case series, the majority of myocarditis cases involved males (often >90%) in their 20s, with a short symptom onset of 2 to 4 days after a second dose (71-100%). The large majority of cases presented with chest pain or pressure and troponin elevation, and a minority (<30%) also had left ventricular dysfunction. Most were hospitalized (≥84%), without ICU stays, for a short duration (2-4 d) and treated with anti-inflammatory and/or other standard supportive therapies. Among the series of confirmed cases that reported on fatalities (n=220), one fatality was reported in a 22-year old with fulminant myocarditis. Within the EudraVigilance dataset (n=5,611 unconfirmed cases), 84 (1.5%) fatalities were reported, though cause of death is not confirmed. Importantly, the vast majority of affected individuals appear to make a complete recovery based on short-term follow-up. Most cases of pericarditis were unconfirmed; for this outcome there appears to be more variation in age, sex, onset timing and rate of hospitalization across cases. The findings across cases appear to be similar to non-vaccine related myoand pericarditis whereby young males are at highest risk and mortality is very rare. 13 Although the mechanism(s) through which the mRNA vaccines may cause myocarditis or pericarditis are not known, several findings in the studies in this review support a causal association, including large IRRs and excess risks compared with controls, highly significant clustering effects showing onset soon after vaccine receipt, 40 47 and higher risk for younger males as seen with other causative agents of myocarditis or pericarditis. Further, an immune-mediated mechanism is suspected, given the much higher incidence of myocarditis after the second compared with first dose of mRNA vaccine. 40 45 47 49-51 The key messages from the patient/parent perspective, co-developed with our patient partners, include: . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint  A risk for myocarditis after COVID-19 vaccination seems to exist for young males (<29y) although is likely very small and occurrences appear to be quite mild with full recovery.  Clear and effective communication of the risks (rates of myocarditis and likely clinical course), benefits from vaccination, and the availability of good alternatives will be critical for young males and their parents. Because many reports used overlapping populations and reported findings based on different methods of case ascertainment (e.g., risk interval, whether cases were verified) a quantitative synthesis was not undertaken and some of the descriptive summary statements may not fully account for this. We also avoided making any conclusions about any one possible estimate of average incidence and instead relied on ranges. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint Policy and decision making about vaccination for adolescent and young adult males will need to weigh the possibility of myocarditis with various factors such as the i) societal benefits from preventing COVID-19 transmission, ii) individual, age-relevant benefits from prevention or mitigating severe COVID-19 related illness and iii) availability and efficacy of the non-mRNA vaccines. Although the short-term course of myocarditis after an mRNA vaccine is likely mild and self-limiting in the majority of cases, the potential for long-term sequelae such as recurrent disease and/or heart failure are not known. Continued active surveillance of myocarditis/myopericarditis incidence out to 30 days from dosing is recommended with respect to i) new populations (i.e., vaccinated children <12y), ii) the impact of 3rd and subsequent doses, and iii) affected individuals receiving subsequent mRNA vaccine doses. Future research is also needed for determining other risk factors for myocarditis after vaccination apart from age and sex. Contributors: JP, LH, AM and IP designed the study. JP, LH, LB, LG, and AW screened citations for inclusion and were involved in data extraction and interpretation. JP, LB, LG and AW were involved is risk of bias assessments. All authors were involved in interpretation of the data. JP wrote the draft manuscript with input from all authors. All authors approved the final version of the manuscript. LH and JP are the guarantors of this manuscript and accept full responsibility for the work and the conduct of the study, had access to the data, and controlled the decision to publish. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. Evidence Network to support Decision-making (COVID-END) at McMaster University and the SPOR Evidence Alliance. The funders provided input on the design of the study, but did not take part in the collection, analysis, or interpretation of data. They reviewed a report generated from the findings but did not make decisions about submission of the article for publication. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this this version posted November 21, 2021. ; https://doi.org/10.1101/2021.11.19.21266605 doi: medRxiv preprint This review was developed through the analysis, interpretation and synthesis of scientific research and/or systematic reviews published in peer-reviewed journals, institutional websites and other distribution channels. This document may not fully reflect all the scientific evidence available at the time this report was prepared. Other relevant scientific findings may have been reported since completion of this synthesis report. SPOR Evidence Alliance, COVID-END and the project team at ARCHE make no warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, data, product, or process disclosed in this report. Conclusions drawn from, or actions undertaken on the basis of, information included in this report are the sole responsibility of the user. Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare support from the funders for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. Ethics approval: This research did not involve human research participants and thus did not require ethics approval. The lead authors of this work, JP and LH, affirm that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as originally planned in the protocol have been explained. Data sharing: All of the data extracted for this review are included in the manuscript and associated supplementary files. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 21, 2021. ; Explanations for GRADE: a Rated down for indirectness of findings to entire population, based on large differences in estimates in analyses for males across age groups indicating one estimate (or even a range of estimates) for all ages (for both sexes or males) is not credible. b Rated down for risk of bias (lack of case confirmation and passive surveillance) and indirectness for expectation of differences between sexes. c Rated up for large magnitude, highly unlikely to be seen by chance and credible to be higher than for other age categories. 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