Investigating the uptake, effectiveness and safety of COVID-19 vaccines: protocol for an observational study using linked UK national data

Eleftheria Vasileiou, Ting Shi, Steven Kerr, Chris Robertson, Mark Joy, Ruby Tsang, Dylan McGagh, John Williams, Richard Hobbs, Simon de Lusignan, Declan Bradley, Dermot OReilly, Siobhan Murphy, Antony Chuter, Jillian Beggs, David Ford, Chris Orton, Ashley Akbari, Stuart Bedston, Gareth DaviesLucy J Griffiths, Rowena Griffiths, Emily Lowthian, Jane Lyons, Ronan A Lyons, Laura North, Malorie Perry, Fatemeh Torabi, James Pickett, Jim McMenamin, Colin McCowan, Utkarsh Agrawal, Rachael Wood, Sarah Jane Stock, Emily Moore, Paul Henery, Colin R Simpson, Aziz Sheikh

Research output: Contribution to journalArticlepeer-review

3 Downloads (Pure)

Abstract

Introduction: The novel coronavirus SARS-CoV-2, which emerged in December 2019, has caused millions of deaths and severe illness worldwide. Numerous vaccines are currently under development of which a few have now been authorised for population-level administration by several countries. As of 20 September 2021, over 48 million people have received their first vaccine dose and over 44 million people have received their second vaccine dose across the UK. We aim to assess the uptake rates, effectiveness, and safety of all currently approved COVID-19 vaccines in the UK. Methods and analysis: We will use prospective cohort study designs to assess vaccine uptake, effectiveness and safety against clinical outcomes and deaths. Test-negative case–control study design will be used to assess vaccine effectiveness (VE) against laboratory confirmed SARS-CoV-2 infection. Self-controlled case series and retrospective cohort study designs will be carried out to assess vaccine safety against mild-to-moderate and severe adverse events, respectively. Individual-level pseudonymised data from primary care, secondary care, laboratory test and death records will be linked and analysed in secure research environments in each UK nation. Univariate and multivariate logistic regression models will be carried out to estimate vaccine uptake levels in relation to various population characteristics. VE estimates against laboratory confirmed SARS-CoV-2 infection will be generated using a generalised additive logistic model. Time-dependent Cox models will be used to estimate the VE against clinical outcomes and deaths. The safety of the vaccines will be assessed using logistic regression models with an offset for the length of the risk period. Where possible, data will be meta-analysed across the UK nations. Ethics and dissemination: We obtained approvals from the National Research Ethics Service Committee, Southeast Scotland 02 (12/SS/0201), the Secure Anonymised Information Linkage independent Information Governance Review Panel project number 0911. Concerning English data, University of Oxford is compliant with the General Data Protection Regulation and the National Health Service (NHS) Digital Data Security and Protection Policy. This is an approved study (Integrated Research Application ID 301740, Health Research Authority (HRA) Research Ethics Committee 21/HRA/2786). The Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub meets NHS Digital's Data Security and Protection Toolkit requirements. In Northern Ireland, the project was approved by the Honest Broker Governance Board, project number 0064. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journals.
Original languageEnglish
Article numbere050062
Number of pages12
JournalBMJ open
Volume12
Issue number2
Early online date14 Feb 2022
DOIs
Publication statusPublished - 14 Feb 2022

Keywords

  • epidemiology
  • public health
  • respiratory infections
  • COVID-19

Fingerprint

Dive into the research topics of 'Investigating the uptake, effectiveness and safety of COVID-19 vaccines: protocol for an observational study using linked UK national data'. Together they form a unique fingerprint.

Cite this