The Durability of immune Responses to vaccination against SARS-CoV-2 and its Variants.

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This proposal has been developed by a team who have worked at the forefront of studies to understand immunity to the SARS-COV-2 virus throughout the pandemic. With time, the focus of these questions has changed. As more people receive COVID-19 vaccination, a key concern becomes the need to understand the details of protective immunity and how long it is typically likely to remain protective in the 'real-life settings' of the many different vaccines available globally. Furthermore, compared to the reductionist conditions under which initial clinical trials were conducted, we now face a situation whereby many people receiving vaccines having been previously infected by SARS-CoV-2 or its alpha to delta variants. We showed that prior infection substantially boosts the response to vaccination. These points in mind, our aim is to generate the detailed immunological datasets enabling us to understand how long protective immunity lasts and thus, when boosts are likely to be needed. To do this, we bring together our work on diverse, longitudinal, COVID-19 cohorts, already developed and characterised with our collaborators over the past year. Our cohorts encompass 12097 individuals, with different exposures to SARS-CoV-2 and its variants, in the UK, South Africa and Brazil. We will be able to study people receiving different vaccines, with or without infection by SARS-CoV-2 and the alpha, beta, gamma and delta variants of concern. Our work aims to understand the durability and nature of immune protection, including susceptibility to reinfection and breakthrough infections. To track longitudinal immunity we will use existing protocols to measure diverse aspects of immunity in sequential blood samples. Tests will consider virus neutralisation by antibody, as well as assessing 'immune memory' (-ability of a primed immune response to 'remember' the virus and so protect) in B cells (which make antibody) and T cells (which orchestrate the antiviral response). Put simply, our question can be framed as: some studies indicate that protective antibodies in serum wane rapidly, so that relatively frequent boosters may be needed, while others show that immunity progressively improves after vaccination, termed 'affinity maturation', and that B and T cell memory are long-lived, implying the possibility of longer delays to boosting. By building a detailed, longitudinal dataset of many measures of immunity, we will model the timecourse from vaccination to the predicted loss of protective immunity. This will enable us to offer precise input to policy-making about immune-monitoring and boosting strategy, as well as informing the realities of applying 'immune certification' measures in everyday life - assessing how long certification is likely to be meaningful. Analysis needs to be mindful of the point that people are diverse. We know that vaccination responses encompass a spectrum, with high-responders and poor-responders at each end. We will analyse data from our large sample in the context of factors such as gender, ethnicity, age and obesity. From past studies, some will make a sub-optimal immune response because of the medicines they are taking. We here include two such cohorts. In one, we consider the impact of one of the most common drugs given to people with autoimmune conditions such as inflammatory bowel disease and rheumatoid arthritis (anti-TNF biologics). In another, we consider the impact of drug treatment in people with chronic myelogenous leukaemia. In summary, the knowledge-gap we aim to fill is the definition of protective immunity and its stability in longitudinal analysis during the year following vaccination. This will supply the dataset and predictive models to inform decision-making on timing of boosters, variant breakthrough, diversity of protective responses within the population and optimisation of protocols for the immunosuppressed.