Discrete choice experiment (DCE) to understand variation in uptake of respiratory disease vaccination
Supervisors: Professor Stavros Petrou; Professor Simon de Lusignan; Dr John Buckell
In contrast to older adults (≥65years), working age adults (18-64years) have much lower uptake of respiratory disease vaccines. Whereas influenza vaccination coverage in people over 65 years is always over 70% (Lusignan, 2016), it has been much lower in younger adults; for example, those >50years have had around 55% uptake with even lower rates seen in adult risk groups. Similarly, only 32% of eligible adults, in risk groups, are receiving a pneumococcal polysaccharide vaccine (PPV) (Matthews, 2020). Although much higher rates of COVID-19 vaccination have been achieved (as of 18th July, 93.9% of adults over 50 had received two doses of a COVID-19 vaccination), there are similar age gradients in uptake with younger adults and pregnant women with lower uptake. Encouraging uptake across a range of respiratory diseases, particularly in risk groups, could confer sizeable public health gains because rates in these risk groups are low. Understanding choice behaviour around vaccination is critical to this goal.
A discrete choice experiment (DCE) to understand what influences vaccine uptake in eligible, older, working age adults (50 to 64) compared to age groups in which vaccination rates are higher (over 70). We will focus on vaccines for: pneumococcal infections, influenza and COVID-19.
Understanding the drivers of respiratory vaccine uptake:
Knowing what governs vaccine decisions across a range of respiratory decisions is of value for both GPs encouraging patients to be vaccinated and for public health bodies seeking to increase uptake. Our approach will uncover the relative influence of vaccine-specific features (e.g. effectiveness) and individual-specific psychological features (e.g. knowledge of diseases) on uptake.
Understanding respiratory vaccine uptake for different diseases:
Observing how vaccination behaviours vary across different diseases, and diseases at different stages (e.g. booster shots for COVID-19 versus prevention against seasonal influenza) can offer rich, actionable insights for preventive behaviours.
Vaccine uptake among the general population and at-risk groups:
Sampling at the general population level offers response to low uptake for vaccination at the population level, e.g. influenza vaccines for working age adults. Specific sampling in at-risk groups addresses specific public health priorities, e.g. PPV vaccination for at-risk groups.
Clinical Informatics; Health Economics
Who should apply?
This project will best suit someone with some experience or training in health economics, medical statistics, or quantitative social sciences. Those with an interest in the topic area and a quantitative background are encouraged to apply. The project will provide training in experimental design, choice modelling, and analysis of routinely collected medical records.