PhD-position in European monitoring of myocarditis cases in COVID -19 vaccination

For this project we are looking for an ambitious candidate who has a MSc in a relevant discipline (biomedical sciences, data science, (pharmaco)epidemiology or similar) and is interested in European monitoring of myocarditis cases in COVID -19 vaccination with observational research, common data model, machine learning and using data from daily clinical practice and existing European registries.

Our healthcare system has entered a new era as a result of the digitalisation of healthcare information, in which ever-increasing amounts of clinical and registry data are collected, stored, mapped, linked and analysed electronically. This data is also called real-world data to indicate that it is clinical data rather than data collected in an experimental/controlled setting. In the past decade, the re-use of this data for research purposes has increased rapidly. Real-world data have therefore also become an integral part of vaccine monitoring research and are essential for studying the risks and benefits of COVID -19 vaccines in to provide insights in their effectives and safety patterns..

An essential component for real-world evidence is data quality, which must be sufficient to support decision-making in daily practice. A causal framework when designing studies with data from daily practice is therefore of great importance. Testing causal relationships in observational data can be used to study the association between medication and clinical outcomes in a wide range of patients in daily practice.

The goal of this study is to characterize the natural history, clinical course, outcomes and risk factors for myocarditis temporally associated with COVID-19 vaccination.

Although most cases of vaccine-associated myocarditis have been described as mild and self-limiting, additional data are needed to characterize the natural history and long-term outcomes of these events and characterize risk factors for both occurrence and severity.