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

Author:

Vasileiou EleftheriaORCID,Shi TingORCID,Kerr Steven,Robertson Chris,Joy Mark,Tsang RubyORCID,McGagh Dylan,Williams John,Hobbs Richard,de Lusignan SimonORCID,Bradley Declan,OReilly Dermot,Murphy Siobhan,Chuter Antony,Beggs Jillian,Ford David,Orton ChrisORCID,Akbari AshleyORCID,Bedston Stuart,Davies Gareth,Griffiths Lucy JORCID,Griffiths Rowena,Lowthian EmilyORCID,Lyons JaneORCID,Lyons Ronan AORCID,North Laura,Perry Malorie,Torabi Fatemeh,Pickett James,McMenamin Jim,McCowan Colin,Agrawal Utkarsh,Wood RachaelORCID,Stock Sarah JaneORCID,Moore Emily,Henery PaulORCID,Simpson Colin R,Sheikh AzizORCID

Abstract

IntroductionThe 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 analysisWe 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 disseminationWe 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.

Funder

UK Research and Innovation

Publisher

BMJ

Subject

General Medicine

Reference77 articles.

1. World Health Organization . Coronavirus disease (COVID-19) outbreak. Available: https://www.who.int/emergencies/diseases/novel-coronavirus-2019

2. World Health Organization . Draft landscape of COVID-19 candidate vaccines. Available: https://www.who.int/publications/m/item/draft-landscape-of-covid-19-candidate-vaccines

3. Regulatory Affairs Professionals Society . COVID-19 vaccine tracker. Available: https://www.raps.org/news-and-articles/news-articles/2020/3/covid-19-vaccine-tracker

4. European Medicines Agency . COVID-19 vaccines: development, evaluation, approval and monitoring. Available: https://www.ema.europa.eu/en/human-regulatory/overview/public-health-threats/coronavirus-disease-covid-19/treatments-vaccines/covid-19-vaccines-development-evaluation-approval-monitoring

5. National Health Service . Coronavirus (COVID-19) vaccine. Available: https://www.nhs.uk/conditions/coronavirus-covid-19/coronavirus-vaccination/coronavirus-vaccine/

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3