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LEAD SUPERVISOR:  Prof Stavros Petrou, Nuffield Department of Primary Health Care Sciences

Co-supervisors: Prof Simon de Lusignan, Nuffield Department of Primary Health Care Sciences, Dr John Buckell, Nuffield Department of Population Health, Dr Catia Nicodemo, Nuffield Department of Primary Health Care Sciences, Dr Mark Joy, Nuffield Department of Primary Health Care Sciences, and Prof FD Richard Hobbs, Nuffield Department of Primary Health Care Sciences

Commercial partner: EMIS Group PLC, Leeds

 

Background

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.

Aim

A discrete choice experiment (DCE) to understand what influences vaccine uptake in eligible, working age adults (aged 16 to 65 years).  We will focus on vaccines for: pneumococcal infections, influenza and COVID-19.

Methods

Discrete Choice Experiments (DCEs) are an established method in health sciences (Genie, 2020), for understanding the behaviours of vaccine-eligible adults toward vaccine uptake and characteristics that can influence their vaccination decisions.

The design of the DCE will be based on systematic reviews, consultation with clinicians, and secondary data. Recent work has used data from DCEs and extended it in two important ways that will enhance the validity of the findings: (i) in combination with data from the real world to enhance external validity (Buckell and Hess, 2019); (ii) incorporating psychology, e.g. information inattention, into mathematical models of behaviour to better understand choices (Erdem et al., 2014; Buckell and Sindelar, 2019).

Sampling both from the general population and among at-risk groups will enable findings that are applicable at the population level and that respond to specific public health priorities.  

Objectives

(1) Systematic review of respiratory virus vaccine uptake in working age adults;

(2) Study the attitudes/psychology of these three vaccines before and after the introduction of the COVID-19 vaccine and analyse behaviors among vulnerable groups;

(3) Pilot then main experimental work running DCEs through the EMIS Access portal with volunteer patients; sampling from the general population and specific risk groups.

(4) Use DCE data in behavioural models, combined with patient record data, to forecast how features of vaccines (e.g. pharmacy or surgery administration) impact on uptake, and so how GPs can encourage uptake; and

(5) Study the economic impact of respiratory disease vaccination uptake on GP practices. 

MRC priorities:

COVID-19 and other respiratory diseases are key priorities. Understanding vaccination behaviours across a range of respiratory diseases would enable more effective prevention and management. This project will contribute to MRC methodological priorities by combining and advancing the health economic and behavioural science/psychology methodologies, developing generalizable methods for use across MRC research areas.   

 

Benefits for EMIS & academics:

EMIS would strengthen our relationships with practices and patients. EMIS is looking to expand its work with the research community; the proposed research would provide an appropriate case study.

 

Apply using course: DPhil in Primary Health Care

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