Antimicrobial resistance (AMR) is considered one of the top ten global health threats by the World Health Organisation. AMR reduces the efficacy of antibiotics (drugs that can treat and prevent bacterial infections), meaning that many bacterial infections which might previously have been treatable are now posing life changing or life-threatening complications. Antibiotic prescription (AP) is the strongest driver of AMR development and dissemination.
Influenza is one of the most common viral respiratory infections in the UK. Influenza can cause mild to severe illness, and is composed of two major viral types that have significant impact on human health, A and B, which can be further divided into many constantly evolving types and sub-types. Influenza vaccines can prevent influenza episodes or severity of infection, and are given annually to overcome year-by-year variation in influenza A or B type prevalence and evolution. Influenza vaccination is widespread in the UK, primarily targeting over 65s, pre-school children and at-risk adults.
Respiratory infections represent the most common reason for AP, and it is recognised that bacterial infections secondary to influenza infection commonly prompt AP. It would therefore seem possible that influenza vaccination might be associated with reduced risk of AP, though evidence that widescale vaccination can reduce AP is currently limited. This project will explore associations between influenza vaccination and AP likelihood and frequency in the commonly vaccinated proportion of the UK population. Findings might suggest a route towards reducing AMR risk, and could support wider deployment of the influenza vaccination amongst the broader population.
Aim: To assess antibiotic prescription (AP) in adults over 60 years of age, at-risk groups under 65 years of age and children according to influenza vaccination status.
Objectives:
To assess whether AP varies in (i) adults over 60 years of age, (ii) at-risk groups under 65 years of age, and (iii) children 0-11 years of age, by presence of influenza vaccination, using:
1. A self-controlled case series (populations i, ii and iii)
2. A cohort analysis (i, ii and iii)
3. An interrupted time series and change-point approach (i and iii)
These will be compared to suggest most effective strategies for future vaccine effectiveness assessments.
Population: Adults over 60 years of age, at-risk groups under 65 years of age, and children aged 0-11 years, between 1 January 2005 and 31 December 2019.
Study design: Self-controlled case series, cohort study, or interrupted time series/change-point analysis
Primary exposure: Influenza vaccination
Secondary exposures: Rotavirus or herpes zoster vaccination (for approach validation)
Primary outcome: AP, measured as total annual patient days prescribed, in total and by WHO prioritisation categories for all consultations.
Secondary outcomes: AP associated with acute respiratory infection consultations
Control conditions: AP associated with acute gastroenteritis and urinary tract infection consultations.
Confounders and adjusters: Pneumococcal vaccination, socioeconomic deprivation, ethnicity, geography, GP, comorbidities, care seeking propensity, age, co-morbidities, influenza disease prevalence, vaccination uptake and effectiveness by season, and residual vaccination immunity.
Analysis:
Data will be analysed separately across the three population groups. Primary analyses will comprise a self-controlled case series, comparing AP and influenza vaccination over time via parametric or semi-parametric conditional Poisson regression models and frailty models, balanced against an array of confounders and adjusters. For cohort analyses, multivariable generalised linear models with a Poisson distribution approach will be used; for interrupted time series counterfactual and change-point models will be utilised.
Total antibiotic prescription (AP) for all consultations; AP by WHO classification (i.e., highest priority critically important antibiotics) for all consultations; AP for consultations classified as being for investigation or management of acute respiratory infection; AP for consultations classified as being for investigation or management of acute urinary tract infection; AP for consultations classified as being for investigation or management of acute gastroenteritis; AP by WHO classification for consultations classified as being for investigation or management of acute respiratory, urinary tract infections or acute gastroenteritis.
Neil French - Chief Investigator - University of Liverpool
David Singleton - Corresponding Applicant - University of Liverpool
Caroline Jeffery - Collaborator - University of Liverpool
Daniel Hungerford - Collaborator - University of Liverpool
Kate Fleming - Collaborator - University of Liverpool
Marc Yves Romain Henrion - Collaborator - Liverpool School of Tropical Medicine
Miren Iturriza-Gomara - Collaborator - Path
Nigel Cunliffe - Collaborator - University of Liverpool
Pieta Schofield - Collaborator - University of Liverpool
Roberto Vivancos - Collaborator - Public Health England
Samantha Kilada - Collaborator - University of Liverpool
Valerie Decraene - Collaborator - Public Health England
Xingna Zhang - Collaborator - University of Liverpool
Patient Level Index of Multiple Deprivation;Rural-Urban Classification