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Vaccines against COVID-19 and influenza can reduce the adverse outcomes caused by infections during pregnancy, but vaccine uptake among pregnant women has been suboptimal. We examined the COVID-19 and influenza vaccine uptake and disparities in pregnant women during the COVID-19 pandemic to inform vaccination interventions. We used data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre database in England and the Secure Anonymised Information Linkage Databank in Wales. The uptake of at least one dose of vaccine was 40.2% for COVID-19 and 41.8% for influenza among eligible pregnant women. We observed disparities in COVID-19 and influenza vaccine uptake, with socioeconomically deprived and ethnic minority groups showing lower vaccination rates. The suboptimal uptake of COVID-19 and influenza vaccines, especially in those from socioeconomically deprived backgrounds and Black, mixed or other ethnic groups, underscores the necessity for interventions to reduce vaccine hesitancy and enhance acceptance in pregnant women.
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Every year, there are ~100,000 hospital admissions for asthma in the UK, many of which are potentially preventable. Evidence suggests that carefully conceptualised and implemented audit and feedback (A&F) cycles have the potential to improve clinical outcomes for those with chronic conditions. We wanted to investigate the technical feasibility of developing a near-real time asthma dashboard to support A&F interventions for asthma management in primary care. We extracted cross-sectional data on asthma from 756 participating GP practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) database in England comprising 7.6 million registered people. Summary indicators for a GP practice were compared to all participating RCGP RSC practices using practice-level data, for the week 6-12th-Mar-2023. A weekly, automated asthma dashboard with features that can support electronic-A&F cycles that compared key asthma indicators for a GP practice to RCGP RSC could be created ( https://tinyurl.com/3ydtrt85 ): 12-weeks-incidence 0.4% vs 0.4%, annual prevalence 6.1% vs 6.7%, inhaled relievers to preventer 1.2 vs 1.1, self-management plan given 83.4% vs 60.8%, annual reviews 36.8% vs 57.3%, prednisolone prescriptions 2.0% vs 3.2%, influenza vaccination 56.6% vs 55.5%, pneumococcal vaccination ever (aged ≥65 years) 90.2% vs 84.1% and current smokers 14.9% vs 14.8%. Across the RCGP RSC, the rate of hospitalisations was 0.024%; comparative data had to be suppressed for the study practice because of small numbers. We have successfully created an automated near real-time asthma dashboard that can be used to support A&F initiatives to improve asthma care and outcomes in primary care.
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Asma , Mejoramiento de la Calidad , Humanos , Asma/terapia , Asma/epidemiología , Inglaterra/epidemiología , Estudios Transversales , Femenino , Masculino , Adulto , Persona de Mediana Edad , Atención Primaria de Salud/estadística & datos numéricos , Anciano , Adolescente , Adulto Joven , Niño , Medicina GeneralRESUMEN
Background: There were substantial reductions in asthma exacerbations during the COVID-19 pandemic for reasons that remain poorly understood. We investigated changes in modifiable risk factors which might help explain the reductions in asthma exacerbations. Methods: Multilevel generalised linear mixed models were fitted to examine changes in modifiable risk factors for asthma exacerbations during 2020-2022, compared to pre-pandemic year (2019), using observational, routine data from general practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre. Asthma exacerbations were defined as any of GP recorded: asthma exacerbations, prescriptions of prednisolone, accident and emergency department attendance or hospitalisation for asthma. Modifiable risk factors of interest were ownership of asthma self-management plan, asthma annual review, inhaled-corticosteroid (ICS) prescriptions, influenza vaccinations and respiratory-tract-infections (RTI). Findings: Compared with 2019 (n = 550,995), in 2020 (n = 565,956) and 2022 (n = 562,167) (p < 0.05): asthma exacerbations declined from 67.1% to 51.9% and 61.1%, the proportion of people who had: asthma exacerbations reduced from 20.4% to 15.1% and 18.5%, asthma self-management plans increased from 28.6% to 37.7% and 55.9%; ICS prescriptions increased from 69.9% to 72.0% and 71.1%; influenza vaccinations increased from 14.2% to 25.4% and 55.3%; current smoking declined from 15.0% to 14.5% and 14.7%; lower-RTI declined from 10.5% to 5.3% and 8.1%; upper-RTI reduced from 10.7% to 5.8% and 7.6%. There was cluster effect of GP practices on asthma exacerbations (p = 0.001). People with asthma were more likely (p < 0.05) to have exacerbations if they had LRTI (seven times(x)), had URTI and ILI (both twice), were current smokers (1.4x), PPV vaccinated (1.3x), seasonal flu vaccinated (1.01x), took ICS (1.3x), had asthma reviews (1.09x). People with asthma were less likely to have exacerbations if they had self-management plan (7%), and were partially (4%) than fully COVID-19 vaccinated. Interpretation: We have identified changes in modifiable risk factors for asthma exacerbation that need to be maintained in the post-pandemic era. Funding: Asthma UK Centre for Applied Research and Health Data Research UK.
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Objective: To evaluate Phenotype Execution and Modelling Architecture (PhEMA), to express sharable phenotypes using Clinical Quality Language (CQL) and intensional Systematised Nomenclature of Medicine (SNOMED) Clinical Terms (CT) Fast Healthcare Interoperability Resources (FHIR) valuesets, for exemplar chronic disease, sociodemographic risk factor, and surveillance phenotypes. Method: We curated 3 phenotypes: Type 2 diabetes mellitus (T2DM), excessive alcohol use, and incident influenza-like illness (ILI) using CQL to define clinical and administrative logic. We defined our phenotypes with valuesets, using SNOMED's hierarchy and expression constraint language, and CQL, combining valuesets and adding temporal elements where needed. We compared the count of cases found using PhEMA with our existing approach using convenience datasets. We assessed our new approach against published desiderata for phenotypes. Results: The T2DM phenotype could be defined as 2 intensionally defined SNOMED valuesets and a CQL script. It increased the prevalence from 7.2% to 7.3%. Excess alcohol phenotype was defined by valuesets that added qualitative clinical terms to the quantitative conceptual definitions we currently use; this change increased prevalence by 58%, from 1.2% to 1.9%. We created an ILI valueset with SNOMED concepts, adding a temporal element using CQL to differentiate new episodes. This increased the weekly incidence in our convenience sample (weeks 26-38) from 0.95 cases to 1.11 cases per 100 000 people. Conclusions: Phenotypes for surveillance and research can be described fully and comprehensibly using CQL and intensional FHIR valuesets. Our use case phenotypes identified a greater number of cases, whilst anticipated from excessive alcohol this was not for our other variable. This may have been due to our use of SNOMED CT hierarchy. Our new process fulfilled a greater number of phenotype desiderata than the one that we had used previously, mostly in the modeling domain. More work is needed to implement that sharing and warehousing domains.
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BACKGROUND: We report 2023/2024 season interim influenza vaccine effectiveness for three studies, namely, primary care in Great Britain, hospital settings in Scotland and hospital settings in England. METHODS: A test negative design was used to estimate vaccine effectiveness. RESULTS: Estimated vaccine effectiveness against all influenzas ranged from 63% (95% confidence interval 46 to 75%) to 65% (41 to 79%) among children aged 2-17, from 36% (20 to 49%) to 55% (43 to 65%) among adults 18-64 and from 40% (29 to 50%) to 55% (32 to 70%) among adults aged 65 and over. CONCLUSIONS: During a period of co-circulation of influenza A(H1N1)pdm09 and A(H3N2) in the United Kingdom, evidence for effectiveness of the influenza vaccine in both children and adults was found.
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Subtipo H1N1 del Virus de la Influenza A , Subtipo H3N2 del Virus de la Influenza A , Vacunas contra la Influenza , Gripe Humana , Atención Primaria de Salud , Atención Secundaria de Salud , Humanos , Vacunas contra la Influenza/inmunología , Vacunas contra la Influenza/administración & dosificación , Gripe Humana/prevención & control , Gripe Humana/epidemiología , Adolescente , Adulto , Niño , Preescolar , Persona de Mediana Edad , Adulto Joven , Reino Unido , Anciano , Subtipo H3N2 del Virus de la Influenza A/inmunología , Subtipo H3N2 del Virus de la Influenza A/genética , Masculino , Femenino , Subtipo H1N1 del Virus de la Influenza A/inmunología , Estaciones del Año , Eficacia de las Vacunas , Vacunación/estadística & datos numéricosRESUMEN
BACKGROUND: The 2022/23 influenza season in the United Kingdom saw the return of influenza to prepandemic levels following two seasons with low influenza activity. The early season was dominated by A(H3N2), with cocirculation of A(H1N1), reaching a peak late December 2022, while influenza B circulated at low levels during the latter part of the season. From September to March 2022/23, influenza vaccines were offered, free of charge, to all aged 2-13 (and 14-15 in Scotland and Wales), adults up to 49 years of age with clinical risk conditions and adults aged 50 and above across the mainland United Kingdom. METHODS: End-of-season adjusted vaccine effectiveness (VE) estimates against sentinel primary-care attendance for influenza-like illness, where influenza infection was laboratory confirmed, were calculated using the test negative design, adjusting for potential confounders. METHODS: Results In the mainland United Kingdom, end-of-season VE against all laboratory-confirmed influenza for all those > 65 years of age, most of whom received adjuvanted quadrivalent vaccines, was 30% (95% CI: -6% to 54%). VE for those aged 18-64, who largely received cell-based vaccines, was 47% (95% CI: 37%-56%). Overall VE for 2-17 year olds, predominantly receiving live attenuated vaccines, was 66% (95% CI: 53%-76%). CONCLUSION: The paper provides evidence of moderate influenza VE in 2022/23.
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Subtipo H3N2 del Virus de la Influenza A , Virus de la Influenza B , Vacunas contra la Influenza , Gripe Humana , Atención Primaria de Salud , Eficacia de las Vacunas , Humanos , Vacunas contra la Influenza/inmunología , Vacunas contra la Influenza/administración & dosificación , Gripe Humana/prevención & control , Gripe Humana/epidemiología , Persona de Mediana Edad , Adolescente , Adulto , Atención Primaria de Salud/estadística & datos numéricos , Reino Unido/epidemiología , Anciano , Adulto Joven , Niño , Femenino , Masculino , Preescolar , Subtipo H3N2 del Virus de la Influenza A/inmunología , Virus de la Influenza B/inmunología , Subtipo H1N1 del Virus de la Influenza A/inmunología , Estaciones del Año , Vacunación/estadística & datos numéricosRESUMEN
BACKGROUND: Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. OBJECTIVE: We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. METHODS: Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. RESULTS: We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. CONCLUSIONS: The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.
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COVID-19 , Vacunas contra la Influenza , Gripe Humana , Infecciones del Sistema Respiratorio , Virosis , Humanos , Gripe Humana/epidemiología , Gripe Humana/prevención & control , Vigilancia de Guardia , Infecciones del Sistema Respiratorio/epidemiología , Organización Mundial de la Salud , Atención Primaria de SaludRESUMEN
OBJECTIVES: Despite being prioritized during initial COVID-19 vaccine rollout, vulnerable individuals at high risk of severe COVID-19 (hospitalization, intensive care unit admission, or death) remain underrepresented in vaccine effectiveness (VE) studies. The RAVEN cohort study (NCT05047822) assessed AZD1222 (ChAdOx1 nCov-19) two-dose primary series VE in vulnerable populations. METHODS: Using the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub, linked to secondary care, death registration, and COVID-19 datasets in England, COVID-19 outcomes in 2021 were compared in vaccinated and unvaccinated individuals matched on age, sex, region, and multimorbidity. RESULTS: Over 4.5 million AZD1222 recipients were matched (mean follow-up â¼5 months); 68% were ≥50 years, 57% had high multimorbidity. Overall, high VE against severe COVID-19 was demonstrated, with lower VE observed in vulnerable populations. VE against hospitalization was higher in the lowest multimorbidity quartile (91.1%; 95% CI: 90.1, 92.0) than the highest quartile (80.4%; 79.7, 81.1), and among individuals ≥65 years, higher in the 'fit' (86.2%; 84.5, 87.6) than the frailest (71.8%; 69.3, 74.2). VE against hospitalization was lowest in immunosuppressed individuals (64.6%; 60.7, 68.1). CONCLUSIONS: Based on integrated and comprehensive UK health data, overall population-level VE with AZD1222 was high. VEs were notably lower in vulnerable groups, particularly the immunosuppressed.