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We examine the use of fixed-effects and random-effects moment-based meta-analytic methods for analysis of binary adverse-event data. Special attention is paid to the case of rare adverse events that are commonly encountered in routine practice. We study estimation of model parameters and between-study heterogeneity. In addition, we examine traditional approaches to hypothesis testing of the average treatment effect and detection of the heterogeneity of treatment effect across studies. We derive three new methods, a simple (unweighted) average treatment effect estimator, a new heterogeneity estimator, and a parametric bootstrapping test for heterogeneity. We then study the statistical properties of both the traditional and the new methods via simulation. We find that in general, moment-based estimators of combined treatment effects and heterogeneity are biased and the degree of bias is proportional to the rarity of the event under study. The new methods eliminate much, but not all, of this bias. The various estimators and hypothesis testing methods are then compared and contrasted using an example dataset on treatment of stable coronary artery disease.

The Coronavirus Disease 2019 (COVID-19) pandemic has had a devastating impact on global health, and has resulted in an unprecedented, international collaborative effort to develop vaccines to control the outbreak, protect human lives, and avoid further social and economic disruption. Mass vaccination campaigns are underway in multiple countries and are expected worldwide once more vaccine becomes available. Some early candidate vaccines use novel platforms, such as mRNA encapsulated in lipid nanoparticles, and relatively new platforms, such as replication-deficient viral vectors. While these new vaccine platforms hold promise, limited safety data in humans are available. Serious health outcomes linked to vaccinations are rare, and some outcomes may occur incidentally in the vaccinated population. Knowledge of background incidence rates of these medical conditions is a critical component of vaccine safety monitoring to aid in the assessment of adverse events temporally associated with vaccination and to put these events into context with what would be expected due to chance alone. A list of 22 potential adverse events of special interest (AESI), including neurologic, autoimmune, and cardiovascular disorders, was compiled by subject matter experts at the U.S. Food and Drug Administration and the Centers for Disease Control and Prevention. The most recently available U.S. background rates for these medical conditions, overall and by age, sex, and race/ethnicity (when available), were sourced from reported statistics (data published by medical panels/ associations or federal government reports), and literature reviews in PubMed. This review provides estimates of background incidence rates for medical conditions that may be monitored or studied as AESI during safety surveillance and research for COVID-19 vaccines and other new vaccines.

Beginning in December of 2019, a novel coronavirus, SARS-CoV-2, emerged in China and is now a global pandemic with extensive morbidity and mortality. With the emergence of this threat, an unprecedented effort to develop vaccines against this virus began. As vaccines are now being introduced globally, we face the prospect of millions of people being vaccinated with multiple types of vaccines many of which use new vaccine platforms. Since medical events happen without vaccines, it will be important to know at what rate events occur in the background so that when adverse events are identified one has a frame of reference with which to compare the rates of these events so as to make an initial assessment as to whether there is a potential safety concern or not. Background rates vary over time, by geography, by sex, socioeconomic status and by age group. Here we describe two key steps for post-introduction safety evaluation of COVID-19 vaccines: Defining a dynamic list of Adverse Events of Special Interest (AESI) and establishing background rates for these AESI. We use multiple examples to illustrate use of rates and caveats for their use. In addition we discuss tools available from the Brighton Collaboration that facilitate case evaluation and understanding of AESI.

•We generated background incidence rates for 41 AESIs across a network of 10 European healthcare databases, which included a population of 63 million individuals.•We highlighted the importance of the nature of the event and the setting in which it is diagnosed, which should be captured by the data banks that are used to calculate rates, otherwise underestimation is likely.•The background incidence rates are used to monitor the safety of COVID-19 vaccines by the EMA, national health authorities and vaccine manufacturers. In May 2020, the ACCESS (The vACCine covid-19 monitoring readinESS) project was launched to prepare real-world monitoring of COVID-19 vaccines. Within this project, this study aimed to generate background incidence rates of 41 adverse events of special interest (AESI) to contextualize potential safety signals detected following administration of COVID-19 vaccines. A dynamic cohort study was conducted using a distributed data network of 10 healthcare databases from 7 European countries (Italy, Spain, Denmark, The Netherlands, Germany, France and United Kingdom) over the period 2017 to 2020. A common protocol (EUPAS37273), common data model, and common analytics programs were applied for syntactic, semantic and analytical harmonization. Incidence rates (IR) for each AESI and each database were calculated by age and sex by dividing the number of incident cases by the total person-time at risk. Age-standardized rates were pooled using random effect models according to the provenance of the events. A total number of 63,456,074 individuals were included in the study, contributing to 211.7 million person-years. A clear age pattern was observed for most AESIs, rates also varied by provenance of disease diagnosis (primary care, specialist care). Thrombosis with thrombocytopenia rates were extremely low ranging from 0.06 to 4.53/100,000 person-years for cerebral venous sinus thrombosis (CVST) with thrombocytopenia (TP) and mixed venous and arterial thrombosis with TP, respectively. Given the nature of the AESIs and the setting (general practitioners or hospital-based databases or both), background rates from databases that show the highest level of completeness (primary care and specialist care) should be preferred, others can be used for sensitivity. The study was designed to ensure representativeness to the European population and generalizability of the background incidence rates. The project has received support from the European Medicines Agency under the Framework service contract nr EMA/2018/28/PE.

The Global COVID Vaccine Safety (GCoVS) project was established in 2021 under the multinational Global Vaccine Data Network (GVDN) consortium to facilitate the rapid assessment of the safety of newly introduced vaccines. This study analyzed data from GVDN member sites on the background incidence rates of conditions designated as adverse events of special interest (AESI) for COVID-19 vaccine safety monitoring. Eleven GVDN global sites obtained data from national or regional healthcare databases using standardized methods. Incident events of 13 pre-defined AESI were included for a pre-pandemic period (2015–19) and the first pandemic year (2020). Background incidence rates (IR) and 95% confidence intervals (CI) were calculated for inpatient and emergency department encounters, stratified by age and sex, and compared between pre-pandemic and pandemic periods using incidence rate ratios. An estimated 197 million people contributed 1,189,652,926 person-years of follow-up time. Among inpatients in the pre-pandemic period (2015–19), generalized seizures were the most common neurological AESI (IR ranged from 22.15 [95% CI 19.01–25.65] to 278.82 [278.20–279.44] per 100,000 person-years); acute disseminated encephalomyelitis was the least common (<0.5 per 100,000 person-years at most sites). Pulmonary embolism was the most common thrombotic event (IR 45.34 [95% CI 44.85–45.84] to 93.77 [95% CI 93.46–94.08] per 100,000 person-years). The IR of myocarditis ranged from 1.60 [(95% CI 1.45–1.76) to 7.76 (95% CI 7.46–8.08) per 100,000 person-years. The IR of several AESI varied by site, healthcare setting, age and sex. The IR of some AESI were notably different in 2020 compared to 2015–19. Background incidence of AESIs exhibited some variability across study sites and between pre-pandemic and pandemic periods. These findings will contribute to global vaccine safety surveillance and research.

•Assessed background incidence rate of 17 AESI in 6 administrative claims databases.•Background rates varied by database and demographic characteristics.•Rates of most AESI increased with age and were higher among males.•AMI (Medicare) and anaphylaxis (all databases) rates showed seasonality.•AESI rates fluctuated in 2020, but most returned to 2019 levels after May 2020. The U.S. Food and Drug Administration (FDA) Biologics Effectiveness and Safety (BEST) Initiative conducts active surveillance of adverse events of special interest (AESI) after COVID-19 vaccination. Historical incidence rates (IRs) of AESI are comparators to evaluate safety. We estimated IRs of 17 AESI in six administrative claims databases from January 1, 2019, to December 11, 2020: Medicare claims for adults ≥ 65 years and commercial claims (Blue Health Intelligence®, CVS Health, HealthCore Integrated Research Database, IBM® MarketScan® Commercial Database, Optum pre-adjudicated claims) for adults < 65 years. IRs were estimated by sex, age, race/ethnicity (Medicare), and nursing home residency (Medicare) in 2019 and for specific periods in 2020. The study included >100 million enrollees annually. In 2019, rates of most AESI increased with age. However, compared with commercially insured adults, Medicare enrollees had lower IRs of anaphylaxis (11 vs 12–19 per 100,000 person-years), appendicitis (80 vs 117–155), and narcolepsy (38 vs 41–53). Rates were higher in males than females for most AESI across databases and varied by race/ethnicity and nursing home status (Medicare). Acute myocardial infarction (Medicare) and anaphylaxis (all databases) IRs varied by season. IRs of most AESI were lower during March–May 2020 compared with March–May 2019 but returned to pre-pandemic levels after May 2020. However, rates of Bell’s palsy, Guillain-Barré syndrome, narcolepsy, and hemorrhagic/non-hemorrhagic stroke remained lower in multiple databases after May 2020, whereas some AESI (e.g., disseminated intravascular coagulation) exhibited higher rates after May 2020 compared with 2019. AESI background rates varied by database and demographics and fluctuated in March–December 2020, but most returned to pre-pandemic levels after May 2020. It is critical to standardize demographics and consider seasonal and other trends when comparing historical rates with post-vaccination AESI rates in the same database to evaluate COVID-19 vaccine safety.

► We identified 2608 narcolepsy cases in 6 EU countries between 2000 and 2010. ► After pandemic vaccination, incidence rates increased in Finland, Sweden and Denmark. ► In Denmark, the increase did not follow high pandemic vaccination coverage. ► In Italy, the Netherlands and the United Kingdom no increased rates were seen. In August 2010 reports of a possible association between exposure to AS03 adjuvanted pandemic A(H1N1)pdm09 vaccine and occurrence of narcolepsy in children and adolescents emerged in Sweden and Finland. In response to this signal, the background rates of narcolepsy in Europe were assessed to rapidly provide information for signal verification. We used a dynamic retrospective cohort study to assess the narcolepsy diagnosis rates during the period 2000–2010 using large linked automated health care databases in six countries: Denmark, Finland, Italy, the Netherlands, Sweden and the United Kingdom. Overall, 2608 narcolepsy cases were identified in almost 280 million person years (PY) of follow up. The pooled incidence rate was 0.93 (95% CI: 0. 90–0.97) per 100,000 PY. There were peaks between 15 and 30 year of age (women>men) and around 60 years of age. In the age group 5–19 years olds rates were increased after the start of pandemic vaccination compared to the period before the start of campaigns, with rate ratios (RR) of 1.9 (95% CI: 1.1–3.1) in Denmark, 6.4 (95% CI: 4.2–9.7) in Finland and 7.5 (95% CI: 5.2–10.7) in Sweden. Cases verification in the Netherlands had a significant effect on the pattern of incidence over time. The results of this incidence study provided useful information for signal verification on a population level. The safety signal of increased narcolepsy diagnoses following the start of the pandemic vaccination campaign as observed in Sweden and Finland could be observed with this approach. An increase in narcolepsy diagnoses was not observed in other countries, where vaccination coverage was low in the affected age group, or did not follow influenza A(H1N1)pdm09 vaccination. Patient level analyses in these countries are being conducted to verify the signal in more detail.

•Background rates of maternal foetal and neonatal adverse events in South Africa have been assessed to support safety assessment of vaccines.•Retrospective review of paper-based medical records is challenging and time-consuming.•Missing data hampered alignment between clinically-reported adverse events and adverse events confirmed with GAIA case definitions.•Brighton Collaboration GAIA case definitions are useful, but some require amendments to improve utilization in real world settings. Background epidemiologic population data from low- and middle-income countries (LMIC), on maternal, foetal and neonatal adverse outcomes are limited. We aimed to estimate the incidence of maternal, foetal and neonatal adverse outcomes at South African maternal vaccine trial sites as reported directly in the clinical notes as well as using the ‘Global Alignment of Immunization Safety Assessment in Pregnancy’ case definitions (GAIA-CDs). GAIA-CDs were utilized as a tool to standardise data collection and outcome assessment, and the applicability and utility of the GAIA-CDs was evaluated in a LMIC observational study. We conducted a retrospective record review of maternity and neonatal case records for births that occurred in Soweto, Inner City- Johannesburg and Metro-East Cape Town, South Africa, between 1st July 2017 and 30th June 2018. Study staff abstracted data from randomly selected medical charts onto standardized study-specific forms. Incidence (per 100,000 population) was calculated for adverse maternal, foetal and neonatal outcomes, which were identified as priority outcomes in vaccine safety studies by the Brighton Collaboration and World Health Organization. Outcomes reported directly in the clinical notes and outcomes which fulfilled GAIA-CDs were compared. Incidence of outcomes was calculated by combining cases which were either reported in clinical notes by attending physicians and/ or fulfilled GAIA-CDs. Of 9371 pregnant women enrolled, 27·6% were HIV-infected, 19·9% attended antenatal clinic in the 1st trimester of pregnancy and 55·3% had ≥1 ultrasound examination. Fourteen percent of women had hypertensive disease of pregnancy, 1·3% had gestational diabetes mellitus and 16% experienced preterm labour. There were 150 stillbirths (1·6%), 26·8% of infants were preterm and five percent had microcephaly. Data available in clinical notes for some adverse outcomes, including maternal- & neonatal death, severe pre-eclampsia/ eclampsia, were able to fulfil GAIA-CDs criteria for all of the clinically-reported cases, however, missing data required to fulfil other GAIA-CD criteria (including stillbirth, gestational diabetes mellitus and gestational hypertension) led to poor correlation between clinically-reported adverse outcomes and outcomes fulfilling GAIA-CDs. Challenges were also encountered in accurately ascertaining gestational age. This study contributes to the expanding body of data on background rates of adverse maternal and foetal/ neonatal outcomes in LMICs. Utilization of GAIA-CDs assists with alignment of data, however, some GAIA-CDs require amendment to improve the applicability in LMICs. This study was funded by Pfizer (Inc).

Background incidence rates are critical in pharmacovigilance to facilitate identification of vaccine safety signals. We estimated background incidence rates of 11 adverse events of special interest related to COVID-19 vaccines in Ontario, Canada. We conducted a population-based retrospective observational study using linked health administrative databases for hospitalizations and emergency department visits among Ontario residents. We estimated incidence rates of Bell’s palsy, idiopathic thrombocytopenia, febrile convulsions, acute disseminated encephalomyelitis, myocarditis, pericarditis, Kawasaki disease, Guillain-Barré syndrome, transverse myelitis, acute myocardial infarction, and anaphylaxis during five pre-pandemic years (2015–2019) and 2020. The average annual population was 14 million across all age groups with 51% female. The pre-pandemic mean annual rates per 100,000 population during 2015–2019 were 191 for acute myocardial infarction, 43.9 for idiopathic thrombocytopenia, 28.8 for anaphylaxis, 27.8 for Bell’s palsy, 25.0 for febrile convulsions, 22.8 for acute disseminated encephalomyelitis, 11.3 for myocarditis/pericarditis, 8.7 for pericarditis, 2.9 for myocarditis, 2.0 for Kawasaki disease, 1.9 for Guillain-Barré syndrome, and 1.7 for transverse myelitis. Females had higher rates of acute disseminated encephalomyelitis, transverse myelitis and anaphylaxis while males had higher rates of myocarditis, pericarditis, and Guillain-Barré syndrome. Bell’s palsy, acute disseminated encephalomyelitis, and Guillain-Barré syndrome increased with age. The mean rates of myocarditis and/or pericarditis increased with age up to 79 years; males had higher rates than females: from 12 to 59 years for myocarditis and ≥12 years for pericarditis. Febrile convulsions and Kawasaki disease were predominantly childhood diseases and generally decreased with age. Our estimated background rates will permit estimating numbers of expected events for these conditions and facilitate detection of potential safety signals following COVID-19 vaccination.

•Annual TTS IRs were similar between Jan-Dec 2019 and Jan-Oct 2020.•Common site TTS IRs increased with age and were higher among males.•Unusual site TTS IRs were higher in males than females.•Unusual site TTS IRs increased with age for adults aged 18–64 years.•For adults aged ≥ 65 years, unusual site TTS IRs decreased with age. Increased risk of thrombosis with thrombocytopenia syndrome (TTS) following adenovirus vector-based COVID-19 vaccinations has been identified in passive surveillance systems. TTS incidence rates (IRs) in the United States (U.S.) are needed to contextualize reports following COVID-19 vaccination. We estimated annual and monthly IRs of overall TTS, common site TTS, and unusual site TTS for adults aged 18–64 years in Carelon Research and MarketScan commercial claims (2017–Oct 2020), CVS Health and Optum commercial claims (2019–Oct 2020), and adults aged ≥ 65 years using CMS Medicare claims (2019–Oct 2020); IRs were stratified by age, sex, and race/ethnicity (CMS Medicare). Across data sources, annual IRs for overall TTS were similar between Jan-Dec 2019 and Jan-Oct 2020. Rates were higher in Medicare (IRs: 370.72 and 365.63 per 100,000 person-years for 2019 and 2020, respectively) than commercial data sources (MarketScan IRs: 24.21 and 24.06 per 100,000 person-years; Optum IRs: 32.60 and 31.29 per 100,000 person-years; Carelon Research IRs: 24.46 and 26.16 per 100,000 person-years; CVS Health IRs: 30.31 and 30.25 per 100,000 person-years). Across years and databases, common site TTS IRs increased with age and were higher among males. Among adults aged ≥ 65 years, the common site TTS IR was highest among non-Hispanic black adults. Annual unusual site TTS IRs ranged between 2.02 and 3.04 (commercial) and 12.49 (Medicare) per 100,000 person-years for Jan-Dec 2019; IRs ranged between 1.53 and 2.67 (commercial) and 11.57 (Medicare) per 100,000 person-years for Jan-Oct 2020. Unusual site TTS IRs were higher in males and increased with age in commercial data sources; among adults aged ≥ 65 years, IRs decreased with age and were highest among non-Hispanic American Indian/Alaska native adults. TTS IRs were generally similar across years, higher for males, and increased with age. These rates may contribute to surveillance of post-vaccination TTS.