Using data to improve public health: COVID-19 secondment

Events following SARS-CoV-2 infection in the era of delta - Technical Summary Aim: The aim of this project is to understand the risk of adverse health events following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the era of delta among the fully vaccinated and the electively unvaccinated. Research Questions: 1. Among vaccinated individuals in the era of the delta variant of SARS-CoV-2, are there higher rates of an incident outcome in those with and without SARS-CoV-2 infection, before and after adjustment for potential confounders? 2. Among electively unvaccinated individuals (individuals eligible for vaccination that have chosen not to receive it) in the era of the delta variant of SARS-CoV-2, are there higher rates of an incident outcome in those with and without SARS-CoV-2 infection, before and after adjustment for potential confounders? Methods: This research will be conducted using the OpenSafely electronic health records data source, with a start date of 01-06-2021 (when delta was thought to be ubiquitous) and end date corresponding to date of most recent data collection. Individual follow-up will end at the earliest date of outcome event, death, or study end date. Exposure to SARS-COV-2 infection will be defined as the first date of a confirmed COVID event after index date. Each outcome will be defined as the first event occurring within the follow-up period, the events of interest are; Acute myocardial infarction, Ischaemic stroke, Pulmonary embolism, Deep vein thrombosis, Transient ischaemic attack, Subarachnoid haemorrhage and haemorrhagic stroke, Heart failure, Angina, Arterial thrombosis events, and Venous thromboembolism events. Cox regression models with a calendar time scale will be fitted to ensure analyses account for changes with calendar time in rates of the outcome event. Hazard ratios will be estimated for events of different types before and after exposure, and by time since exposure. Results will be adjusted for potential confounders including Sex, Age, Ethnicity, Deprivation, Region, Consultation rate, Number of regular medications, Smoking status, Obesity, previous events, Combined oral contraceptive pill, and Hormone replacement therapy.