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  Real-time benefit-risk assessment of vaccine exposure across a nationally representative primary care sentinel network: cutting edge technologies to prevent disease


   Division of Medical Sciences

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  Prof S de Lusignan, Prof R Hobbs, Dr M Joy  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Commercial partner: EMIS Group, Leeds - https://www.emisgroupplc.com/

Despite good evidence about safety and effectiveness, vaccine ‘hesitancy’ of refusal is a contemporary problem acknowledged by both WHO and European Centre for Disease Control.

Currently there are few robust comparisons of individual brands or types of influenza vaccine, and a range of different vaccines will be introduced for coronavirus 2019 disease (COVID-19) in the coming season.

The national community surveillance system for influenza and other respiratory infections, the Oxford-Royal College of General Practitioners Research and Surveillance Centre, has expanded to >1,700 general practices (N>15,000,000). Its data are linked to hospital, death, and Public Health England’s virology databases. It extracts pseudonymised data from practice records twice weekly.

We have developed with EMIS, the UK’s largest computerised medical record system (CMR) suppliers, a daily data extract, and a collaboration to be able to collect questionnaire data directly from patients through the EMIS “Patient Access” app. This is widely used by patients to request prescriptions, book appointments and look at results, for example 67,000 people in Oxfordshire are registered to use this app with 10 million users nationally (2.4 million prescriptions ordered monthly). We will use this app to enable patients to report contemporaneously about any adverse events of interest (AEIs) or if they have a vaccine preventable disease, post administration.

Aim
To develop and evaluate a real-time vaccine benefit-risk (VB-R) platform that includes direct contributions from patients, linked to their medical records.

Method
We will use of conventional test-negative case-control (TNCC) and cohort studies to measure vaccine effectiveness and use self-controlled case series (SCCS) to report AEIs. Whilst patient questionnaires, have had a high take up, they lack the immediacy of online reporting.

The novel in our study will be recruiting a representative sample of patients attending for vaccination to report AEIs, in the short term (7 days post-vaccination), medium term (3 months), or long term (one year).

References

de Lusignan S, Jones N, Dorward J, et al. The Oxford Royal College of General Practitioners Clinical Informatics Digital Hub: Protocol to Develop Extended COVID-19 Surveillance and Trial Platforms. JMIR Public Health Surveill. 2020;6(3):e19773. Published 2020 Jul 2. doi:10.2196/19773
Pebody RG, Warburton F, Andrews N, et al. Uptake and effectiveness of influenza vaccine in those aged 65 years and older in the United Kingdom, influenza seasons 2010/11 to 2016/17. Euro Surveill. 2018;23(39):1800092. doi:10.2807/1560-7917.ES.2018.23.39.1800092
Cross JW, Joy M, McGee C, Akinyemi O, Gatenby P, de Lusignan S. Adverse events of interest vary by influenza vaccine type and brand: Sentinel network study of eight seasons (2010-2018). Vaccine. 2020;3822):3869-3880. doi:10.1016/j.vaccine.2020.03.034
de Lusignan S, Damaso S, Ferreira F, et al. Brand-specific enhanced safety surveillance of GSK's Fluarix Tetra seasonal influenza vaccine in England: 2017/2018 season [published online ahead of print, 2020 Mar 2]. Hum Vaccine Immunother. 2020;1-10. doi:10.1080/21645515.2019.1705112

 About the Project