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1.
Euro Surveill ; 28(3)2023 01.
Article in English | MEDLINE | ID: covidwho-2215127

ABSTRACT

BackgroundPost-authorisation vaccine safety surveillance is well established for reporting common adverse events of interest (AEIs) following influenza vaccines, but not for COVID-19 vaccines.AimTo estimate the incidence of AEIs presenting to primary care following COVID-19 vaccination in England, and report safety profile differences between vaccine brands.MethodsWe used a self-controlled case series design to estimate relative incidence (RI) of AEIs reported to the national sentinel network, the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub. We compared AEIs (overall and by clinical category) 7 days pre- and post-vaccination to background levels between 1 October 2020 and 12 September 2021.ResultsWithin 7,952,861 records, 781,200 individuals (9.82%) presented to general practice with 1,482,273 AEIs, 4.85% within 7 days post-vaccination. Overall, medically attended AEIs decreased post-vaccination against background levels. There was a 3-7% decrease in incidence within 7 days after both doses of Comirnaty (RI: 0.93; 95% CI: 0.91-0.94 and RI: 0.96; 95% CI: 0.94-0.98, respectively) and Vaxzevria (RI: 0.97; 95% CI: 0.95-0.98). A 20% increase was observed after one dose of Spikevax (RI: 1.20; 95% CI: 1.00-1.44). Fewer AEIs were reported as age increased. Types of AEIs, e.g. increased neurological and psychiatric conditions, varied between brands following two doses of Comirnaty (RI: 1.41; 95% CI: 1.28-1.56) and Vaxzevria (RI: 1.07; 95% CI: 0.97-1.78).ConclusionCOVID-19 vaccines are associated with a small decrease in medically attended AEI incidence. Sentinel networks could routinely report common AEI rates, contributing to reporting vaccine safety.


Subject(s)
COVID-19 Vaccines , COVID-19 , Influenza Vaccines , Humans , BNT162 Vaccine , ChAdOx1 nCoV-19 , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , England/epidemiology , Influenza Vaccines/adverse effects , Vaccination/adverse effects
2.
Lancet ; 400(10360): 1305-1320, 2022 10 15.
Article in English | MEDLINE | ID: covidwho-2069811

ABSTRACT

BACKGROUND: Current UK vaccination policy is to offer future COVID-19 booster doses to individuals at high risk of serious illness from COVID-19, but it is still uncertain which groups of the population could benefit most. In response to an urgent request from the UK Joint Committee on Vaccination and Immunisation, we aimed to identify risk factors for severe COVID-19 outcomes (ie, COVID-19-related hospitalisation or death) in individuals who had completed their primary COVID-19 vaccination schedule and had received the first booster vaccine. METHODS: We constructed prospective cohorts across all four UK nations through linkages of primary care, RT-PCR testing, vaccination, hospitalisation, and mortality data on 30 million people. We included individuals who received primary vaccine doses of BNT162b2 (tozinameran; Pfizer-BioNTech) or ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in our initial analyses. We then restricted analyses to those given a BNT162b2 or mRNA-1273 (elasomeran; Moderna) booster and had a severe COVID-19 outcome between Dec 20, 2021, and Feb 28, 2022 (when the omicron (B.1.1.529) variant was dominant). We fitted time-dependent Poisson regression models and calculated adjusted rate ratios (aRRs) and 95% CIs for the associations between risk factors and COVID-19-related hospitalisation or death. We adjusted for a range of potential covariates, including age, sex, comorbidities, and previous SARS-CoV-2 infection. Stratified analyses were conducted by vaccine type. We then did pooled analyses across UK nations using fixed-effect meta-analyses. FINDINGS: Between Dec 8, 2020, and Feb 28, 2022, 16 208 600 individuals completed their primary vaccine schedule and 13 836 390 individuals received a booster dose. Between Dec 20, 2021, and Feb 28, 2022, 59 510 (0·4%) of the primary vaccine group and 26 100 (0·2%) of those who received their booster had severe COVID-19 outcomes. The risk of severe COVID-19 outcomes reduced after receiving the booster (rate change: 8·8 events per 1000 person-years to 7·6 events per 1000 person-years). Older adults (≥80 years vs 18-49 years; aRR 3·60 [95% CI 3·45-3·75]), those with comorbidities (≥5 comorbidities vs none; 9·51 [9·07-9·97]), being male (male vs female; 1·23 [1·20-1·26]), and those with certain underlying health conditions-in particular, individuals receiving immunosuppressants (yes vs no; 5·80 [5·53-6·09])-and those with chronic kidney disease (stage 5 vs no; 3·71 [2·90-4·74]) remained at high risk despite the initial booster. Individuals with a history of COVID-19 infection were at reduced risk (infected ≥9 months before booster dose vs no previous infection; aRR 0·41 [95% CI 0·29-0·58]). INTERPRETATION: Older people, those with multimorbidity, and those with specific underlying health conditions remain at increased risk of COVID-19 hospitalisation and death after the initial vaccine booster and should, therefore, be prioritised for additional boosters, including novel optimised versions, and the increasing array of COVID-19 therapeutics. FUNDING: National Core Studies-Immunity, UK Research and Innovation (Medical Research Council), Health Data Research UK, the Scottish Government, and the University of Edinburgh.


Subject(s)
COVID-19 , Aged , BNT162 Vaccine , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , ChAdOx1 nCoV-19 , England/epidemiology , Female , Humans , Immunization, Secondary , Immunosuppressive Agents , Male , Northern Ireland , Prospective Studies , SARS-CoV-2 , Scotland , Vaccination , Wales/epidemiology
3.
JMIR Form Res ; 6(8): e37821, 2022 Aug 22.
Article in English | MEDLINE | ID: covidwho-1923868

ABSTRACT

BACKGROUND: The Data and Connectivity COVID-19 Vaccines Pharmacovigilance (DaC-VaP) UK-wide collaboration was created to monitor vaccine uptake and effectiveness and provide pharmacovigilance using routine clinical and administrative data. To monitor these, pooled analyses may be needed. However, variation in terminologies present a barrier as England uses the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), while the rest of the United Kingdom uses the Read v2 terminology in primary care. The availability of data sources is not uniform across the United Kingdom. OBJECTIVE: This study aims to use the concept mappings in the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to identify common concepts recorded and to report these in a repeated cross-sectional study. We planned to do this for vaccine coverage and 2 adverse events of interest (AEIs), cerebral venous sinus thrombosis (CVST) and anaphylaxis. We identified concept mappings to SNOMED CT, Read v2, the World Health Organization's International Classification of Disease Tenth Revision (ICD-10) terminology, and the UK Dictionary of Medicines and Devices (dm+d). METHODS: Exposures and outcomes of interest to DaC-VaP for pharmacovigilance studies were selected. Mappings of these variables to different terminologies used across the United Kingdom's devolved nations' health services were identified from the Observational Health Data Sciences and Informatics (OHDSI) Automated Terminology Harmonization, Extraction, and Normalization for Analytics (ATHENA) online browser. Lead analysts from each nation then confirmed or added to the mappings identified. These mappings were then used to report AEIs in a common format. We reported rates for windows of 0-2 and 3-28 days postvaccine every 28 days. RESULTS: We listed the mappings between Read v2, SNOMED CT, ICD-10, and dm+d. For vaccine exposure, we found clear mapping from OMOP to our clinical terminologies, though dm+d had codes not listed by OMOP at the time of searching. We found a list of CVST and anaphylaxis codes. For CVST, we had to use a broader cerebral venous thrombosis conceptual approach to include Read v2. We identified 56 SNOMED CT codes, of which we selected 47 (84%), and 15 Read v2 codes. For anaphylaxis, our refined search identified 60 SNOMED CT codes and 9 Read v2 codes, of which we selected 10 (17%) and 4 (44%), respectively, to include in our repeated cross-sectional studies. CONCLUSIONS: This approach enables the use of mappings to different terminologies within the OMOP CDM without the need to catalogue an entire database. However, Read v2 has less granular concepts than some terminologies, such as SNOMED CT. Additionally, the OMOP CDM cannot compensate for limitations in the clinical coding system. Neither Read v2 nor ICD-10 is sufficiently granular to enable CVST to be specifically flagged. Hence, any pooled analysis will have to be at the less specific level of cerebrovascular venous thrombosis. Overall, the mappings within this CDM are useful, and our method could be used for rapid collaborations where there are only a limited number of concepts to pool.

4.
Br J Psychiatry ; 221(1): 417-424, 2022 07.
Article in English | MEDLINE | ID: covidwho-1731562

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) has disproportionately affected people with mental health conditions. AIMS: We investigated the association between receiving psychotropic drugs, as an indicator of mental health conditions, and COVID-19 vaccine uptake. METHOD: We conducted a cross-sectional analysis of a prospective cohort of the Northern Ireland adult population using national linked primary care registration, vaccination, secondary care and pharmacy dispensing data. Univariable and multivariable logistic regression analyses investigated the association between anxiolytic, antidepressant, antipsychotic, and hypnotic use and COVID-19 vaccination status, accounting for age, gender, deprivation and comorbidities. Receiving any COVID-19 vaccine was the primary outcome. RESULTS: There were 1 433 814 individuals, of whom 1 166 917 received a COVID-19 vaccination. Psychotropic medications were dispensed to 267 049 people. In univariable analysis, people who received any psychotropic medication had greater odds of receiving COVID-19 vaccination: odds ratio (OR) = 1.42 (95% CI 1.41-1.44). However, after adjustment, psychotropic medication use was associated with reduced odds of vaccination (ORadj = 0.90, 95% CI 0.89-0.91). People who received anxiolytics (ORadj = 0.63, 95% CI 0.61-0.65), antipsychotics (ORadj = 0.75, 95% CI 0.73-0.78) and hypnotics (ORadj = 0.90, 95% CI 0.87-0.93) had reduced odds of being vaccinated. Antidepressant use was not associated with vaccination (ORadj = 1.02, 95% CI 1.00-1.03). CONCLUSIONS: We found significantly lower odds of vaccination in people who were receiving treatment with anxiolytic and antipsychotic medications. There is an urgent need for evidence-based, tailored vaccine support for people with mental health conditions.


Subject(s)
Anti-Anxiety Agents , Antipsychotic Agents , COVID-19 , Adult , Anti-Anxiety Agents/therapeutic use , Antidepressive Agents/therapeutic use , Antipsychotic Agents/therapeutic use , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/therapeutic use , Cross-Sectional Studies , Humans , Hypnotics and Sedatives/therapeutic use , Prospective Studies , Psychotropic Drugs/therapeutic use , Vaccination
5.
Vaccine ; 40(8): 1180-1189, 2022 02 16.
Article in English | MEDLINE | ID: covidwho-1621088

ABSTRACT

BACKGROUND: While population estimates suggest high vaccine effectiveness against SARS-CoV-2 infection, the protection for health care workers, who are at higher risk of SARS-CoV-2 exposure, is less understood. METHODS: We conducted a national cohort study of health care workers in Wales (UK) from 7 December 2020 to 30 September 2021. We examined uptake of any COVID-19 vaccine, and the effectiveness of BNT162b2 mRNA (Pfizer-BioNTech) against polymerase chain reaction (PCR) confirmed SARS-CoV-2 infection. We used linked and routinely collected national-scale data within the SAIL Databank. Data were available on 82,959 health care workers in Wales, with exposure extending to 26 weeks after second doses. RESULTS: Overall vaccine uptake was high (90%), with most health care workers receiving theBNT162b2 vaccine (79%). Vaccine uptake differed by age, staff role, socioeconomic status; those aged 50-59 and 60+ years old were 1.6 times more likely to get vaccinated than those aged 16-29. Medical and dental staff, and Allied Health Practitioners were 1.5 and 1.1 times more likely to get vaccinated, compared to nursing and midwifery staff. The effectiveness of the BNT162b2 vaccine was found to be strong and consistent across the characteristics considered; 52% three to six weeks after first dose, 86% from two weeks after second dose, though this declined to 53% from 22 weeks after the second dose. CONCLUSIONS: With some variation in rate of uptake, those who were vaccinated had a reduced risk of PCR-confirmed SARS-CoV-2 infection, compared to those unvaccinated. Second dose has provided stronger protection for longer than first dose but our study is consistent with waning from seven weeks onwards.


Subject(s)
COVID-19 Vaccines , COVID-19 , Adolescent , Adult , BNT162 Vaccine , Cohort Studies , Health Personnel , Humans , Prospective Studies , SARS-CoV-2 , Wales/epidemiology , Young Adult
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