Adverse events of special interest for COVID-19 vaccines - background incidences vary by sex, age and time period and are affected by the pandemic (preprint)

Background With large-scale COVID-19 vaccination implemented world-wide, safety signals needing rapid evaluation will emerge. We report population-based, age- and-sex-specific background incidence rates of conditions representing potential vaccine adverse events of special interest (AESI) for the Swedish general population using register data. Methods We studied an age/sex-stratified random 10% sample of the Swedish population on 1 Jan 2020, followed for AESI outcomes during 1 year, as the COVID-19 pandemic emerged and developed, before the start of vaccinations. We selected and defined the following outcomes based on information from regulatory authorities, large-scale adverse events initiatives and previous studies: aseptic meningitis, febrile seizure, Kawasaki syndrome, MISC, post-infectious arthritis, arthritis, myocarditis, ARDS, myocardial infarction, stroke, ischemic stroke, hemorrhagic stroke, venous thromboembolism, pulmonary embolism, kidney failure, liver failure, erythema multiforme, disseminated intravascular coagulation, autoimmune thyroiditis, and appendicitis. We calculated incidence rates stratified by age, sex and time period (quarters of 2020), and classified them using Council of International Organizations of Medical Sciences (CIOMS) categories: very common, common, uncommon, rare, or very rare. Results We included 972,723 study subjects, representing the Swedish national population on 1 Jan 2020. We found that AESI incidence rates vary greatly by age and in some cases sex. Several common AESIs showed expected increase with age, while some (e.g. appendicitis, aseptic meningitis, autoimmune thyroiditis, Kawasaki syndrome and MISC) were more common in young people, and others exhibited a flatter age pattern (e.g. myocarditis, DIC and erythema multiforme). Consequently, the CIOMS classification for AESIs varied widely according to age. Considerable variability was suggested for some AESI rates across the 4 quarters of 2020, potentially related to pandemic waves, seasonal variation, healthcare system overload or other healthcare delivery effects. Conclusion Age, sex, and timing of rates are important to consider when background AESI rates are compared to corresponding rates observed with COVID-19 vaccines.

Serum-IgG responses to SARS-CoV-2 after mild and severe COVID-19 infection and analysis of IgG non-responders (preprint)

BackgroundTo accurately interpret COVID-19 seroprevalence surveys, knowledge of serum-IgG responses to SARS-CoV-2 with a better understanding of patients who do not seroconvert, is imperative. This study aimed to describe serum-IgG responses to SARS-CoV-2 in a cohort of patients with both severe and mild COVID-19, including extended studies of patients who remained seronegative more than 90 days post symptom onset. ResultsForty-seven patients (mean age 49 years, 38% female) were included. All (15/15) patients with severe symptoms and 29/32 (90.6%) patients with mild symptoms of COVID-19 developed SARS-CoV-2-specific IgG antibodies in serum. Time to seroconversion was significantly shorter (median 11 vs. 22 days, P=0.04) in patients with severe compared to mild symptoms. Of the three patients without detectable IgG-responses after >90 days, all had detectable virus-neutralizing antibodies and in two, spike-protein receptor binding domain-specific IgG was detected with an in-house assay. Antibody titers were preserved during follow-up and all patients who seroconverted, irrespective of the severity of symptoms, still had detectable IgG levels >75 days post symptom onset. ConclusionsPatients with severe COVID-19 both seroconvert earlier and develop higher concentrations of SARS-CoV-2-specific IgG than patients with mild symptoms. Of those patients who not develop detectable IgG antibodies, all have detectable virus-neutralizing antibodies, suggesting immunity. Our results showing that not all COVID-19 patients develop detectable IgG using two validated commercial clinical methods, even over time, are vital for the interpretation of COVID-19 seroprevalence surveys and for estimating the true infection prevalence in populations.