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
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
Patient Level Index of Multiple Deprivation;Rural-Urban Classification