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

Estimating transmission parameters for respiratory syncytial virus and predicting the impact of maternal and pediatric vaccination

Background Respiratory syncytial virus (RSV) is a leading cause of respiratory tract illness in young children and a major cause of hospital admissions globally. Methods Here we fit age-structured transmission models with immunity propagation to data from the Netherlands (2012–2017). Data included nationwide hospitalizations with confirmed RSV, general practitioner (GP) data on attendance for care from acute respiratory infection, and virological testing of acute respiratory infections at the GP. The transmission models, equipped with key parameter estimates, were used to predict the impact of maternal and pediatric vaccination. Results Estimates of the basic reproduction number were generally high (R0 > 10 in scenarios with high statistical support), while susceptibility was estimated to be low in nonelderly adults (<10% in persons 20–64 years) and was higher in older adults (≥65 years). Scenario analyses predicted that maternal vaccination reduces the incidence of infection in vulnerable infants (<1 year) and shifts the age of first infection from infants to young children. Conclusions Pediatric vaccination is expected to reduce the incidence of infection in infants and young children (0–5 years), slightly increase incidence in 5 to 9-year-old children, and have minor indirect benefits

Early warning signs of a mental health tsunami: a coordinated response to gather initial data insights from multiple digital services providers

Introduction: The immediate impact of COVID-19 on morbidity and mortality has raised the need for accurate and real time data monitoring and communication. The aim of this study is to document initial observations from multiple digital services providers during the COVID-19 crisis, especially those related to mental health and wellbeing. Methods: We used email and social media to announce an urgent call for support. Digital mental health services providers (N=46), financial services providers (N=4) and other relevant digital data source providers (N=3) responded with quantitative and/or qualitative data insights. People with lived experience of distress, as service users/consumers, and carers are included as co-authors. Results: This study provides proof-of-concept of the viability for researchers and private companies to work collaboratively towards a common good. Digital services providers reported a diverse range of mental health concerns. A recurring observation is that demand for digital mental health support has risen, and that the nature of this demand has also changed since COVID-19, with an apparent increased presentation of anxiety and loneliness. Conclusion: Following this study, we will continue to work with providers in more in-depth ways to capture follow-up insights at regular time points. We will also onboard new providers to address data representativeness. Looking ahead, we anticipate the need for a rigorous process to interpret insights from an even wider variety of sources in order to monitor and respond to mental health needs