COVID-19 vaccine safety in Scotland - background rates of adverse events of special interest.

OBJECTIVES: Mass COVID-19 vaccination commenced in December 2020 in Scotland. Monitoring vaccine safety relies on accurate background incidence rates (IRs) for health outcomes potentially associated with vaccination. This study aimed to quantify IRs in Scotland of adverse events of special interest (AESI) potentially associated with COVID-19 vaccination. STUDY DESIGN AND METHODS: IRs and 95% confidence intervals (CIs) for 36 AESI were calculated retrospectively for the pre-COVID-19 pandemic period (01 January 2015-31 December 2019) and the COVID-19 pandemic period (01 April 2020-30 November 2020), with age-sex stratification, and separately by calendar month and year. Incident cases were determined using International Classification of Diseases-10th Revision (ICD-10)-coded hospitalisations. RESULTS: Prepandemic population-wide IRs ranged from 0.4 (0.3-0.5 CIs) cases per 100,000 person-years (PYRS) for neuromyelitis optica to 478.4 (475.8-481.0 CIs) cases per 100,000 PYRS for acute renal failure. Pandemic population-wide IRs ranged from 0.3 (0.2-0.5 CIs) cases per 100,000 PYRS for Kawasaki disease to 483.4 (473.2-493.7 CIs) cases per 100,000 PYRS for acute coronary syndrome. All AESI IRs varied by age and sex. Ten AESI (acute coronary syndrome, acute myocardial infarction, angina pectoris, heart failure, multiple sclerosis, polyneuropathies and peripheral neuropathies, respiratory failure, rheumatoid arthritis and polyarthritis, seizures and vasculitis) had lower pandemic than prepandemic period IRs overall. Only deep vein thrombosis and pulmonary embolism had a higher pandemic IR. CONCLUSION: Lower pandemic IRs likely resulted from reduced health-seeking behaviours and healthcare provision. Higher IRs may be associated with SARS-CoV-2 infections. AESI IRs will facilitate future vaccine safety studies in Scotland.

Expected Rates of Select Adverse Events After Immunization for Coronavirus Disease 2019 Vaccine Safety Monitoring.

Using meta-analytic methods, we calculated expected rates of 20 potential adverse events of special interest (AESI) that would occur after coronavirus disease 2019 (COVID-19) vaccination within 1-, 7-, and 42-day intervals without causal associations. Based on these expected rates, if 10 000 000 persons are vaccinated, (1) 0.5, 3.7, and 22.5 Guillain-Barre syndrome cases, (2) 0.3, 2.4, and 14.3 myopericarditis cases, (3) and 236.5, 1655.5, and 9932.8 all-cause deaths would occur coincidentally within 1, 7, and 42 days postvaccination, respectively. Expected rates of potential AESI can contextualize events associated temporally with immunization, aid in safety signal detection, guide COVID-19 vaccine health communications, and inform COVID-19 vaccine benefit-risk assessments.

Variation in incidence rates of outcomes relevant to vaccine safety monitoring in a US commercially insured population by case identification algorithm.

BACKGROUND: Large health insurance claims databases can be used to estimate rates of rare safety outcomes. We measured incidence rates of rare outcomes that could be used to contextualize adverse events among people receiving pneumococcal vaccines in clinical trials or clinical practice. However, algorithms used to identify outcomes in administrative databases are subject to error. Using two algorithms for each outcome, we assessed the influence of algorithm choice on the rates of the outcomes. METHODS: We used closed administrative medical and pharmacy claims in the Healthcare Integrated Research DatabaseSM (HIRD) to construct a broad cohort of individuals less than 100 years old (i.e., the target cohort) and a trial-similar cohort of individuals resembling those potentially eligible for a vaccine clinical trial (e.g., for a pneumococcal vaccine). We stratified by age and sex and used specific and sensitive algorithms to estimate rates of 39 outcomes including cardiac/cerebrovascular, metabolic, allergic/autoimmune, neurological, and hematologic outcomes. Specific algorithms intended to reduce false positive errors, while sensitive algorithms intended to reduce false negative errors, thereby providing lower and upper bounds for the "true" rates. RESULTS: We followed approximately 40 million individuals in the target cohort for an average of 3 years. Of 39 outcomes, 14 (36 %) had a rate from the specific algorithm that was less than half the rate from the sensitive algorithm. Rates of cardiac/cerebrovascular outcomes were most consistent (mean ratio of rates from specific algorithms compared to rates from sensitive algorithms = 0.76), while the rates of neurological and hematologic outcomes were the least consistent (mean ratio of rates = 0.33 and 0.36, respectively). CONCLUSIONS: For many cardiac/cerebrovascular outcomes, rates were similar regardless of the algorithm. For other outcomes, rates varied substantially by algorithm. Using multiple algorithms to ascertain outcomes in claims data can be informative about the extent of uncertainty due to outcome misclassification.

Obstetric and neonatal outcomes in South Africa.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: This study was funded by Pfizer (Inc).

Incidence rates of thrombosis with thrombocytopenia syndrome (TTS) among adults in United States commercial and Medicare claims databases, 2017-2020.

BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSION: TTS IRs were generally similar across years, higher for males, and increased with age. These rates may contribute to surveillance of post-vaccination TTS.

Background rates of adverse events of special interest for COVID-19 vaccine safety monitoring in the United States, 2019-2020.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Background incidence rates of selected adverse events of special interest (AESI) to monitor the safety of COVID-19 vaccines.

BACKGROUND: Determining background rates of medical conditions identified as adverse events of special interest (AESI) that may occur following COVID-19 vaccination is important for contextualising and investigating potential vaccine safety signals. METHODS: We conducted a retrospective population-based cohort study using linked emergency department, hospitalisation and death data for 2017 and 2018 from Australia's most populous state, New South Wales. Incident cases of select neurological conditions, arterial or venous thromboembolic conditions, secondary thrombocytopenia, myocarditis/pericarditis, and unique events of anaphylaxis and generalised convulsions were identified using internationally agreed upon diagnostic (ICD-10) codes. State-specific rates per 100,000 person-years were calculated, with further stratification by age group and sex where clinically relevant to the condition, and the number of expected cases nationally in one and 6 weeks was estimated. RESULTS: Background rates of selected neurological conditions were low with the exception of generalised convulsions for which 1,599-1,872 cases were estimated nationally in a 1-week period in the absence of vaccination. Using a narrow case definition, rates of Guillain-Barré Syndrome (3.9 per 100,000 person-years) were higher than international rates reported elsewhere. Thromboembolic and cerebral venous sinus thrombosis event rates increased with age. Myocarditis occurred more commonly in males, and was highest in males aged 18-24 years, with an estimated 1-4 cases expected nationally in a 1-week period. CONCLUSIONS: Using routinely collected linked healthcare data provides localised estimates of background rates of new onset or periodic AESI which enables rapid estimation of observed-versus-expected rates of events reported following COVID-19 vaccination. This Australian-specific analysis contributes AESI background rates which can be compared with those from other countries to enhance understanding of geographic variability in the frequency of specific AESI in the absence of vaccination, and can be utilised for signal detection during program implementation.

Background rates of 41 adverse events of special interest for COVID-19 vaccines in 10 European healthcare databases - an ACCESS cohort study.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: The project has received support from the European Medicines Agency under the Framework service contract nr EMA/2018/28/PE.

Background rates of adverse events of special interest for COVID-19 vaccines: A multinational Global Vaccine Data Network (GVDN) analysis.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Background incidence rates of adverse events of special interest related to COVID-19 vaccines in Ontario, Canada, 2015 to 2020, to inform COVID-19 vaccine safety surveillance.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases.

Objective: Background incidence rates are routinely used in safety studies to evaluate an association of an exposure and outcome. Systematic research on sensitivity of rates to the choice of the study parameters is lacking. Materials and Methods: We used 12 data sources to systematically examine the influence of age, race, sex, database, time-at-risk, season and year, prior observation and clean window on incidence rates using 15 adverse events of special interest for COVID-19 vaccines as an example. For binary comparisons we calculated incidence rate ratios and performed random-effect meta-analysis. Results: We observed a wide variation of background rates that goes well beyond age and database effects previously observed. While rates vary up to a factor of 1,000 across age groups, even after adjusting for age and sex, the study showed residual bias due to the other parameters. Rates were highly influenced by the choice of anchoring (e.g., health visit, vaccination, or arbitrary date) for the time-at-risk start. Anchoring on a healthcare encounter yielded higher incidence comparing to a random date, especially for short time-at-risk. Incidence rates were highly influenced by the choice of the database (varying by up to a factor of 100), clean window choice and time-at-risk duration, and less so by secular or seasonal trends. Conclusion: Comparing background to observed rates requires appropriate adjustment and careful time-at-risk start and duration choice. Results should be interpreted in the context of study parameter choices.

The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety.

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.

U.S. Population-Based background incidence rates of medical conditions for use in safety assessment of COVID-19 vaccines.

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.

Incidence of outcomes relevant to vaccine safety monitoring in a US commercially-insured population.

BACKGROUND: Background incidence rates (IRs) of potential safety outcomes among vaccine eligible individuals can inform assessment of vaccine safety. Vaccine safety surveillance often uses claims databases, but the impact of outcome definitions on background IR estimates is largely unexplored. Using two definitions for each outcome, we estimated background IRs of 32 cardiac, metabolic, allergic, autoimmune, neurologic, hematologic and nephrologic outcomes among individuals eligible to receive pneumococcal vaccination. METHODS: We defined a cohort of individuals aged 6-100 years in US commercial health plans who had ≥12 months of health plan enrollment between January 2007 and August 2014 and no previous record of conjugate or simple polysaccharide pneumococcal vaccination. We developed a sensitive and a specific definition for each outcome, with the specific definition requiring evidence of additional care consistent with the outcome. IRs per 100,000 person-years for each outcome were presented overall and stratified by age, gender, and invasive pneumococcal disease (IPD) risk category. RESULTS: We followed 19.9 million individuals for a median of 2.5 years. Wide variation was seen in IRs across different definitions of the 32 outcomes, with 19 (59%) outcomes having a specific definition IR less than half of the sensitive definition IR. IRs were particularly variable by definition for outcomes categorized as either hematologic/nephrologic or neurologic (mean ratio of specific IR to sensitive IR = 0.26 and 0.30, respectively). Across definitions, the IRs of the 32 outcomes were often highest in females, adults ≥65, and those at higher IPD risk. CONCLUSIONS: Background IRs of safety outcomes relevant to populations indicated for pneumococcal vaccine varied by outcome definitions and population subgroups in this large US commercially-insured population. Given large differences in estimated IRs using sensitive versus specific case definitions, neurologic, and hematologic/nephrologic safety outcomes as compared to allergic and autoimmune outcomes may warrant more refined definitions and medical record validation.