R14.2 - COVID-IMPACT-UK. Health conditions and COVID19: using UK-wide linked routine healthcare data to address the impact of health conditions on COVID-19 and the impact of COVID-19 on health conditions.

This request is for NHS England data for the purpose of the COVID-IMPACT-UK research consortium coordinated by the British Heart Foundation (BHF) Data Science Centre. The following is a summary of the aims of the research programme provided by the controllers:

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with a range of pre-existing health conditions have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to health conditions per se (myocardial infarction, diabetes, asthma etc.); their risk factors (e.g. age, ethnicity, blood pressure, obesity, diet and lifestyle) or medications (e.g. antihypertensive medications or statins); or combinations of these. Understanding the drivers of this excess risk (i.e. which patients are affected and why) will be a major step towards developing strategies to reduce it.

Just as important as the effects of pre-existing health conditions, and their risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on a wide range of health outcomes.

The direct impacts include acute complications of SARS-CoV-2 infection, such as acute respiratory compromise and venous thromboembolism. In addition, the inflammatory, pro-coagulant and other effects of COVID-19 are, like influenza and other respiratory virus infections, are associated with increased risk of a wide range of physical and mental health conditions in the short, medium and long term. However, the nature and extent of these direct effects are far from fully understood. These conditions include long-COVID, encompassing an as yet incompletely understood spectrum of longer term effects of SARS-CoV-2 infection on a significant proportion of patients.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of many diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke and of those receiving assessment and treatment for cancer declined dramatically during 2020 due to the impact of the pandemic on health service provision and behaviours. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and interventions, including delays in diagnosis caused by cancelled diagnostic tests, and changes over time in response to mitigating actions (e.g. regional and national government advice), is needed to inform current and future government and NHS policy.

The main aims of the COVID-IMPACT-UK research consortium, coordinated by the BHF Data Science Centre are to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1. What are the effects of prior health conditions, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2. What is the direct impact of SARS-CoV-2 infection on acute complications as well as on medium and longer term health conditions?

3. What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of health conditions?

The programme commenced in July 2020. The work is organised into the work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

This WP involves:

• the identification of relevant nationally collated datasets across the UK

• the coordination of applications for ethics approval

• the coordination of applications for access to linked data within national trusted research environments

• the coordination of ongoing developments to NHS England's SDE in partnership with NHS England to support the COVID-IMPACT-UK programme, so that it can, in due course, enable work beyond COVID 19

• the coordination of specialist inputs from data custodians, data scientists with methodological and analytical expertise (statisticians, epidemiologists, health informaticians, bioinformaticians, computer scientists and others) and clinicians

• administrative support for and coordination across all work packages

• the coordination of reporting to Chief Medical Officer (CMO), Joint Committee on Vaccination and Immunisation (JCVI), Medicines & Healthcare products Regulatory Agency (MHRA), NICE and equivalent bodies in the devolved nations via established HDR UK processes

• the on-boarding of new members to the inclusive and transparent consortium (formally CVD-COVID-UK, now renamed COVID-IMPACT-UK)

• the coordination of regular consortium update meetings

• the development and documentation of the consortium’s ways of working

Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments (TREs) in each of the four nations. A paper laying out the approach (see https://www.hdruk.ac.uk/wp-content/uploads/2020/04/200416-COVID19-Research-Data-Final.pdf) was endorsed by SAGE in April 2020. Up-to-date details of datasets requested and accessible within TREs in England, Scotland and Wales (primary care, prescribing/dispensing, hospital, death registry, COVID-19 laboratory testing and vaccination, specialist audit/registry datasets, maternity services and mental health, amongst others, is provided here: https://bhfdatasciencecentre.org/wp-content/uploads/2024/10/241010-CVD-COVID-UK-COVID-IMPACT-TRE-Dataset-Provisioning-Dashboard.pdf.

The CVD-COVID-UK programme has obtained research ethics approval, following an application via IRAS, to expand to cover a wider range of COVID-related research under the name COVID-IMPACT-UK. The consortium has over 400 members from over 50 NHS / academic organisations and >70 approved analysts are working on approved projects within one or more of the TREs providing data access in England, Scotland and Wales. The team continue to work with data custodians across the four nations to enable access to the required linked datasets as these become available, and have also developed mechanisms for regular updates to these linked datasets.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

The BHF Data Science Centre coordinates a streamlined system for considering, refining and approving proposals for research projects that address aspects of one or more of the three key questions outlined above. Any member of the COVID-IMPACT-UK consortium can contribute to an existing project or submit a project proposal to the Approvals and Oversight Board, which includes representatives from data custodians, researchers and public contributors. The Approvals and Oversight Board assesses project proposals, ensures that they fall within the programme’s ethical and regulatory approvals and are aiming to access datasets that are appropriate to their research question(s), identifies un-necessary overlap with existing projects, and provides constructive feedback, particularly from the perspective of the public contributors.

An up-to-date list of projects together with their plain English summaries is maintained on the COVID-IMPACT-UK webpage: https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/.

Given that data custodians in each of the four UK nations will bring together and make available their datasets within separate trusted research environments (TREs), and given the differences between countries in the datasets available, the general approach for each analytic work package will be to develop a master protocol from which country-specific protocols will be developed, aiming for maximum consistency but allowing for country-specific differences in the datasets. Where appropriate, results of country-specific analyses will be combined in meta-analyses.

Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

Detailed protocols and statistical analysis plans for each approved project are made available in the public domain through repositories in the BHF Data Science Centre’s GitHub organisation (https://github.com/BHFDSC)

WP3: Public, patient and professional involvement and communications:

Public contributors of the Approvals and Oversight Board review and discuss project proposals with the relevant researchers, ensuring that the proposed research meets the interests of patients and the public, helping to refine and prioritise the research questions, addressing any patient and/or public concerns, and advising on best approaches to patient and public involvement in each project, including communicating research results to lay audiences. This work package also coordinates communications of the consortium’s activities and emerging results through websites, social media and other outlets, and leads on interactions with the press and other media.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK [HDR UK]) has worked in partnership with NHS England to establish a Secure Data Environment (SDE) [service] for England to enable analyses of linked, nationally collated healthcare datasets as part of its COVID-IMPACT-UK programme. The SDE will:

• Enable timely research on the effects/impacts of pre-existing health on COVID-19, and the direct and indirect impacts of COVID-19 on health;

• Coordinate similar approaches across the four nations of the UK;

• Demonstrate how accessing data within an SDE could support future research initiatives.

The linked datasets required for COVID-IMPACT-UK include the following:

• HES and SUS

These data are needed to provide information on admissions to hospital and outpatient appointments with diagnoses so that history of cardiovascular disease and future cardiovascular conditions and associated procedures can be ascertained.

• Emergency Care Dataset

These data are needed to provide information on attendances for cardiovascular conditions before, during and (in due course) after the COVID-19 emergency.

(The SUS and ECDS products are represented by the Secondary Care Data product in the products section of the application. This is a tactical product created to represent the SUS and ECDS products (and the fields within them) for the purposes of the SDE).

• SGSS (COVID-19 laboratory test results provided to NHS England (from PHE)

These data are needed to ascertain all cases with proven SARS-CoV-2 infection. Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease.

• Mortality data

These data are needed to provide information on dates and underlying + contributing causes of death as part of the assessment of severity of COVID-19 disease and of the impact on cardiovascular diseases.

• General Practice Extraction Service (GPES) data for pandemic planning and research (provided to NHS England from GP system suppliers)

These data are needed to provide information on prior medical history (cardiovascular conditions and co-morbidities), other cardiovascular risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes etc), and prescribed medications for those who have and have not gone on to develop COVID-19 disease with various different levels of severity. It is also needed to provide prospective information on cardiovascular conditions which may occur as a direct or indirect consequence of COVID-19 in the short, medium and long term.

• CHESS (COVID-19 Hospitalisation in England Surveillance System)

These data are needed to provide information on the severity and treatments of people with COVID-19 disease.

• The Medicines dispensed in Primary Care (NHSBSA data)

This dataset will provide information of value for any analyses that assess the potential impact of various different medications on outcomes for patients with COVID-19. The data will complement the information in the GP data for pandemic planning and research dataset, which includes information on medicines prescribed in primary care, by providing information on which prescribed medicines are actually dispensed from pharmacies. It is well known that, for a range of reasons, not all medications prescribed are actually collected by patients. Although a full picture of adherence to prescribed medicines cannot be captured through these routinely collected healthcare data, knowing that a medication was both prescribed (from the GP data) and dispensed (from the NHSBSA data) takes the researchers one step further towards knowing that it was actually collected, providing a more complete picture of ‘medication exposure’.

The NHSBSA data must only be used to ascertain the safety and effectiveness of medications dispensed or supplied, as per the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.

• COVID-19 ICNARC Case Mix Programme for Adult Critical Care data set (linked data provided to NHS England by the Intensive Care National Audit and Research Centre)

These data are needed to provide information on the severity of disease in people with COVID-19 disease. In particular they are needed to provide prospective information on severe consequences (requiring intensive care management) of cardiovascular conditions which may occur as a direct or indirect consequence of COVID-19 in the short, medium and long term. This asset can be accessed for COVID-19 purposes only, all data flows must cease at the end of the COPI regulations.

• NICOR datasets (National Institute for Cardiovascular Outcome Research NHS Arden & GEM Commissioning Support Unit commissioned cardiovascular audit registries – provided to NHS England)

These data are needed to provide additional details on cardiovascular conditions and procedures before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease. Linking these datasets to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the impact of COVID-19 on cardiovascular disease occurrence, reoccurrence and outcomes in short, medium and long term, and the impact of cardiovascular conditions on susceptibility to COVID-19 infection and disease. The various NICOR datasets provide more detailed and accurate information on a range of cardiovascular diseases that will complement and enhance the information on cardiovascular diseases and multiple relevant co-morbid conditions available within the HES, primary care records and other linked datasets requested.

• NICOR TAVI data (Trans-catheter aortic valve implantation registry – to be provided to NHS England)

These data are needed to provide additional details on aortic valve replacement procedures before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease.

Linking these datasets to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the direct and indirect impact of COVID-19 on TAVI procedures for aortic stenosis and their potentially beneficial and harmful consequences in the short, medium and long term.

• SSNAP (Stroke Sentinel National Audit Programme HQIP commissioned audit registry – to be provided to NHS England)

These data are needed to provide additional details on strokes before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease. Linking this dataset to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the impact of COVID-19 on stroke occurrence, reoccurrence and outcomes in short, medium and long term. The detailed data on stroke, stroke types, and stroke treatment / processes of care will complement and enrich those available in the other linked datasets to enable more informed, clinically relevant and impactful research outputs.

• NVR (National Vascular Registry HQIP commissioned audit registries – to be provided to NHS England)

These data are needed to provide additional details on vascular surgical procedures before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease. Linking this dataset to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the impact of COVID-19 on cardiovascular disease occurrence, reoccurrence and outcomes in short, medium and long term.

• Electronic Prescribing and Medicines Administration (EPMA) Data

This dataset will provide information of value for any analyses that assess the potential impact of various different medications on outcomes for patients with COVID-19. These data are needed to provide information on hospital prescribed medications for those who have gone on to develop COVID-19 disease with various different levels of severity. The data will complement the information in the ‘medicines dispensed in primary care’ (NHSBSA data) and ‘GP data for pandemic planning and research’ dataset, which includes information on medicines prescribed and dispensed in primary care. Data can be requested only for the purposes set out in the Direction (COVID-19 Public Health Directions 2020), currently limited to COVID-19 purposes.

• COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)

The ‘Pillar 2’ dataset will provide information on antigen test results for those who have had swab testing in the community, including at drive through test centres, walk in centres, home kits returned by post, care homes, prisons etc and will include information on PCR and lateral flow test types. These data are required to ascertain all cases with proven or suspected SARS-CoV-2 infection. Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. These data will complement the information provided in the SGSS dataset.

• COVID-19 UK Non-hospital Antibody Testing Results (Pillar 3) data

The 'Pillar 3' dataset will provide information on serology test results from those who have undergone a finger prick test for antibodies to COVID-19. These data are required to ascertain all cases with proven or suspected SARS-CoV-2 infection. Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. These data will complement the information provided in the SGSS dataset.

• Vaccination event dataset

This dataset will provide information on when patients receive the vaccine and the vaccine product used. Linkage of these data to other data on hospitalisations, intensive care and mortality will be used to indicate the implications of adverse reactions, infection by SARS-CoV-2 post vaccination and subsequent severity of COVID-19 disease and the impact on cardiovascular disease.

• Vaccine adverse reaction dataset:

This dataset will provide information on if there were any adverse reactions associated with the vaccine. Linkage of these data to other data on hospitalisations, intensive care and mortality will be used to indicate the implications of adverse reactions, infection by SARS-CoV-2 post vaccination and subsequent severity of COVID-19 disease and the impact on cardiovascular disease.

• Uncurated Low Latency Hospital Data Sets - (Admitted Patient Care, Outpatient, Critical Care and Emergency Care) Data Sets

These data are needed to provide information on admissions to hospital and outpatient appointments with diagnoses so that history of health conditions and future health conditions and associated procedures can be ascertained. These data are important for projects where the most up-to-date data on hospital admissions, outpatient admissions and diagnoses, critical care and emergency care are required. These data are provided in a format similar to HES (unlike the currently provided SUS data), which enables analysis on linked data to be more efficient and in a more timely manner.

• IAPT (Improving Access to Psychological Therapies)

These data are required to provide details on people referred to IAPT services for anxiety and depression. These data are important for understanding the mental health impact of COVID-19 and Long COVID.

• MSDS (Maternity Services Data Set)

These data are required to provide additional details on maternity services for mother and baby(s) before and after the COVID-19 epidemic, in individuals with and without COVID-19.

• MHSDS (Mental Health data)

These data are required to provide details on adults and children receiving specialist or secondary mental health or learning disability services. These data are important for understanding the impact of COVID-19 and Long COVID on mental health and individuals with learning disabilities.

• Patient Reported Outcome Measures (Linkable to HES)

These data are requested to examine the association between regional palliative care response across settings (from the CovPall survey) and patient centred outcomes and utilities during the pandemic. The data will be linked to Hospital Episode Statistics as it will enable the examination of hospital activity and its relationship with activities and associations in patient outcomes that are available, to infer recommendations for routine patient outcome collection in palliative care.

The data will be minimised for each use in the following ways:

~ to only include those datasets required to address the questions included within the agreement

~ only for organisations who are part of the BHF DSC/HDRUK COVID-IMPACT-UK consortium

~ a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

~ as an interim measure until these data minimisation techniques can be applied, projects will only be included if they are urgent (or do not require data minimisation beyond minimisation at the dataset level).

~ although physical data minimisation is not yet physically possible, there are contractual restrictions in place which ensures that researchers only access the datasets they need to.

The minimisation per use will be reviewed and approved by the BHF Data Science Centre during the application process for access to linked data within national trusted research environments.

Data across all datasets should include information on patients who died prior to 2020. The reason for this is that a number of the projects conducted as part of COVID-IMPACT-UK will need to compare medical histories and mortality associated with a range of different cardiovascular conditions prior to, during and – in due course – after the COVID-19 pandemic. (For example, comparing overall and cause-specific mortality data during 2020 with mortality during the previous 5 years is currently the standard way of calculating excess deaths).

Some analyses based on primary care data will require analysis at the level of individual GP practices. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS England and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

A consortium of organisations as listed below are the data controllers and substantive employees, enrolled students and honorary contract holders with one of the data controller institutions will have access to data within the SDE:

Imperial College London

King's College London

London School of Hygiene and Tropical Medicine

Swansea University

University College London

University of Bristol

University of Cambridge

University of Dundee

University of Glasgow

University of Leicester

University of Liverpool

University of Manchester

University of Nottingham

University of Oxford

University of Sheffield

University of Southampton

Data will be accessed by Undergraduate, Masters or PhD students enrolled with a named controller. Any student working with the Data held under this Data Sharing Agreement (DSA) must have completed relevant data protection and confidentiality training and are subject to the affiliated controller’s policies on data protection and confidentiality. Any students accessing the Data will do so under the supervision of a substantive employee of a named controller who would be responsible and liable for any work carried out by students. These students would only work on the Data for the purposes described in this DSA.

Data will be accessed by individuals holding an honorary contract under the supervision of a substantive employee of a named controller for the purposes described in this DSA only. The controller must maintain records in a single location that cover the following details of each individual given access under an honorary contract:

• Their substantive employer;

• Their role in respect of the purpose for the processing specified in the DSA;

• The start date and end date of the duration in which the Data will be accessed by the individual under an honorary contract;

• The necessity for the Data to be accessed by the person(s) holding an honorary contract, instead of a substantive employee of an organisation named as controller or a processor in this DSA;

• Confirmation that an appropriate contract is in place which follows the relevant guidance and is countersigned by the substantive employer of the honorary contract holder.

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work may be reported as appropriate to the CMO and equivalent bodies in the devolved nations as well as to NICE, MHRA, the Joint Committee on Vaccination and Immunisation and other relevant bodies, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs may also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the UK Government’s National Core Studies. Outputs may inform the clinical management of patients with different health conditions presenting with COVID-19 disease and strategies for patients with complications and consequences of COVID-19.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the BHF DSC website (linking to additional institutional documentation if appropriate), repositories in the BHF DSC GitHub organisation, and in open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (COVID-IMPACT-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

The outputs achieved via access to the data so far are detailed in the Yielded Benefits section, and are also available via a regularly updated list on the programme webpage (https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/)

There are 42 publications or preprints (papers not yet peer reviewed) currently publicly available that have been produced through analyses of English data in the SDE, as follows, with a further 17 manuscripts nearing the point of submission:

• Project CCU002: Association of COVID-19 infection and vaccination on venous and arterial events

o CCU002_01: Association of COVID-19 with major arterial and venous thrombotic diseases: a population-wide cohort study of 48 million adults in England and Wales (https://doi.org/10.1161/CIRCULATIONAHA.122.060785)

o CCU002_02: Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, and thrombocytopenic events: A population-based cohort study of 46 million adults in England (https://doi.org/10.1371/journal.pmed.1003926)

o CCU002_03: Risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccinations (https://doi.org/10.1101/2022.03.06.21267462)

o CCU002_06: Cohort study of cardiovascular safety of different COVID-19 vaccination doses among 46 million adults in England (https://doi.org/10.1038/s41467-024-49634-x)

• Project CCU003: Direct and indirect effects of the coronavirus (COVID-19) pandemic in individuals with cardiovascular disease

o CCU003_01: A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease (https://doi.org/10.1016/j.kint.2022.05.015)

o CCU003_03: Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19 - a data-driven retrospective cohort study (https://doi.org/10.1177/01410768221131897)

o CCU003_04: Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries (https://doi.org/10.1093/ehjqcco/qcac077)

• CCU004_02: A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation (https://doi.org/10.1101/2021.12.20.21268113)

• Project CCU005: Data management and analysis methods

o CCU005_01: Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource (bmj.com/content/373/bmj.n826 and blogs.bmj.com/bmj/2021/04/08/lynn-laidlaw-how-do-we-bring-data-and-its-outputs-to-life/)

o CCU005_03: Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration (https://doi.org/10.1186/s12911-022-02093-0)

• CCU007_01: Impact of COVID-19 pandemic on rates of congenital heart disease procedures among children: Prospective cohort analyses of 26,270 procedures in 17,860 children using CVD-COVID-UK consortium record linkage data (https://doi.org/10.1101/2024.05.20.24307597)

• CCU008_01: Routine measurement of cardiometabolic disease risk factors in primary care in England before, during and after the COVID-19 pandemic: A population-based cohort study (https://dx.doi.org/10.2139/ssrn.4641150 – accepted by PLOS Medicine and awaiting publication)

• CCU013_01: COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records (https://doi.org/10.1016/S2589-7500(22)00091-7)

• Project CCU014: Assessing the impact of COVID-19 on clinical pathways using a medicines approach

o CCU014_01: The impact of COVID-19 pandemic on cardiovascular disease prevention and management (https://doi.org/10.1038/s41591-022-02158-7)

o CCU014_03: Use of sodium valproate and other anti-seizure medications in England and Wales during the COVID-19 pandemic: a population-level analysis of 60 million individuals (https://dx.doi.org/10.2139/ssrn.4544777)

• CCU018_01: COVID-19 diagnosis, vaccination during pregnancy, and adverse pregnancy outcomes of 865,654 women in England and Wales: a population-based cohort study (https://doi.org/10.1016/j.lanepe.2024.101037)

• CCU019_01: A nationwide study of 331 rare diseases among 58 million individuals: prevalence, demographics, and COVID-19 outcomes (https://doi.org/10.1101/2023.10.12.23296948)

• CCU020: Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort (http://dx.doi.org/10.1136/heartjnl-2021-320325)

• Project CCU024: CovPall-Connect. Evaluation of how palliative and end of life care teams have responded to COVID-19: Connecting to boost impact and data assets

o CCU024_01: Better End of Life 2022. Mind the gaps: understanding and improving out-of-hours care for people with advanced illness and their informal carers. Research report. (https://www.mariecurie.org.uk/globalassets/media/documents/policy/beol-reports-2022/better-end-of-life-report-2022.pdf)

o CCU024_02: Association between ethnicity and emergency department visits in the last three months of life in England: a retrospective population-based study using electronic health records (accepted by BMJ Public Health and awaiting publication)

• CCU029_01: Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England (https://doi.org/10.1136/bmj-2022-073639)

• CCU030_01: Understanding covid-19 outcomes among people with Intellectual Disabilities in England (https://doi.org/10.1186/s12889-023-16993-x)

• CCU035_01: Risk of cardiovascular events following COVID-19 in people with and without pre-existing chronic respiratory disease (https://doi.org/10.1093/ije/dyae068)

• CCU036_01: COVID-19 vaccination and birth outcomes of 186,990 women vaccinated before pregnancy: an England-wide cohort study (https://doi.org/10.1016/j.lanepe.2024.101025)

• CCU037_01: Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity (https://doi.org/10.1038/s41597-024-02958-1)

• Project CCU040: Investigating why some people with diabetes have a greater risk of becoming seriously unwell or dying with COVID-19

o CCU040_01: Sars-Cov-2 infection in people with Type 1 diabetes and hospital admission: an analysis of risk factors for England (https://doi.org/10.1007/s13300-023-01456-8)

o CCU040_02: The challenges of replication: a worked example of methods reproducibility using routinely collected healthcare data (https://doi.org/10.1101/2024.08.06.24311535)

o CCU040_03: Replicating a regional COVID-19 study in the national UK COVID-IMPACT database (https://doi.org/10.1101/2024.08.06.24311538)

• Project CCU045: The impact of COVID-19 on heart failure epidemiology, quality of care and outcomes across primary and secondary care

o CCU045_01: A nationwide, population-based study on specialized care for acute heart failure throughout the COVID-19 pandemic (https://doi.org/10.1002/ejhf.3306)

o CCU045_02: Modern epidemiology of heart failure with reduced and preserved ejection fraction among 57 million individuals in England: a study of whole-population electronic health records (accepted by The Lancet Public Health and awaiting publication)

• CCU049_01: Healthcare utilisation of 282,080 individuals with long COVID over two years: a multiple matched control cohort analysis (accepted by Journal of the Royal Society of Medicine and awaiting publication)

• CCU051_01: Under-vaccination and severe COVID-19 outcomes: meta-analysis of national cohort studies of over 64 million people in England, Northern Ireland, Scotland and Wales (https://doi.org/10.1016/S0140-6736(23)02467-4)

• CCU059_01: Combinations of multiple long-term conditions and risk of hospitalisation or death during winter 2021-22: population-based cohort study of 48 million people in England (accepted by BMJ Medicine and awaiting publication)

• CCU060_01: Vaccinations, cardiovascular drugs, hospitalisation and mortality in COVID-19 and Long COVID (https://doi.org/10.1016/j.ijid.2024.107155)

• CCU068_01: The impact of COVID-19 vaccination on patients with congenital heart disease in England: a case-control study (https://doi.org/10.1136/heartjnl-2024-324470)

Additional and critically important outputs from completed studies, including data curation and analysis code, phenotype algorithms and protocols, are made publicly available for re-use by the health data science research community via repositories in the GitHub organisation (https://github.com/BHFDSC).

The SDE (formerly the TRE) has been available since July 2020 and, given the scale of the data that has been brought together and linked for the first time, significant data cleaning and curation has been required to understand the data quality and generate linked datasets that are suitable for analysis. This process has been far more time consuming and analyst resource intensive than first anticipated.

However, the analyst team is now reaping the rewards of this effort by being able to make rapid progress with analyses for many of the 50+ approved projects, with more in the pipeline (https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/).

Significant examples of the benefits are:

1. Impact on policy and healthcare

As part of a UK Government Chief Medical Officer (CMO)-led initiative to better understand the direct and indirect cardiovascular impacts of COVID-19, one of the projects (CCU003_05) investigated pre, during and post-pandemic trends in incidence of hypertension, atrial fibrillation, myocardial infarction and stroke. It showed dips in new diagnoses of all of these early in the pandemic, followed by variable recovery of hypertension and atrial fibrillation diagnoses and a sustained increase in MI and stroke incidence from mid-2020. These results have been discussed with the CMO, UK Government Chief Scientific Adviser for Health and their teams to inform DHSC secondary prevention policies and is also being prepared for publication. Building on this the team are supporting researchers to investigate the burden of a range of cardiovascular diseases before, during and after the pandemic and developing a dashboard to provide insights in a digestible format.

Research from three of the projects (CCU019_03, CCU059, CCU060) fed into an NIHR call to address the NHS Winter Pressures crisis (with one paper published and another accepted for publication).

The first whole UK population study of 68 million people revealed the impact of COVID-19 under-vaccination. The COALESCE (Capacity and capability Of UK-wide Analysts to LEverage health data at Scale using COVID-19 as an Exemplar) study (project CCU051_01 - https://doi.org/10.1016/S0140-6736(23)02467-4) showed over 7,000 hospitalisations and deaths might have been averted in the summer of 2022 if the UK had had better vaccine coverage (Fig 5). Results were presented to the Chief Medical Officers and relevant Chief Scientific Advisers across the four UK nations. The BHF Data Science Centre co-led this pathfinder study to develop capacity, capability and analytical approaches to demonstrate the feasibility of using routinely collected NHS data of all people living in Northern Ireland, Wales, Scotland, and England for research with public benefit by informing health policies. Analysis covering more granular ethnicity detail is ongoing at the request of the CMO for England. Working with the Science Media Centre (SMC) resulted in widespread positive media coverage, including the BBC Radio 4 Today programme (see Appendix 2 – media coverage).

Another study has investigated the association between COVID-19 vaccines and rare blood clots (CCU002_02 - https://doi.org/10.1371/journal.pmed.1003926). This work has informed the COVID-19 vaccination programme in the UK and globally through reports to the Medicines and Healthcare products Regulatory Agency (MHRA), the Joint Committee on Vaccination and Immunisation (JCVI) and the Chief Medical Officer (CMO) for England. It is published in PLOS Medicine.

Analysis has shown a reduction in risk when looking at all types of clots in veins (the most common being pulmonary embolism and deep vein thrombosis (DVT)) and all types of clots in arteries (the most common being heart attacks and strokes), after vaccination with a first dose of the Pfizer or Oxford-AstraZeneca vaccine.

When looking at just a subset of these clots - the very rare types of blood clots - such as ICVT (intracranial venous thrombosis, which are clots in the veins of the brain) and thrombocytopenia (low platelet count) there is a small increase in these events in those <70 years of age in the first month after being given the first dose of the Oxford-AstraZeneca vaccine. As these events are very rare, the increase is still extremely small.

Extension of this work has investigated the impact of COVID-19 infection (CCU002_01 - https://doi.org/10.1161/CIRCULATIONAHA.122.060785) on all types of clots in veins and all types of clots in arteries, in 48 million adults in England and Wales during the first wave of the pandemic (so before vaccines were available). It has shown an increase in these events up to 1-2 weeks after COVID-19 infection. This risk then rapidly reduces over time (from infection), but more quickly for clots in the arteries compared with clots in the veins. The increased risk of blood clots remains for at least 49 weeks after infection and may have led to an additional 10,500 cases of heart attack, strokes and other complications caused by blood clots – although the risk to individuals remains small.

This study will continue to look at the effects 1) after a second dose of the vaccine; 2) of other Covid-19 vaccines; 3) of longer follow up periods.

Study CCU003_01 (published in Kidney International - https://doi.org/10.1016/j.kint.2022.05.015) investigated the impact of individuals with chronic kidney disease. Results indicated a significant health burden for these individuals, with over two-thirds of the 2.3 million people over 30 with chronic kidney disease identified in this study having at least one other health condition (e.g. high blood pressure). The authors recommended people living with kidney disease be prioritised for measures such as vaccination and shielding in the future.

The first three-nations (England, Scotland and Wales) analysis published in Nature Medicine (study CCU014_01 - https://doi.org/10.1038/s41591-022-02158-7), used trends in dispensed medicines data to demonstrate the impact of COVID-19 on the management of risk factors for cardiovascular diseases across England, Scotland and Wales. The study showed that 500,000 people had potentially missed blood pressure lowering medications during the pandemic. A synchronised media effort with the BHF media team resulted in widespread broadsheet and tabloid coverage, with broadcast highlights including BBC Radio 4 Today and BBC News live. Tesco supermarket cited this paper as evidence when highlighting the need for BP checks and offering free BP checks in store (https://www.tescoplc.com/tesco-to-offer-up-to-half-a-million-free-blood-pressure-checks-as-millions-are-deprioritising-routine-health-checks/). The work was featured internationally e.g. the International Society for Hypertension newsletter (https://ish-world.com/wp-content/uploads/2023/05/ISH-Hypertension-News-May-2023_.pdf).

Study CCU037_01 (published in Scientific Data - https://doi.org/10.1038/s41597-024-02958-1) looked at populations that are typically underserved in cardiovascular disease research, such as, the analysis of ethnicity recording across different routinely collected NHS datasets.

Studies CCU018_01 and CCU036_01 investigated COVID-19 infection and vaccination during pregnancy and the role in cardiovascular-related maternal health outcomes, and COVID-19 vaccination impact on birth outcomes respectively (both published in The Lancet Regional Health Europe - https://doi.org/10.1016/j.lanepe.2024.101037 and https://doi.org/10.1016/j.lanepe.2024.101025).

Study CCU007_01 analysed the impact of COVID-19 on congenital heart disease procedures in children.

Study CCU019_01 completed the first analysis of rare diseases at a national scale (>58 million people) and outcomes after COVID-19 infection, enabling research on even very rare conditions ((<1 case per million).

2. Impact on reducing analysis time for research and insights into the pandemic

The CCU013_01 project (published in The Lancet Digital Health - https://doi.org/10.1016/S2589-7500(22)00091-7) investigated different ways to extract information from electronic health records to accurately categorise patients (e.g. if they have a particular disease), which will speed up analysis of health information for all CVD-COVID-UK/COVID-IMPACT to ultimately benefit patients. This work also looked at differences between wave 1 (Feb to May 2020) and wave 2 (Sept 2020 to Feb 2021) of the pandemic. The researchers showed that the number of days from hospitalisation to death increased from 4 days in the first wave to 7 days in the second wave - likely because of vaccination and improved treatments for COVID-19. However, one-third of patients received ventilatory support outside of ICU departments, and this was associated with the highest death rates in both wave one and wave two – indicating the need for planning on how to scale ICU services in the event of future pandemics and healthcare emergencies.

Other benefits can be found on the BHF Data Science Centre’s webpage - https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/

This request is for NHS England data for the purpose of the COVID-IMPACT-UK research consortium coordinated by the British Heart Foundation (BHF) Data Science Centre. The following is a summary of the aims of the research programme provided by the controllers:

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with a range of pre-existing health conditions have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to health conditions per se (myocardial infarction, diabetes, asthma etc.); their risk factors (e.g. age, ethnicity, blood pressure, obesity, diet and lifestyle) or medications (e.g. antihypertensive medications or statins); or combinations of these. Understanding the drivers of this excess risk (i.e. which patients are affected and why) will be a major step towards developing strategies to reduce it.

Just as important as the effects of pre-existing health conditions, and their risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on a wide range of health outcomes.

The direct impacts include acute complications of SARS-CoV-2 infection, such as acute respiratory compromise and venous thromboembolism. In addition, the inflammatory, pro-coagulant and other effects of COVID-19 are, like influenza and other respiratory virus infections, are associated with increased risk of a wide range of physical and mental health conditions in the short, medium and long term. However, the nature and extent of these direct effects are far from fully understood. These conditions include long-COVID, encompassing an as yet incompletely understood spectrum of longer term effects of SARS-CoV-2 infection on a significant proportion of patients.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of many diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke and of those receiving assessment and treatment for cancer declined dramatically during 2020 due to the impact of the pandemic on health service provision and behaviours. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and interventions, including delays in diagnosis caused by cancelled diagnostic tests, and changes over time in response to mitigating actions (e.g. regional and national government advice), is needed to inform current and future government and NHS policy.

The main aims of the COVID-IMPACT-UK research consortium, coordinated by the BHF Data Science Centre are to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1. What are the effects of prior health conditions, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2. What is the direct impact of SARS-CoV-2 infection on acute complications as well as on medium and longer term health conditions?

3. What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of health conditions?

The programme commenced in July 2020. The work is organised into the work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

This WP involves:

• the identification of relevant nationally collated datasets across the UK

• the coordination of applications for ethics approval

• the coordination of applications for access to linked data within national trusted research environments

• the coordination of ongoing developments to NHS England's SDE in partnership with NHS England to support the COVID-IMPACT-UK programme, so that it can, in due course, enable work beyond COVID 19

• the coordination of specialist inputs from data custodians, data scientists with methodological and analytical expertise (statisticians, epidemiologists, health informaticians, bioinformaticians, computer scientists and others) and clinicians

• administrative support for and coordination across all work packages

• the coordination of reporting to Chief Medical Officer (CMO), Joint Committee on Vaccination and Immunisation (JCVI), Medicines & Healthcare products Regulatory Agency (MHRA), NICE and equivalent bodies in the devolved nations via established HDR UK processes

• the on-boarding of new members to the inclusive and transparent consortium (formally CVD-COVID-UK, now renamed COVID-IMPACT-UK)

• the coordination of regular consortium update meetings

• the development and documentation of the consortium’s ways of working

Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations. A paper laying out the approach (see https://www.hdruk.ac.uk/wp-content/uploads/2020/04/200416-COVID19-Research-Data-Final.pdf) was endorsed by SAGE in April 2020. Up-to-date details of datasets requested and accessible within TREs in England, Scotland and Wales (primary care, prescribing/dispensing, hospital, death registry, COVID-19 laboratory testing and vaccination, specialist audit/registry datasets, maternity services and mental health, amongst others, is provided here: http://bhfdatasciencecentre.org/wp-content/uploads/2023/10/231012-CVD-COVID-UK-COVID-IMPACT-TRE-Dataset-Provisioning-Dashboard.pdf.

The CVD-COVID-UK programme has obtained research ethics approval, following an application via IRAS, to expand to cover a wider range of COVID-related research under the name COVID-IMPACT-UK. The consortium has over 380 members from over 50 NHS / academic organisations and >70 approved analysts are working on approved projects within one or more of the TREs providing data access in England, Scotland and Wales. We continue to work with data custodians across the four nations to enable access to the required linked datasets as these become available, and have also developed mechanisms for regular updates to these linked datasets.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

The BHF Data Science Centre coordinates a streamlined system for considering, refining and approving proposals for research projects that address aspects of one or more of the three key questions outlined above. Any member of the COVID-IMPACT-UK consortium can contribute to an existing project or submit a project proposal to the Approvals and Oversight Board, which includes representatives from data custodians, researchers and public contributors. The Approvals and Oversight Board assesses project proposals, ensures that they fall within the programme’s ethical and regulatory approvals and are aiming to access datasets that are appropriate to their research question(s), identifies un-necessary overlap with existing projects, and provides constructive feedback, particularly from the perspective of the public contributors.

An up-to-date list of projects together with their plain English summaries is maintained on the COVID-IMPACT-UK webpage: https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/.

Given that data custodians in each of the four UK nations will bring together and make available their datasets within separate trusted research environments (TREs), and given the differences between countries in the datasets available, the general approach for each analytic work package will be to develop a master protocol from which country-specific protocols will be developed, aiming for maximum consistency but allowing for country-specific differences in the datasets. Where appropriate, results of country-specific analyses will be combined in meta-analyses.

Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

Detailed protocols and statistical analysis plans for each approved project are made available in the public domain through repositories in the BHF Data Science Centre’s GitHub organisation (https://github.com/BHFDSC)

WP3: Public, patient and professional involvement and communications:

Public contributors of the Approvals and Oversight Board review and discuss project proposals with the relevant researchers, ensuring that the proposed research meets the interests of patients and the public, helping to refine and prioritise the research questions, addressing any patient and/or public concerns, and advising on best approaches to patient and public involvement in each project, including communicating research results to lay audiences. This work package also coordinates communications of the consortium’s activities and emerging results through websites, social media and other outlets, and leads on interactions with the press and other media.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK [HDR UK]) has worked in partnership with NHS England to establish a Secure Data Environment (SDE) [service] for England to enable analyses of linked, nationally collated healthcare datasets as part of its COVID-IMPACT-UK programme. The SDE will:

• Enable timely research on the effects/impacts of pre-existing health on COVID-19, and the direct and indirect impacts of COVID-19 on health;

• Coordinate similar approaches across the four nations of the UK;

• Demonstrate how accessing data within an SDE could support future research initiatives.

The linked datasets required for COVID-IMPACT-UK include the following:

• HES and SUS

These data are needed to provide information on admissions to hospital and outpatient appointments with diagnoses so that history of cardiovascular disease and future cardiovascular conditions and associated procedures can be ascertained.

• Emergency Care Dataset

These data are needed to provide information on attendances for cardiovascular conditions before, during and (in due course) after the COVID-19 emergency.

(The SUS and ECDS products are represented by the Secondary Care Data product in the products section of the application. This is a tactical product created to represent the SUS and ECDS products (and the fields within them) for the purposes of the SDE).

• SGSS (COVID-19 laboratory test results provided to NHS England (from PHE)

These data are needed to ascertain all cases with proven SARS-CoV-2 infection. Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease.

• Mortality data

These data are needed to provide information on dates and underlying + contributing causes of death as part of the assessment of severity of COVID-19 disease and of the impact on cardiovascular diseases.

• General Practice Extraction Service (GPES) data for pandemic planning and research (provided to NHS England from GP system suppliers)

These data are needed to provide information on prior medical history (cardiovascular conditions and co-morbidities), other cardiovascular risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes etc), and prescribed medications for those who have and have not gone on to develop COVID-19 disease with various different levels of severity. It is also needed to provide prospective information on cardiovascular conditions which may occur as a direct or indirect consequence of COVID-19 in the short, medium and long term.

• CHESS (COVID-19 Hospitalisation in England Surveillance System)

These data are needed to provide information on the severity and treatments of people with COVID-19 disease.

• The Medicines dispensed in Primary Care (NHSBSA data)

This dataset will provide information of value for any analyses that assess the potential impact of various different medications on outcomes for patients with COVID-19. The data will complement the information in the GP data for pandemic planning and research dataset, which includes information on medicines prescribed in primary care, by providing information on which prescribed medicines are actually dispensed from pharmacies. It is well known that, for a range of reasons, not all medications prescribed are actually collected by patients. Although a full picture of adherence to prescribed medicines cannot be captured through these routinely collected healthcare data, knowing that a medication was both prescribed (from the GP data) and dispensed (from the NHSBSA data) takes the researchers one step further towards knowing that it was actually collected, providing a more complete picture of ‘medication exposure’.

The NHSBSA data must only be used to ascertain the safety and effectiveness of medications dispensed or supplied, as per the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.

• COVID-19 ICNARC Case Mix Programme for Adult Critical Care data set (linked data provided to NHS England by the Intensive Care National Audit and Research Centre)

These data are needed to provide information on the severity of disease in people with COVID-19 disease. In particular they are needed to provide prospective information on severe consequences (requiring intensive care management) of cardiovascular conditions which may occur as a direct or indirect consequence of COVID-19 in the short, medium and long term. This asset can be accessed for COVID-19 purposes only, all data flows must cease at the end of the COPI regulations.

• NICOR datasets (National Institute for Cardiovascular Outcome Research NHS Arden & GEM Commissioning Support Unit commissioned cardiovascular audit registries – provided to NHS England)

These data are needed to provide additional details on cardiovascular conditions and procedures before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease. Linking these datasets to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the impact of COVID-19 on cardiovascular disease occurrence, reoccurrence and outcomes in short, medium and long term, and the impact of cardiovascular conditions on susceptibility to COVID-19 infection and disease. The various NICOR datasets provide more detailed and accurate information on a range of cardiovascular diseases that will complement and enhance the information on cardiovascular diseases and multiple relevant co-morbid conditions available within the HES, primary care records and other linked datasets requested.

• NICOR TAVI data (Trans-catheter aortic valve implantation registry – to be provided to NHS England)

These data are needed to provide additional details on aortic valve replacement procedures before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease.

Linking these datasets to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the direct and indirect impact of COVID-19 on TAVI procedures for aortic stenosis and their potentially beneficial and harmful consequences in the short, medium and long term.

• SSNAP (Stroke Sentinel National Audit Programme HQIP commissioned audit registry – to be provided to NHS England)

These data are needed to provide additional details on strokes before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease. Linking this dataset to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the impact of COVID-19 on stroke occurrence, reoccurrence and outcomes in short, medium and long term. The detailed data on stroke, stroke types, and stroke treatment / processes of care will complement and enrich those available in the other linked datasets to enable more informed, clinically relevant and impactful research outputs.

• NVR (National Vascular Registry HQIP commissioned audit registries – to be provided to NHS England)

These data are needed to provide additional details on vascular surgical procedures before and after the COVID-19 epidemic, in individuals with and without COVID-19 disease. Linking this dataset to routinely collected data (e.g. primary care, hospital) will enable a comprehensive assessment of the impact of COVID-19 on cardiovascular disease occurrence, reoccurrence and outcomes in short, medium and long term.

• Electronic Prescribing and Medicines Administration (EPMA) Data

This dataset will provide information of value for any analyses that assess the potential impact of various different medications on outcomes for patients with COVID-19. These data are needed to provide information on hospital prescribed medications for those who have gone on to develop COVID-19 disease with various different levels of severity. The data will complement the information in the ‘medicines dispensed in primary care’ (NHSBSA data) and ‘GP data for pandemic planning and research’ dataset, which includes information on medicines prescribed and dispensed in primary care. Data can be requested only for the purposes set out in the Direction (COVID-19 Public Health Directions 2020), currently limited to COVID-19 purposes.

• COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)

The ‘Pillar 2’ dataset will provide information on antigen test results for those who have had swab testing in the community, including at drive through test centres, walk in centres, home kits returned by post, care homes, prisons etc and will include information on PCR and lateral flow test types. These data are required to ascertain all cases with proven or suspected SARS-CoV-2 infection. Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. These data will complement the information provided in the SGSS dataset.

• COVID-19 UK Non-hospital Antibody Testing Results (Pillar 3) data

The 'Pillar 3' dataset will provide information on serology test results from those who have undergone a finger prick test for antibodies to COVID-19. These data are required to ascertain all cases with proven or suspected SARS-CoV-2 infection. Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. These data will complement the information provided in the SGSS dataset.

• Vaccination event dataset

This dataset will provide information on when patients receive the vaccine and the vaccine product used. Linkage of these data to other data on hospitalisations, intensive care and mortality will be used to indicate the implications of adverse reactions, infection by SARS-CoV-2 post vaccination and subsequent severity of COVID-19 disease and the impact on cardiovascular disease.

• Vaccine adverse reaction dataset:

This dataset will provide information on if there were any adverse reactions associated with the vaccine. Linkage of these data to other data on hospitalisations, intensive care and mortality will be used to indicate the implications of adverse reactions, infection by SARS-CoV-2 post vaccination and subsequent severity of COVID-19 disease and the impact on cardiovascular disease.

• Uncurated Low Latency Hospital Data Sets - (Admitted Patient Care, Outpatient, Critical Care and Emergency Care) Data Sets

These data are needed to provide information on admissions to hospital and outpatient appointments with diagnoses so that history of health conditions and future health conditions and associated procedures can be ascertained. These data are important for projects where the most up-to-date data on hospital admissions, outpatient admissions and diagnoses, critical care and emergency care are required. These data are provided in a format similar to HES (unlike the currently provided SUS data), which enables analysis on linked data to be more efficient and in a more timely manner.

• IAPT (Improving Access to Psychological Therapies)

These data are required to provide details on people referred to IAPT services for anxiety and depression. These data are important for understanding the mental health impact of COVID-19 and Long COVID.

• MSDS (Maternity Services Data Set)

These data are required to provide additional details on maternity services for mother and baby(s) before and after the COVID-19 epidemic, in individuals with and without COVID-19.

• MHSDS (Mental Health data)

These data are required to provide details on adults and children receiving specialist or secondary mental health or learning disability services. These data are important for understanding the impact of COVID-19 and Long COVID on mental health and individuals with learning disabilities.

• Patient Reported Outcome Measures (Linkable to HES)

These data are requested to examine the association between regional palliative care response across settings (from the CovPall survey) and patient centred outcomes and utilities during the pandemic. The data will be linked to Hospital Episode Statistics as it will enable the examination of hospital activity and its relationship with activities and associations in patient outcomes that are available, to infer recommendations for routine patient outcome collection in palliative care.

The data will be minimised for each use in the following ways:

~ to only include those datasets required to address the questions included within the agreement

~ only for organisations who are part of the BHF DSC/HDRUK COVID-IMPACT-UK consortium

~ a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

~ as an interim measure until these data minimisation techniques can be applied, projects will only be included if they are urgent (or do not require data minimisation beyond minimisation at the dataset level).

~ although physical data minimisation is not yet physically possible, there are contractual restrictions in place which ensures that researchers only access the datasets they need to.

The minimisation per use will be reviewed and approved by the BHF Data Science Centre during the application process for access to linked data within national trusted research environments.

Data across all datasets should include information on patients who died prior to 2020. The reason for this is that a number of the projects conducted as part of COVID-IMPACT-UK will need to compare medical histories and mortality associated with a range of different cardiovascular conditions prior to, during and – in due course – after the COVID-19 pandemic. (For example, comparing overall and cause-specific mortality data during 2020 with mortality during the previous 5 years is currently the standard way of calculating excess deaths).

Some analyses based on primary care data will require analysis at the level of individual GP practices. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS England and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

A consortium of organisations as listed below are the data controllers and substantive employees, enrolled students and affiliated researchers of these organisations will have access to the record level data within the SDE:

Imperial College London

King's College London

London School of Hygiene and Tropical Medicine (in this amendment request)

Swansea University

University College London

University of Bristol

University of Cambridge

University of Dundee (in this amendment request

University of Glasgow

University of Leicester

University of Liverpool

University of Manchester

University of Nottingham (in this amendment request

University of Oxford

University of Sheffield

University of Southampton

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the SDE until the agreement has been amended:

British Heart Foundation

Keele University

St George’s, University of London

The National Institute for Health and Care Excellence (NICE)

University of Aberdeen

University of Edinburgh

University of Leeds

University of Strathclyde

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work may be reported as appropriate to the CMO and equivalent bodies in the devolved nations as well as to NICE, MHRA, the Joint Committee on Vaccination and Immunisation and other relevant bodies, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs may also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the UK Government’s National Core Studies. Outputs may inform the clinical management of patients with different health conditions presenting with COVID-19 disease and strategies for patients with complications and consequences of COVID-19.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the BHF DSC website (linking to additional institutional documentation if appropriate), repositories in the BHF DSC GitHub organisation, and in open access publications. Hence all outputs will be freely available..

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (COVID-IMPACT-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

The outputs achieved via access to the data so far are detailed in the Yielded Benefits section, and are also available via a regularly updated list on the programme webpage (https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/)

There are 23 publications or preprints (papers not yet peer reviewed) currently publicly available that have been produced through analyses of English data in the SDE, as follows, with a further 18 manuscripts nearing the point of submission:

• Project CCU002: Association of COVID-19 infection and vaccination on venous and arterial events

o CCU002_01: Association of COVID-19 with major arterial and venous thrombotic diseases: a population-wide cohort study of 48 million adults in England and Wales (https://doi.org/10.1161/CIRCULATIONAHA.122.060785)

o CCU002_02: Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, and thrombocytopenic events: A population-based cohort study of 46 million adults in England (https://doi.org/10.1371/journal.pmed.1003926)

o CCU002_03: Risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccinations (https://doi.org/10.1101/2022.03.06.21267462)

• Project CCU003: Direct and indirect effects of the coronavirus (COVID-19) pandemic in individuals with cardiovascular disease

o CCU003_01: A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease (https://doi.org/10.1016/j.kint.2022.05.015)

o CCU003_03: Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19 - a data-driven retrospective cohort study (https://doi.org/10.1177/01410768221131897)

o CCU003_04: Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries (https://doi.org/10.1093/ehjqcco/qcac077)

• CCU004_02: A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation (https://doi.org/10.1101/2021.12.20.21268113)

• Project CCU005: Data management and analysis methods

o CCU005_01: Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource (bmj.com/content/373/bmj.n826 and blogs.bmj.com/bmj/2021/04/08/lynn-laidlaw-how-do-we-bring-data-and-its-outputs-to-life/)

o CCU005_03: Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration (https://doi.org/10.1186/s12911-022-02093-0)

• CCU013_01: COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records (https://doi.org/10.1016/S2589-7500(22)00091-7)

• Project CCU014: Assessing the impact of COVID-19 on clinical pathways using a medicines approach

o CCU014_01: The impact of COVID-19 pandemic on cardiovascular disease prevention and management (https://doi.org/10.1038/s41591-022-02158-7)

o CCU014_03: Use of sodium valproate and other anti-seizure medications in England and Wales during the COVID-19 pandemic: a population-level analysis of 60 million individuals (https://dx.doi.org/10.2139/ssrn.4544777)

• CCU019_01: A nationwide study of 331 rare diseases among 58 million individuals: prevalence, demographics, and COVID-19 outcomes (https://doi.org/10.1101/2023.10.12.23296948)

• CCU020: Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort (http://dx.doi.org/10.1136/heartjnl-2021-320325)

• CCU024_01: Better End of Life 2022. Mind the gaps: understanding and improving out-of-hours care for people with advanced illness and their informal carers. Research report. (https://www.mariecurie.org.uk/globalassets/media/documents/policy/beol-reports-2022/better-end-of-life-report-2022.pdf)

• CCU029_01: Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England (https://doi.org/10.1136/bmj-2022-073639)

• CCU030_01: Understanding covid-19 outcomes among people with Intellectual Disabilities in England (accepted by BMC Public Health, awaiting publication)

• CCU035_01: Risk of cardiovascular events following COVID-19 in people with and without pre-existing chronic respiratory disease (https://doi.org/10.1101/2023.03.01.23286624)

• CCU037_01: Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity (https://doi.org/10.1101/2022.11.11.22282217)

• CCU040_01: Sars-Cov-2 infection in people with Type 1 diabetes and hospital admission: an analysis of risk factors for England (https://doi.org/10.1007/s13300-023-01456-8)

• CCU049_01: Healthcare utilisation of 282,080 individuals with long COVID over two years: a multiple matched control cohort analysis (submitted to a journal, decision pending)

• CCU051_01: Under-vaccination and severe COVID-19 outcomes: meta-analysis of national cohort studies of over 64 million people in England, Northern Ireland, Scotland and Wales (submitted to a journal, decision pending)

Additional and critically important outputs from completed studies, including data curation and analysis code, phenotype algorithms and protocols, are made publicly available for re-use by the health data science research community via repositories in our GitHub organisation (https://github.com/BHFDSC).

The SDE (formerly the TRE) has been available since July 2020 and, given the scale of the data that has been brought together and linked for the first time, significant data cleaning and curation has been required to understand the data quality and generate linked datasets that are suitable for analysis. This process has been far more time consuming and analyst resource intensive than first anticipated.

However, the analyst team is now reaping the rewards of this effort by being able to make rapid progress with analyses for many of the 50+ approved projects, with more in the pipeline (https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/).

Significant examples of the benefits are:

1. Impact on policy and healthcare

As part of a UK Government Chief Medical Officer (CMO)-led initiative to better understand the direct and indirect cardiovascular impacts of COVID-19, one of our projects (CCU003_05) investigated pre, during and post-pandemic trends in incidence of hypertension, atrial fibrillation, myocardial infarction and stroke. It showed dips in new diagnoses of all of these early in the pandemic, followed by variable recovery of hypertension and atrial fibrillation diagnoses and a sustained increase in MI and stroke incidence from mid-2020. These results have been discussed with the CMO, UK Government Chief Scientific Adviser for Health and their teams to inform DHSC secondary prevention policies and is also being prepared for publication.

Research from three of our projects (CCU019_03, CCU059, CCU060) fed into an NIHR call to address the NHS Winter Pressures crisis.

The COALESCE (Capacity and capability Of UK-wide Analysts to LEverage health data at Scale using COVID-19 as an Exemplar) project (CCU051_01), looked at vaccination rates across the UK. to provide the UK and devolved nation governments with the information necessary to understand the determinants and consequences of sub-optimal COVID-19 vaccine uptake and so to improve it. The results have been presented to the Chief Medical Officers and relevant Chief Scientific Advisers from each of the four UK nations and has been submitted to The Lancet.

Another study has investigated the association between COVID-19 vaccines and rare blood clots (CCU002_02 - https://doi.org/10.1371/journal.pmed.1003926). This work has informed the COVID-19 vaccination programme in the UK and globally through reports to the Medicines and Healthcare products Regulatory Agency (MHRA), the Joint Committee on Vaccination and Immunisation (JCVI) and the Chief Medical Officer (CMO) for England. It is published in PLOS Medicine.

Analysis has shown a reduction in risk when looking at all types of clots in veins (the most common being pulmonary embolism and deep vein thrombosis (DVT)) and all types of clots in arteries (the most common being heart attacks and strokes), after vaccination with a first dose of the Pfizer or Oxford-AstraZeneca vaccine.

When looking at just a subset of these clots - the very rare types of blood clots - such as ICVT (intracranial venous thrombosis, which are clots in the veins of the brain) and thrombocytopenia (low platelet count) there is a small increase in these events in those <70 years of age in the first month after being given the first dose of the Oxford-AstraZeneca vaccine. As these events are very rare, the increase is still extremely small.

Extension of this work has investigated the impact of COVID-19 infection (CCU002_01 - https://doi.org/10.1161/CIRCULATIONAHA.122.060785) on all types of clots in veins and all types of clots in arteries, in 48 million adults in England and Wales during the first wave of the pandemic (so before vaccines were available). It has shown an increase in these events up to 1-2 weeks after COVID-19 infection. This risk then rapidly reduces over time (from infection), but more quickly for clots in the arteries compared with clots in the veins. The increased risk of blood clots remains for at least 49 weeks after infection and may have led to an additional 10,500 cases of heart attack, strokes and other complications caused by blood clots – although the risk to individuals remains small.

This study will continue to look at the effects 1) after a second dose of the vaccine; 2) of other Covid-19 vaccines; 3) of longer follow up periods.

Study CCU003_01 (published in Kidney International - https://doi.org/10.1016/j.kint.2022.05.015) investigated the impact of individuals with chronic kidney disease. Results indicated a significant health burden for these individuals, with over two-thirds of the 2.3 million people over 30 with chronic kidney disease identified in this study having at least one other health condition (e.g. high blood pressure). The authors recommended people living with kidney disease be prioritised for measures such as vaccination and shielding in the future.

Study CCU014_01 (published in Nature Medicine – https://doi.org/10.1038/s41591-022-02158-7) investigated the impact of the COVID-19 pandemic on cardiovascular disease through the use of medicines data in England, Scotland and Wales. They found the use of many medications dropped during the pandemic and have not returned to pre-pandemic levels. For example the estimated reduction in treatment with antihypertensives may lead to over 13,600 additional cardiovascular events if individuals remain untreated.

2. Impact on reducing analysis time for research and insights into the pandemic

The CCU013_01 project (published in The Lancet Digital Health - https://doi.org/10.1016/S2589-7500(22)00091-7) investigated different ways to extract information from electronic health records to accurately categorise patients (e.g. if they have a particular disease), which will speed up analysis of health information for all CVD-COVID-UK/COVID-IMPACT to ultimately benefit patients. This work also looked at differences between wave 1 (Feb to May 2020) and wave 2 (Sept 2020 to Feb 2021) of the pandemic. The researchers showed that the number of days from hospitalisation to death increased from 4 days in the first wave to 7 days in the second wave - likely because of vaccination and improved treatments for COVID-19. However, one-third of patients received ventilatory support outside of ICU departments, and this was associated with the highest death rates in both wave one and wave two – indicating the need for planning on how to scale ICU services in the event of future pandemics and healthcare emergencies.

Other benefits can be found on the BHF Data Science Centre’s webpage - https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/

v9 is a simple amendment to ensure all Controllers sign to the NHS England terms and not NHS Digital ones. No other changes made to the Agreement.

___________________________________________________________________________________________________

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

Patients with a range of pre-existing health conditions have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to health conditions per se (myocardial infarction, diabetes, asthma etc.); their risk factors (e.g. age, ethnicity, blood pressure, obesity, diet and lifestyle) or medications (e.g. antihypertensive medications or statins); or combinations of these. Understanding the drivers of this excess risk (i.e. which patients are affected and why) will be a major step towards developing strategies to reduce it.

Just as important as the effects of pre-existing health conditions, and their risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on a wide range of health outcomes.

The direct impacts include acute complications of SARS-CoV-2 infection, such as acute respiratory compromise and venous thromboembolism. In addition, the inflammatory, pro-coagulant and other effects of COVID-19 are, like influenza and other respiratory virus infections, are associated with increased risk of a wide range of physical and mental health conditions in the short, medium and long term. However, the nature and extent of these direct effects are far from fully understood. These conditions include long-COVID, encompassing an as yet incompletely understood spectrum of longer term effects of SARS-CoV-2 infection on a significant proportion of patients.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of many diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke and of those receiving assessment and treatment for cancer declined dramatically during 2020 due to the impact of the pandemic on health service provision and behaviours. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and interventions, including delays in diagnosis caused by cancelled diagnostic tests, and changes over time in response to mitigating actions (e.g. regional and national government advice), is needed to inform current and future government and NHS policy.

The main aims of the COVID-IMPACT-UK research consortium, coordinated by the BHF Data Science Centre are to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1. What are the effects of prior health conditions, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2. What is the direct impact of SARS-CoV-2 infection on acute complications as well as on medium and longer term health conditions?

3. What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of health conditions?

The work is organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

This WP involves:

• the identification of relevant nationally collated datasets across the UK

• the coordination of applications for ethics approval

• the coordination of applications for access to linked data within national trusted research environments

• the coordination of ongoing developments to NHS England's TRE in partnership with NHS England to support the COVID-IMPACT-UK programme, so that it can, in due course, enable work beyond COVID 19

• the coordination of specialist inputs from data custodians, data scientists with methodological and analytical expertise (statisticians, epidemiologists, health informaticians, bioinformaticians, computer scientists and others) and clinicians

• administrative support for and coordination across all work packages

• the coordination of reporting to Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations via established HDR UK processes

• the on-boarding of new members to the inclusive and transparent consortium (formally CVD-COVID-UK, now renamed COVID-IMPACT-UK)

• the coordination of regular consortium update meetings

• the development and documentation of the consortium’s ways of working

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

The BHF Data Science Centre coordinates a streamlined system for considering, refining and approving proposals for research projects that address aspects of one or more of the three key questions outlined above. Any member of the COVID-IMPACT-UK consortium can contribute to an existing project or submit a project proposal to the Approvals and Oversight Board, which includes representatives from data custodians, researchers and lay members. The Approvals and Oversight Board assesses project proposals, ensures that they fall within the programme’s ethical and regulatory approvals and are aiming to access datasets that are appropriate to their research question(s), identifies un-necessary overlap with existing projects, and provides constructive feedback, particularly from the perspective of the lay members.

An up-to-date list of projects together with their lay summaries is maintained on the COVID-IMPACT-UK webpage: https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/.

WP3: Public, patient and professional involvement and communications:

Lay members of the Approvals and Oversight Board review and discuss project proposals with the relevant researchers, ensuring that the proposed research meets the interests of patients and the public, helping to refine and prioritise the research questions, addressing any patient and/or public concerns, and advising on best approaches to patient and public involvement in each project, including communicating research results to lay audiences. This work package also coordinates communications of the consortium’s activities and emerging results through websites, social media and other outlets, and leads on interactions with the press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees, enrolled students and affiliated researchers of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

Swansea University

University of Oxford

King's College London

University of Glasgow

Imperial College London

University of Manchester

University of Liverpool (in this amendment request)

University of Southampton (in this amendment request)

University of Sheffield (in this amendment request)

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

British Heart Foundation

Keele University

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

The National Institute for Health and Care Excellence (NICE)

University of Strathclyde

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work may be reported as appropriate to SAGE and equivalent bodies in the devolved nations as well as to NICE, MHRA, the Joint Committee on Vaccination and Immunisation and other relevant bodies, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs may also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the UK Government’s National Core Studies. Outputs may inform the clinical management of patients with different health conditions presenting with COVID-19 disease and strategies for patients with complications and consequences of COVID-19.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (COVID-IMPACT-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

The additional requested datasets will not lead to any further outputs, however the datasets may help enrich the planned outputs such as reports for government advisory groups and policy makers, the lay public and academic publications.

The outputs achieved via access to the data so far are detailed in the Yielded Benefits section, and are also available via a regularly updated list on the programme webpage (https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/)

There are 14 publications or preprints (papers not yet peer reviewed) currently publicly available, as follows, with a further 5 manuscripts nearing the point of submission:

• Project CCU002: Association of COVID-19 infection and vaccination on venous and arterial events

o CCU002_01: Association of COVID-19 with major arterial and venous thrombotic diseases: a population-wide cohort study of 48 million adults in England and Wales (https://doi.org/10.1161/CIRCULATIONAHA.122.060785)

o CCU002_02: Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, and thrombocytopenic events: A population-based cohort study of 46 million adults in England (https://doi.org/10.1371/journal.pmed.1003926)

o CCU002_03: Risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccinations (https://doi.org/10.1101/2022.03.06.21267462)

• Project CCU003: Direct and indirect effects of the coronavirus (COVID-19) pandemic in individuals with cardiovascular disease

o CCU003_01: A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease (https://doi.org/10.1016/j.kint.2022.05.015)

o CCU003_03: Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19 - a data-driven retrospective cohort study (https://doi.org/10.1177/01410768221131897)

o CCU003_04: Indirect effects of the first two years of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries (https://doi.org/10.1101/2022.10.13.22281031)

• CCU004_02: A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation (https://doi.org/10.1101/2021.12.20.21268113)

• CCU005_01: Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource (bmj.com/content/373/bmj.n826 and blogs.bmj.com/bmj/2021/04/08/lynn-laidlaw-how-do-we-bring-data-and-its-outputs-to-life/)

• CCU005_03: Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration (https://doi.org/10.21203/rs.3.rs-2109276/v1)

• CCU013_01: COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records (https://doi.org/10.1016/S2589-7500(22)00091-7)

• CCU014_01: The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale analysis of trends in medication data (https://doi.org/10.1101/2021.12.31.21268587 - also accepted by and due to be published in Nature Medicine)

• CCU020: Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort (http://dx.doi.org/10.1136/heartjnl-2021-320325)

• CCU029_01: Hospital admissions linked to SARS-CoV-2 infection in children: a cohort study of 3.2 million first ascertained infections in England (submitted to a journal, decision pending)

• CCU037_01: Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity (https://doi.org/10.1101/2022.11.11.22282217)

Additional and critically important outputs from completed studies, including data curation and analysis code, phenotype algorithms and protocols, are made publicly available for re-use by the health data science research community via repositories in our GitHub organisation (https://github.com/BHFDSC).

The TRE has been available since July 2020 and, given the scale of the data that has been brought together and linked for the first time, significant data cleaning and curation has been required to understand the data quality and generate linked datasets that are suitable for analysis. This process has been far more time consuming and analyst resource intensive than first anticipated.

However, the analyst team is now reaping the rewards of this effort by being able to make rapid progress with analyses for many of the 40 approved projects, with more in the pipeline (https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/).

Significant examples of the benefits are:

1. Impact on policy and healthcare

A key benefit from this study has investigated the association between COVID-19 vaccines and rare blood clots (CCU002_02 - https://doi.org/10.1371/journal.pmed.1003926). This work has informed the COVID-19 vaccination programme in the UK and globally through reports to the Medicines and Healthcare products Regulatory Agency (MHRA), the Joint Committee on Vaccination and Immunisation (JCVI) and the Chief Medical Officer (CMO) for England. It is published in PLOS Medicine.

Analysis has shown a reduction in risk when looking at all types of clots in veins (the most common being pulmonary embolism and deep vein thrombosis (DVT)) and all types of clots in arteries (the most common being heart attacks and strokes), after vaccination with a first dose of the Pfizer or Oxford-AstraZeneca vaccine.

When looking at just a subset of these clots - the very rare types of blood clots - such as ICVT (intracranial venous thrombosis, which are clots in the veins of the brain) and thrombocytopenia (low platelet count) there is a small increase in these events in those <70 years of age in the first month after being given the first dose of the Oxford-AstraZeneca vaccine. As these events are very rare, the increase is still extremely small.

Extension of this work has investigated the impact of COVID-19 infection (CCU002_01 - https://doi.org/10.1161/CIRCULATIONAHA.122.060785) on all types of clots in veins and all types of clots in arteries, in 48 million adults in England and Wales during the first wave of the pandemic (so before vaccines were available). It has shown an increase in these events up to 1-2 weeks after COVID-19 infection. This risk then rapidly reduces over time (from infection), but more quickly for clots in the arteries compared with clots in the veins. The increased risk of blood clots remains for at least 49 weeks after infection and may have led to an additional 10,500 cases of heart attack, strokes and other complications caused by blood clots – although the risk to individuals remains small.

This study will continue to look at the effects 1) after a second dose of the vaccine; 2) of other Covid-19 vaccines; 3) of longer follow up periods.

Study CCU003_01 (published in Kidney International) investigated the impact of individuals with chronic kidney disease. Results indicated a significant health burden for these individuals, with over two-thirds of the 2.3 million people over 30 with chronic kidney disease identified in this study having at least one other health condition (e.g. high blood pressure). The authors recommended people living with kidney disease be prioritised for measures such as vaccination and shielding in the future.

Study CCU014 has investigated the impact of the COVID-19 pandemic on cardiovascular disease through the use of medicines data in England, Scotland and Wales. They found the use of many medications dropped during the pandemic and have not returned to pre-pandemic levels. For example the estimated reduction in treatment with antihypertensives may lead to over 13,600 additional cardiovascular events if individuals remain untreated. This study has been accepted for publication in Nature Medicine.

2. Impact on reducing analysis time for research and insights into the pandemic

The CCU013_01 project (published in The Lancet Digital Health) listed above has investigated different ways to extract information from electronic health records to accurately categorise patients (e.g. if they have a particular disease), which will speed up analysis of health information for all CVD-COVID-UK/COVID-IMPACT to ultimately benefit patients. This work also looked at differences between wave 1 (Feb to May 2020) and wave 2 (Sept 2020 to Feb 2021) of the pandemic. The researchers showed that the number of days from hospitalisation to death increased from 4 days in the first wave to 7 days in the second wave - likely because of vaccination and improved treatments for COVID-19. However, one-third of patients received ventilatory support outside of ICU departments, and this was associated with the highest death rates in both wave one and wave two – indicating the need for planning on how to scale ICU services in the event of future pandemics and healthcare emergencies.

Other benefits can be found on the HDRUK CVD-COVID-UK / COVID-IMPACT website - https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

Patients with a range of pre-existing health conditions have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to health conditions per se (myocardial infarction, diabetes, asthma etc.); their risk factors (e.g. age, ethnicity, blood pressure, obesity, diet and lifestyle) or medications (e.g. antihypertensive medications or statins); or combinations of these. Understanding the drivers of this excess risk (i.e. which patients are affected and why) will be a major step towards developing strategies to reduce it.

Just as important as the effects of pre-existing health conditions, and their risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on a wide range of health outcomes.

The direct impacts include acute complications of SARS-CoV-2 infection, such as acute respiratory compromise and venous thromboembolism. In addition, the inflammatory, pro-coagulant and other effects of COVID-19 are, like influenza and other respiratory virus infections, are associated with increased risk of a wide range of physical and mental health conditions in the short, medium and long term. However, the nature and extent of these direct effects are far from fully understood. These conditions include long-COVID, encompassing an as yet incompletely understood spectrum of longer term effects of SARS-CoV-2 infection on a significant proportion of patients.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of many diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke and of those receiving assessment and treatment for cancer declined dramatically during 2020 due to the impact of the pandemic on health service provision and behaviours. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and interventions, including delays in diagnosis caused by cancelled diagnostic tests, and changes over time in response to mitigating actions (e.g. regional and national government advice), is needed to inform current and future government and NHS policy.

The main aims of the COVID-IMPACT-UK research consortium, coordinated by the BHF Data Science Centre are to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1. What are the effects of prior health conditions, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2. What is the direct impact of SARS-CoV-2 infection on acute complications as well as on medium and longer term health conditions?

3. What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of health conditions?

The work is organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

This WP involves:

• the identification of relevant nationally collated datasets across the UK

• the coordination of applications for ethics approval

• the coordination of applications for access to linked data within national trusted research environments

• the coordination of ongoing developments to NHS Digital’s TRE in partnership with NHS Digital to support the COVID-IMPACT-UK programme, so that it can, in due course, enable work beyond COVID 19

• the coordination of specialist inputs from data custodians, data scientists with methodological and analytical expertise (statisticians, epidemiologists, health informaticians, bioinformaticians, computer scientists and others) and clinicians

• administrative support for and coordination across all work packages

• the coordination of reporting to Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations via established HDR UK processes

• the on-boarding of new members to the inclusive and transparent consortium (formally CVD-COVID-UK, now renamed COVID-IMPACT-UK)

• the coordination of regular consortium update meetings

• the development and documentation of the consortium’s ways of working

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

The BHF Data Science Centre coordinates a streamlined system for considering, refining and approving proposals for research projects that address aspects of one or more of the three key questions outlined above. Any member of the COVID-IMPACT-UK consortium can contribute to an existing project or submit a project proposal to the Approvals and Oversight Board, which includes representatives from data custodians, researchers and lay members. The Approvals and Oversight Board assesses project proposals, ensures that they fall within the programme’s ethical and regulatory approvals and are aiming to access datasets that are appropriate to their research question(s), identifies un-necessary overlap with existing projects, and provides constructive feedback, particularly from the perspective of the lay members.

An up-to-date list of projects together with their lay summaries is maintained on the COVID-IMPACT-UK webpage: https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/.

WP3: Public, patient and professional involvement and communications:

Lay members of the Approvals and Oversight Board review and discuss project proposals with the relevant researchers, ensuring that the proposed research meets the interests of patients and the public, helping to refine and prioritise the research questions, addressing any patient and/or public concerns, and advising on best approaches to patient and public involvement in each project, including communicating research results to lay audiences. This work package also coordinates communications of the consortium’s activities and emerging results through websites, social media and other outlets, and leads on interactions with the press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees, enrolled students and affiliated researchers of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

Swansea University

University of Oxford

King's College London

University of Glasgow

Imperial College London

University of Manchester

University of Liverpool (in this amendment request)

University of Southampton (in this amendment request)

University of Sheffield (in this amendment request)

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

British Heart Foundation

Keele University

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

The National Institute for Health and Care Excellence (NICE)

University of Strathclyde

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work may be reported as appropriate to SAGE and equivalent bodies in the devolved nations as well as to NICE, MHRA, the Joint Committee on Vaccination and Immunisation and other relevant bodies, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs may also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the UK Government’s National Core Studies. Outputs may inform the clinical management of patients with different health conditions presenting with COVID-19 disease and strategies for patients with complications and consequences of COVID-19.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (COVID-IMPACT-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

The additional requested datasets will not lead to any further outputs, however the datasets may help enrich the planned outputs such as reports for government advisory groups and policy makers, the lay public and academic publications.

The outputs achieved via access to the data so far are detailed in the Yielded Benefits section, and are also available via a regularly updated list on the programme webpage (https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/)

There are 14 publications or preprints (papers not yet peer reviewed) currently publicly available, as follows, with a further 5 manuscripts nearing the point of submission:

• Project CCU002: Association of COVID-19 infection and vaccination on venous and arterial events

o CCU002_01: Association of COVID-19 with major arterial and venous thrombotic diseases: a population-wide cohort study of 48 million adults in England and Wales (https://doi.org/10.1161/CIRCULATIONAHA.122.060785)

o CCU002_02: Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, and thrombocytopenic events: A population-based cohort study of 46 million adults in England (https://doi.org/10.1371/journal.pmed.1003926)

o CCU002_03: Risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccinations (https://doi.org/10.1101/2022.03.06.21267462)

• Project CCU003: Direct and indirect effects of the coronavirus (COVID-19) pandemic in individuals with cardiovascular disease

o CCU003_01: A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease (https://doi.org/10.1016/j.kint.2022.05.015)

o CCU003_03: Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19 - a data-driven retrospective cohort study (https://doi.org/10.1177/01410768221131897)

o CCU003_04: Indirect effects of the first two years of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries (https://doi.org/10.1101/2022.10.13.22281031)

• CCU004_02: A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation (https://doi.org/10.1101/2021.12.20.21268113)

• CCU005_01: Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource (bmj.com/content/373/bmj.n826 and blogs.bmj.com/bmj/2021/04/08/lynn-laidlaw-how-do-we-bring-data-and-its-outputs-to-life/)

• CCU005_03: Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration (https://doi.org/10.21203/rs.3.rs-2109276/v1)

• CCU013_01: COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records (https://doi.org/10.1016/S2589-7500(22)00091-7)

• CCU014_01: The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale analysis of trends in medication data (https://doi.org/10.1101/2021.12.31.21268587 - also accepted by and due to be published in Nature Medicine)

• CCU020: Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort (http://dx.doi.org/10.1136/heartjnl-2021-320325)

• CCU029_01: Hospital admissions linked to SARS-CoV-2 infection in children: a cohort study of 3.2 million first ascertained infections in England (submitted to a journal, decision pending)

• CCU037_01: Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity (https://doi.org/10.1101/2022.11.11.22282217)

Additional and critically important outputs from completed studies, including data curation and analysis code, phenotype algorithms and protocols, are made publicly available for re-use by the health data science research community via repositories in our GitHub organisation (https://github.com/BHFDSC).

The TRE has been available since July 2020 and, given the scale of the data that has been brought together and linked for the first time, significant data cleaning and curation has been required to understand the data quality and generate linked datasets that are suitable for analysis. This process has been far more time consuming and analyst resource intensive than first anticipated.

However, the analyst team is now reaping the rewards of this effort by being able to make rapid progress with analyses for many of the 40 approved projects, with more in the pipeline (https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/).

Significant examples of the benefits are:

1. Impact on policy and healthcare

A key benefit from this study has investigated the association between COVID-19 vaccines and rare blood clots (CCU002_02 - https://doi.org/10.1371/journal.pmed.1003926). This work has informed the COVID-19 vaccination programme in the UK and globally through reports to the Medicines and Healthcare products Regulatory Agency (MHRA), the Joint Committee on Vaccination and Immunisation (JCVI) and the Chief Medical Officer (CMO) for England. It is published in PLOS Medicine.

Analysis has shown a reduction in risk when looking at all types of clots in veins (the most common being pulmonary embolism and deep vein thrombosis (DVT)) and all types of clots in arteries (the most common being heart attacks and strokes), after vaccination with a first dose of the Pfizer or Oxford-AstraZeneca vaccine.

When looking at just a subset of these clots - the very rare types of blood clots - such as ICVT (intracranial venous thrombosis, which are clots in the veins of the brain) and thrombocytopenia (low platelet count) there is a small increase in these events in those <70 years of age in the first month after being given the first dose of the Oxford-AstraZeneca vaccine. As these events are very rare, the increase is still extremely small.

Extension of this work has investigated the impact of COVID-19 infection (CCU002_01 - https://doi.org/10.1161/CIRCULATIONAHA.122.060785) on all types of clots in veins and all types of clots in arteries, in 48 million adults in England and Wales during the first wave of the pandemic (so before vaccines were available). It has shown an increase in these events up to 1-2 weeks after COVID-19 infection. This risk then rapidly reduces over time (from infection), but more quickly for clots in the arteries compared with clots in the veins. The increased risk of blood clots remains for at least 49 weeks after infection and may have led to an additional 10,500 cases of heart attack, strokes and other complications caused by blood clots – although the risk to individuals remains small.

This study will continue to look at the effects 1) after a second dose of the vaccine; 2) of other Covid-19 vaccines; 3) of longer follow up periods.

Study CCU003_01 (published in Kidney International) investigated the impact of individuals with chronic kidney disease. Results indicated a significant health burden for these individuals, with over two-thirds of the 2.3 million people over 30 with chronic kidney disease identified in this study having at least one other health condition (e.g. high blood pressure). The authors recommended people living with kidney disease be prioritised for measures such as vaccination and shielding in the future.

Study CCU014 has investigated the impact of the COVID-19 pandemic on cardiovascular disease through the use of medicines data in England, Scotland and Wales. They found the use of many medications dropped during the pandemic and have not returned to pre-pandemic levels. For example the estimated reduction in treatment with antihypertensives may lead to over 13,600 additional cardiovascular events if individuals remain untreated. This study has been accepted for publication in Nature Medicine.

2. Impact on reducing analysis time for research and insights into the pandemic

The CCU013_01 project (published in The Lancet Digital Health) listed above has investigated different ways to extract information from electronic health records to accurately categorise patients (e.g. if they have a particular disease), which will speed up analysis of health information for all CVD-COVID-UK/COVID-IMPACT to ultimately benefit patients. This work also looked at differences between wave 1 (Feb to May 2020) and wave 2 (Sept 2020 to Feb 2021) of the pandemic. The researchers showed that the number of days from hospitalisation to death increased from 4 days in the first wave to 7 days in the second wave - likely because of vaccination and improved treatments for COVID-19. However, one-third of patients received ventilatory support outside of ICU departments, and this was associated with the highest death rates in both wave one and wave two – indicating the need for planning on how to scale ICU services in the event of future pandemics and healthcare emergencies.

Other benefits can be found on the HDRUK CVD-COVID-UK / COVID-IMPACT website - https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

Patients with a range of pre-existing health conditions have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to health conditions per se (myocardial infarction, diabetes, asthma etc.); their risk factors (e.g. age, ethnicity, blood pressure, obesity, diet and lifestyle) or medications (e.g. antihypertensive medications or statins); or combinations of these. Understanding the drivers of this excess risk (i.e. which patients are affected and why) will be a major step towards developing strategies to reduce it.

Just as important as the effects of pre-existing health conditions, and their risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on a wide range of health outcomes.

The direct impacts include acute complications of SARS-CoV-2 infection, such as acute respiratory compromise and venous thromboembolism. In addition, the inflammatory, pro-coagulant and other effects of COVID-19 are, like influenza and other respiratory virus infections, are associated with increased risk of a wide range of physical and mental health conditions in the short, medium and long term. However, the nature and extent of these direct effects are far from fully understood. These conditions include long-COVID, encompassing an as yet incompletely understood spectrum of longer term effects of SARS-CoV-2 infection on a significant proportion of patients.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of many diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke and of those receiving assessment and treatment for cancer declined dramatically during 2020 due to the impact of the pandemic on health service provision and behaviours. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and interventions, including delays in diagnosis caused by cancelled diagnostic tests, and changes over time in response to mitigating actions (e.g. regional and national government advice), is needed to inform current and future government and NHS policy.

The main aims of the COVID-IMPACT-UK research consortium, coordinated by the BHF Data Science Centre are to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1. What are the effects of prior health conditions, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2. What is the direct impact of SARS-CoV-2 infection on acute complications as well as on medium and longer term health conditions?

3. What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of health conditions?

The work is organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

This WP involves:

• the identification of relevant nationally collated datasets across the UK

• the coordination of applications for ethics approval

• the coordination of applications for access to linked data within national trusted research environments

• the coordination of ongoing developments to NHS Digital’s TRE in partnership with NHS Digital to support the COVID-IMPACT-UK programme, so that it can, in due course, enable work beyond COVID 19

• the coordination of specialist inputs from data custodians, data scientists with methodological and analytical expertise (statisticians, epidemiologists, health informaticians, bioinformaticians, computer scientists and others) and clinicians

• administrative support for and coordination across all work packages

• the coordination of reporting to SAGE and equivalent bodies in the devolved nations via established HDR UK processes

• the on-boarding of new members to the inclusive and transparent consortium (currently CVD-COVID-UK, to be renamed COVID-IMPACT-UK)

• the coordination of regular consortium update meetings

• the development and documentation of the consortium’s ways of working

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

The BHF Data Science Centre coordinates a streamlined system for considering, refining and approving proposals for research projects that address aspects of one or more of the three key questions outlined above. Any member of the COVID-IMPACT-UK consortium can contribute to an existing project or submit a project proposal to the Approvals and Oversight Board, which includes representatives from data custodians, researchers and lay members. The Approvals and Oversight Board assesses project proposals, ensures that they fall within the programme’s ethical and regulatory approvals and are aiming to access datasets that are appropriate to their research question(s), identifies un-necessary overlap with existing projects, and provides constructive feedback, particularly from the perspective of the lay members.

An up-to-date list of projects together with their lay summaries is maintained on the COVID-IMPACT-UK webpage: https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/.

WP3: Public, patient and professional involvement and communications:

Lay members of the Approvals and Oversight Board review and discuss project proposals with the relevant researchers, ensuring that the proposed research meets the interests of patients and the public, helping to refine and prioritise the research questions, addressing any patient and/or public concerns, and advising on best approaches to patient and public involvement in each project, including communicating research results to lay audiences. This work package also coordinates communications of the consortium’s activities and emerging results through websites, social media and other outlets, and leads on interactions with the press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

Swansea University

University of Oxford

King's College London

University of Glasgow

Imperial College London

University of Manchester (amendment request)

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Keele University

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Liverpool

The National Institute for Health and Care Excellence (NICE)

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work may be reported as appropriate to SAGE and equivalent bodies in the devolved nations as well as to NICE, MHRA, the Joint Committee on Vaccination and Immunisation and other relevant bodies, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs may also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the UK Government’s National Core Studies. Outputs may inform the clinical management of patients with different health conditions presenting with COVID-19 disease and strategies for patients with complications and consequences of COVID-19.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (COVID-IMPACT-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

AMENDMENT REQUEST

The additional requested datasets will not lead to any further outputs, however the datasets may help enrich the planned outputs such as reports for government advisory groups and policy makers, the lay public and academic publications.

To date, a description of the data resource of linked datasets within the NHS Digital COVID-IMPACT-UK TRE for the benefit of the research community has been provided:

BMJ publication: https://www.bmj.com/content/373/bmj.n826

BMJ editorial: https://www.bmj.com/content/373/bmj.n898

BMJ public contributor opinion piece: https://blogs.bmj.com/bmj/2021/04/08/lynn-laidlaw-how-do-we-bring-data-and-its-outputs-to-life/

The TRE has been available since July 2020 and, given the scale of the data that has been brought together and linked for the first time, significant data cleaning and curation has been required to understand the data quality and generate linked datasets that are suitable for analysis. This process has been far more time consuming and analyst resource intensive than first anticipated.

However, the analyst team is now reaping the rewards of this effort by being able to make rapid progress with analyses for many of the 27 approved projects, with more in the pipeline (https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/).

The publications or preprints (papers not yet peer reviewed) currently publicly available are as follows:

• CCU002_01: Association of COVID-19 with arterial and venous vascular diseases: a population-wide cohort study of 48 million adults in England and Wales (https://doi.org/10.1101/2021.11.22.21266512)

• CCU002_02: Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, and thrombocytopenic events: whole population cohort study in 46 million adults in England (https://doi.org/10.1101/2021.08.18.21262222)

• CCU002_03: Risk of myocarditis and pericarditis following COVID-19 vaccination (preprint pending upload to medRxiv)

• CCU003_01: Predicting and validating risk of pre-pandemic and excess mortality in individuals with chronic kidney disease (http://ssrn.com/abstract=3970707)

• CCU004_02: A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation (https://doi.org/10.1101/2021.12.20.21268113)

• CCU005_01: Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource (bmj.com/content/373/bmj.n826 and blogs.bmj.com/bmj/2021/04/08/lynn-laidlaw-how-do-we-bring-data-and-its-outputs-to-life/)

• CCU013_01: Understanding COVID-19 trajectories from a nationwide linked electronic health record cohort of 57 million people: phenotypes, severity, waves & vaccination (https://doi.org/10.1101/2021.11.08.21265312)

• CCU014_01: The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data (https://doi.org/10.1101/2021.12.31.21268587)

• CCU020: Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort (https://doi.org/10.1101/2021.09.03.21263023)

Examples of the benefits are:

1. Impact on policy and healthcare

One key benefit from this study work has investigated the association between COVID-19 vaccines and rare blood clots. This work has informed the COVID-19 vaccination programme in the UK and globally through reports to the Medicines and Healthcare products Regulatory Agency (MHRA), the Joint Committee on Vaccination and Immunisation (JCVI) and the Chief Medical Officer (CMO) for England. It has been accepted for publication by PLOS Medicine.

Analysis has shown a reduction in risk when looking at all types of clots in veins (the most common being pulmonary embolism and deep vein thrombosis (DVT)) and all types of clots in arteries (the most common being heart attacks and strokes), after vaccination with a first dose of the Pfizer or Oxford-AstraZeneca vaccine.

When looking at just a subset of these clots - the very rare types of blood clots - such as ICVT (intracranial venous thrombosis, which are clots in the veins of the brain) and thrombocytopenia (low platelet count) there is a small increase in these events in those <70 years of age in the first month after being given the first dose of the Oxford-AstraZeneca vaccine. As these events are very rare, the increase is still extremely small.

Extension of this work has investigated the impact of COVID-19 infection on all types of clots in veins and all types of clots in arteries, for the adult English and Welsh populations. It has shown an increase in these events up to 1-2 weeks after COVID-19 infection. This risk then rapidly reduces over time (from infection), but more quickly for clots in the arteries compared with clots in the veins.

This study will continue to look at the effects 1) after a second dose of the vaccine; 2) of other Covid-19 vaccines; 3) of longer follow up periods.

2. Impact on reducing analysis time for research and insights into the pandemic

The CCU013_01 project listed above has investigated different ways to extract information from electronic health records to accurately categorise patients (e.g. if they have a particular disease), which will speed up analysis of health information for all CVD-COVID-UK/COVID-IMPACT to ultimately benefit patients. This work also looked at differences between wave 1 (Feb to May 2020) and wave 2 (Sept 2020 to Feb 2021) of the pandemic. The researchers showed that the number of days from hospitalisation to death increased from 4 days in the first wave to 7 days in the second wave – likely because of vaccination and improved treatments for COVID-19.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

Patients with a range of pre-existing health conditions have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to health conditions per se (myocardial infarction, diabetes, asthma etc.); their risk factors (e.g. age, ethnicity, blood pressure, obesity, diet and lifestyle) or medications (e.g. antihypertensive medications or statins); or combinations of these. Understanding the drivers of this excess risk (i.e. which patients are affected and why) will be a major step towards developing strategies to reduce it.

Just as important as the effects of pre-existing health conditions, and their risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on a wide range of health outcomes.

The direct impacts include acute complications of SARS-CoV-2 infection, such as acute respiratory compromise and venous thromboembolism. In addition, the inflammatory, pro-coagulant and other effects of COVID-19 are, like influenza and other respiratory virus infections, are associated with increased risk of a wide range of physical and mental health conditions in the short, medium and long term. However, the nature and extent of these direct effects are far from fully understood. These conditions include long-COVID, encompassing an as yet incompletely understood spectrum of longer term effects of SARS-CoV-2 infection on a significant proportion of patients.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of many diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke and of those receiving assessment and treatment for cancer declined dramatically during 2020 due to the impact of the pandemic on health service provision and behaviours. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and interventions, including delays in diagnosis caused by cancelled diagnostic tests, and changes over time in response to mitigating actions (e.g. regional and national government advice), is needed to inform current and future government and NHS policy.

The main aims of the COVID-IMPACT-UK research consortium, coordinated by the BHF Data Science Centre are to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1. What are the effects of prior health conditions, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2. What is the direct impact of SARS-CoV-2 infection on acute complications as well as on medium and longer term health conditions?

3. What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of health conditions?

The work is organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

This WP involves:

• the identification of relevant nationally collated datasets across the UK

• the coordination of applications for ethics approval

• the coordination of applications for access to linked data within national trusted research environments

• the coordination of ongoing developments to NHS Digital’s TRE in partnership with NHS Digital to support the COVID-IMPACT-UK programme, so that it can, in due course, enable work beyond COVID 19

• the coordination of specialist inputs from data custodians, data scientists with methodological and analytical expertise (statisticians, epidemiologists, health informaticians, bioinformaticians, computer scientists and others) and clinicians

• administrative support for and coordination across all work packages

• the coordination of reporting to SAGE and equivalent bodies in the devolved nations via established HDR UK processes

• the on-boarding of new members to the inclusive and transparent consortium (currently CVD-COVID-UK, to be renamed COVID-IMPACT-UK)

• the coordination of regular consortium update meetings

• the development and documentation of the consortium’s ways of working

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

The BHF Data Science Centre coordinates a streamlined system for considering, refining and approving proposals for research projects that address aspects of one or more of the three key questions outlined above. Any member of the COVID-IMPACT-UK consortium can contribute to an existing project or submit a project proposal to the Approvals and Oversight Board, which includes representatives from data custodians, researchers and lay members. The Approvals and Oversight Board assesses project proposals, ensures that they fall within the programme’s ethical and regulatory approvals and are aiming to access datasets that are appropriate to their research question(s), identifies un-necessary overlap with existing projects, and provides constructive feedback, particularly from the perspective of the lay members.

An up-to-date list of projects together with their lay summaries is maintained on the COVID-IMPACT-UK webpage: https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/.

WP3: Public, patient and professional involvement and communications:

Lay members of the Approvals and Oversight Board review and discuss project proposals with the relevant researchers, ensuring that the proposed research meets the interests of patients and the public, helping to refine and prioritise the research questions, addressing any patient and/or public concerns, and advising on best approaches to patient and public involvement in each project, including communicating research results to lay audiences. This work package also coordinates communications of the consortium’s activities and emerging results through websites, social media and other outlets, and leads on interactions with the press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

Swansea University

University of Oxford

King's College London

University of Glasgow

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Imperial College London

Keele University

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Liverpool

University of Manchester

The National Institute for Health and Care Excellence (NICE)

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work may be reported as appropriate to SAGE and equivalent bodies in the devolved nations as well as to NICE, MHRA, the Joint Committee on Vaccination and Immunisation and other relevant bodies, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs may also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the UK Government’s National Core Studies. Outputs may inform the clinical management of patients with different health conditions presenting with COVID-19 disease and strategies for patients with complications and consequences of COVID-19.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (COVID-IMPACT-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

AMENDMENT REQUEST

The additional requested datasets will not lead to any further outputs, however the datasets may help enrich the planned outputs such as reports for government advisory groups and policy makers, the lay public and academic publications.

To date, a description of the data resource of linked datasets within the NHS Digital COVID-IMPACT-UK TRE for the benefit of the research community has been provided:

BMJ publication: https://www.bmj.com/content/373/bmj.n826

BMJ editorial: https://www.bmj.com/content/373/bmj.n898

BMJ public contributor opinion piece: https://blogs.bmj.com/bmj/2021/04/08/lynn-laidlaw-how-do-we-bring-data-and-its-outputs-to-life/

The TRE has been available for almost 12 months and, given the scale of the data that has been brought together and linked for the first time, has required significant data cleaning and curation to generate linked datasets that are suitable for analysis. This data cleaning and curation has been far more time consuming, required significant analyst resource and taken longer than first anticipated.

However, due to significant effort being made to curate these datasets, the team are now in a good position to make rapid progress with the analysis required for the 16 currently approved projects: (https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/)

One key benefit from this study work has investigated the association between COVID-19 vaccines and rare blood clots. This work will inform the COVID-19 vaccination programme in the UK and globally and has been submitted to the Lancet as well as being reported to the Medicines and Healthcare products Regulatory Agency (MHRA), the Joint Committee on Vaccination and Immunisation (JCVI) and the Chief Medical Officer (CMO) for England.

Analysis has shown a reduction in risk when looking at all types of clots in veins (the most common being pulmonary embolism and deep vein thrombosis (DVT)) and all types of clots in arteries (the most common being heart attacks and strokes), after vaccination with a first dose of the Pfizer or Oxford-AstraZeneca vaccine.

When looking at just a subset of these clots - the very rare types of blood clots - such as ICVT (intracranial venous thrombosis, which are clots in the veins of the brain) and thrombocytopenia (low platelet count) there is a small increase in these events in those <70 years of age in the first month after being given the first dose of the Oxford-AstraZeneca vaccine. As these events are very rare, the increase is still extremely small.

This study will continue to look at the effects 1) after a second dose of the vaccine; 2) of other Covid-19 vaccines; 3) of Covid-19 infection; 4) of longer follow up periods.

Other projects are also making good progress with their analysis. Results are expected soon from the project investigating the effects of angiotensin converting enzyme inhibitors and angiotensin receptor blockers on COVID-19 outcomes; and the project investigating different ways to extract information from electronic health records to accurately categorise patients (e.g. if they have a particular disease), which will speed up analysis of health information to ultimately benefit patients.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with pre-existing cardiovascular disease have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to cardiovascular conditions per se (heart attack, heart failure, stroke etc.); their risk factors (e.g., age, obesity, raised blood pressure or cholesterol, diet and lifestyle) or medications (e.g. drugs to reduce blood pressure); or combinations of these. Understanding which patients with cardiovascular diseases are affected and why will be a major step towards developing strategies to reduce their risk.

Just as important as the effects of cardiovascular disease, and its risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on cardiovascular disease. The direct impacts include acute life-threatening complications, such as heart attacks, strokes and clots in the legs and lungs. In addition, since COVID-19 increases both inflammation and the risk of blood clots, there may be an increased risk of heart attack, stroke and other cardiovascular events in the medium and long term. However, the nature and extent of these direct effects is far from fully understood.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of cardiovascular diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke have declined dramatically, while patients who do present to hospital are frequently arriving too late to receive acute treatments proven to improve outcomes (e.g., clot removal or clot busting treatments) or after preventable complications have developed. Anecdotal reports from clinicians suggest that referrals to specialist outpatient services of patients with milder symptoms (e.g., mini strokes and angina), who would benefit from treatment to reduce the risk of more serious vascular events, have also plummeted. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK, HDR UK) is working in partnership with NHS Digital to establish a Cardiovascular Disease Trusted Research Environment (CVD TRE) (service) for England to enable analyses of linked, nationally collated healthcare datasets. This project is entitled CVD COVID UK. It will:

• Enable timely research on the effects/impacts of cardiovascular disease on COVID-19, and the direct and indirect impacts of COVID-19 on cardiovascular diseases

• Coordinate similar approaches across the four nations of the UK

• Future proof an enduring CVD TRE service post-Covid19

Coordinated by the BHF Data Science Centre, the CVD COVID UK research group which will be made up by proposes to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1) What are the effects of cardiovascular diseases, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2) What is the direct impact of SARS-CoV-2 infection on acute cardiovascular complications and on medium and longer term cardiovascular risk?

3) What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of cardiovascular diseases?

The work would be organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

Identify relevant datasets and required dataset linkages across the UK. Coordinate applications for relevant approvals and access. Coordinate specialist inputs from cardiologists, stroke physicians, vascular surgeons and other relevant clinical groups. Coordinate reporting to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations via established HDR UK processes.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

• WP 2.1 Indirect impact of COVID-19 on cardiovascular diseases: Time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic

• WP 2.2 Influence/associations of cardiovascular conditions on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death)

• WP 2.3 Influence/associations of cardiovascular risk factors on COVID-19 outcomes

• WP 2.4 Influence/associations of cardiovascular medications on COVID-19 outcomes

• WP 2.5 Direct impact of COVID-19 disease on cardiovascular disease occurrence, re-occurrence and outcomes in short, medium and long term

WP3: Public, patient and professional involvement and communications:

Work with existing HDR UK and BHF public, patient and professional panels to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

University of Liverpool

Swansea University

The National Institute for Health and Care Excellence (NICE)

University of Oxford

King's College London

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Imperial College London

Keele University

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Manchester

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work will be reported to SAGE and equivalent bodies in the devolved nations as well as (especially in WP 2.4) to NICE, MHRA and Scottish Medicine Consortium, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the British Heart Foundation (it is anticipated that outputs will inform the clinical management of patients with different types of cardiovascular disease presenting with COVID-19 disease and cardiovascular prevention strategies for patients with COVID-19 and no prior cardiovascular disease).

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (CVD-COVID-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

AMENDMENT REQUEST

The additional requested datasets will not lead to any further outputs, however the datasets will help enrich the planned outputs such as reports for government advisory groups and policy makers, the lay public and academic publications.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with pre-existing cardiovascular disease have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to cardiovascular conditions per se (heart attack, heart failure, stroke etc.); their risk factors (e.g., age, obesity, raised blood pressure or cholesterol, diet and lifestyle) or medications (e.g. drugs to reduce blood pressure); or combinations of these. Understanding which patients with cardiovascular diseases are affected and why will be a major step towards developing strategies to reduce their risk.

Just as important as the effects of cardiovascular disease, and its risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on cardiovascular disease. The direct impacts include acute life-threatening complications, such as heart attacks, strokes and clots in the legs and lungs. In addition, since COVID-19 increases both inflammation and the risk of blood clots, there may be an increased risk of heart attack, stroke and other cardiovascular events in the medium and long term. However, the nature and extent of these direct effects is far from fully understood.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of cardiovascular diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke have declined dramatically, while patients who do present to hospital are frequently arriving too late to receive acute treatments proven to improve outcomes (e.g., clot removal or clot busting treatments) or after preventable complications have developed. Anecdotal reports from clinicians suggest that referrals to specialist outpatient services of patients with milder symptoms (e.g., mini strokes and angina), who would benefit from treatment to reduce the risk of more serious vascular events, have also plummeted. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK, HDR UK) is working in partnership with NHS Digital to establish a Cardiovascular Disease Trusted Research Environment (CVD TRE) (service) for England to enable analyses of linked, nationally collated healthcare datasets. This project is entitled CVD COVID UK. It will:

• Enable timely research on the effects/impacts of cardiovascular disease on COVID-19, and the direct and indirect impacts of COVID-19 on cardiovascular diseases

• Coordinate similar approaches across the four nations of the UK

• Future proof an enduring CVD TRE service post-Covid19

Coordinated by the BHF Data Science Centre, the CVD COVID UK research group which will be made up by proposes to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1) What are the effects of cardiovascular diseases, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2) What is the direct impact of SARS-CoV-2 infection on acute cardiovascular complications and on medium and longer term cardiovascular risk?

3) What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of cardiovascular diseases?

The work would be organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

Identify relevant datasets and required dataset linkages across the UK. Coordinate applications for relevant approvals and access. Coordinate specialist inputs from cardiologists, stroke physicians, vascular surgeons and other relevant clinical groups. Coordinate reporting to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations via established HDR UK processes.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

• WP 2.1 Indirect impact of COVID-19 on cardiovascular diseases: Time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic

• WP 2.2 Influence/associations of cardiovascular conditions on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death)

• WP 2.3 Influence/associations of cardiovascular risk factors on COVID-19 outcomes

• WP 2.4 Influence/associations of cardiovascular medications on COVID-19 outcomes

• WP 2.5 Direct impact of COVID-19 disease on cardiovascular disease occurrence, re-occurrence and outcomes in short, medium and long term

WP3: Public, patient and professional involvement and communications:

Work with existing HDR UK and BHF public, patient and professional panels to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

University of Liverpool

Swansea University

The National Institute for Health and Care Excellence (NICE)

University of Oxford

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Imperial College London

Keele University

Kings College London

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Manchester

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work will be reported to SAGE and equivalent bodies in the devolved nations as well as (especially in WP 2.4) to NICE, MHRA and Scottish Medicine Consortium, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the British Heart Foundation (it is anticipated that outputs will inform the clinical management of patients with different types of cardiovascular disease presenting with COVID-19 disease and cardiovascular prevention strategies for patients with COVID-19 and no prior cardiovascular disease).

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (CVD-COVID-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

AMENDMENT REQUEST

The additional requested datasets will not lead to any further outputs, however the datasets will help enrich the planned outputs such as reports for government advisory groups and policy makers, the lay public and academic publications.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with pre-existing cardiovascular disease have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to cardiovascular conditions per se (heart attack, heart failure, stroke etc.); their risk factors (e.g., age, obesity, raised blood pressure or cholesterol, diet and lifestyle) or medications (e.g. drugs to reduce blood pressure); or combinations of these. Understanding which patients with cardiovascular diseases are affected and why will be a major step towards developing strategies to reduce their risk.

Just as important as the effects of cardiovascular disease, and its risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on cardiovascular disease. The direct impacts include acute life-threatening complications, such as heart attacks, strokes and clots in the legs and lungs. In addition, since COVID-19 increases both inflammation and the risk of blood clots, there may be an increased risk of heart attack, stroke and other cardiovascular events in the medium and long term. However, the nature and extent of these direct effects is far from fully understood.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of cardiovascular diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke have declined dramatically, while patients who do present to hospital are frequently arriving too late to receive acute treatments proven to improve outcomes (e.g., clot removal or clot busting treatments) or after preventable complications have developed. Anecdotal reports from clinicians suggest that referrals to specialist outpatient services of patients with milder symptoms (e.g., mini strokes and angina), who would benefit from treatment to reduce the risk of more serious vascular events, have also plummeted. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK, HDR UK) is working in partnership with NHS Digital to establish a Cardiovascular Disease Trusted Research Environment (CVD TRE) (service) for England to enable analyses of linked, nationally collated healthcare datasets. This project is entitled CVD COVID UK. It will:

• Enable timely research on the effects/impacts of cardiovascular disease on COVID-19, and the direct and indirect impacts of COVID-19 on cardiovascular diseases

• Coordinate similar approaches across the four nations of the UK

• Future proof an enduring CVD TRE service post-Covid19

Coordinated by the BHF Data Science Centre, the CVD COVID UK research group which will be made up by proposes to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1) What are the effects of cardiovascular diseases, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2) What is the direct impact of SARS-CoV-2 infection on acute cardiovascular complications and on medium and longer term cardiovascular risk?

3) What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of cardiovascular diseases?

The work would be organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

Identify relevant datasets and required dataset linkages across the UK. Coordinate applications for relevant approvals and access. Coordinate specialist inputs from cardiologists, stroke physicians, vascular surgeons and other relevant clinical groups. Coordinate reporting to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations via established HDR UK processes.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

• WP 2.1 Indirect impact of COVID-19 on cardiovascular diseases: Time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic

• WP 2.2 Influence/associations of cardiovascular conditions on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death)

• WP 2.3 Influence/associations of cardiovascular risk factors on COVID-19 outcomes

• WP 2.4 Influence/associations of cardiovascular medications on COVID-19 outcomes

• WP 2.5 Direct impact of COVID-19 disease on cardiovascular disease occurrence, re-occurrence and outcomes in short, medium and long term

WP3: Public, patient and professional involvement and communications:

Work with existing HDR UK and BHF public, patient and professional panels to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

University of Liverpool

Swansea University

The National Institute for Health and Care Excellence (NICE)

University of Oxford

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Imperial College London

Keele University

Kings College London

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Manchester

The data controller(s) listed within this agreement in Section 1 confirm that they will ensure that a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The outputs of each piece of work will be reported to SAGE and equivalent bodies in the devolved nations as well as (especially in WP 2.4) to NICE, MHRA and Scottish Medicine Consortium, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the British Heart Foundation (it is anticipated that outputs will inform the clinical management of patients with different types of cardiovascular disease presenting with COVID-19 disease and cardiovascular prevention strategies for patients with COVID-19 and no prior cardiovascular disease).

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (CVD-COVID-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

AMENDMENT REQUEST

The additional requested datasets will not lead to any further outputs, however the datasets will help enrich the planned outputs such as reports for government advisory groups and policy makers, the lay public and academic publications.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with pre-existing cardiovascular disease have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to cardiovascular conditions per se (heart attack, heart failure, stroke etc.); their risk factors (e.g., age, obesity, raised blood pressure or cholesterol, diet and lifestyle) or medications (e.g. drugs to reduce blood pressure); or combinations of these. Understanding which patients with cardiovascular diseases are affected and why will be a major step towards developing strategies to reduce their risk.

Just as important as the effects of cardiovascular disease, and its risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on cardiovascular disease. The direct impacts include acute life-threatening complications, such as heart attacks, strokes and clots in the legs and lungs. In addition, since COVID-19 increases both inflammation and the risk of blood clots, there may be an increased risk of heart attack, stroke and other cardiovascular events in the medium and long term. However, the nature and extent of these direct effects is far from fully understood.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of cardiovascular diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke have declined dramatically, while patients who do present to hospital are frequently arriving too late to receive acute treatments proven to improve outcomes (e.g., clot removal or clot busting treatments) or after preventable complications have developed. Anecdotal reports from clinicians suggest that referrals to specialist outpatient services of patients with milder symptoms (e.g., mini strokes and angina), who would benefit from treatment to reduce the risk of more serious vascular events, have also plummeted. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK, HDR UK) is working in partnership with NHS Digital to establish a Cardiovascular Disease Trusted Research Environment (CVD TRE) (service) for England to enable analyses of linked, nationally collated healthcare datasets. This project is entitled CVD COVID UK. It will:

• Enable timely research on the effects/impacts of cardiovascular disease on COVID-19, and the direct and indirect impacts of COVID-19 on cardiovascular diseases

• Coordinate similar approaches across the four nations of the UK

• Future proof an enduring CVD TRE service post-Covid19

Coordinated by the BHF Data Science Centre, the CVD COVID UK research group which will be made up by proposes to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1) What are the effects of cardiovascular diseases, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2) What is the direct impact of SARS-CoV-2 infection on acute cardiovascular complications and on medium and longer term cardiovascular risk?

3) What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of cardiovascular diseases?

The work would be organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

Identify relevant datasets and required dataset linkages across the UK. Coordinate applications for relevant approvals and access. Coordinate specialist inputs from cardiologists, stroke physicians, vascular surgeons and other relevant clinical groups. Coordinate reporting to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations via established HDR UK processes.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

• WP 2.1 Indirect impact of COVID-19 on cardiovascular diseases: Time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic

• WP 2.2 Influence/associations of cardiovascular conditions on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death)

• WP 2.3 Influence/associations of cardiovascular risk factors on COVID-19 outcomes

• WP 2.4 Influence/associations of cardiovascular medications on COVID-19 outcomes

• WP 2.5 Direct impact of COVID-19 disease on cardiovascular disease occurrence, re-occurrence and outcomes in short, medium and long term

WP3: Public, patient and professional involvement and communications:

Work with existing HDR UK and BHF public, patient and professional panels to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

University of Liverpool

Swansea University

AMENDMENT REQUEST

An amendment has been made to add the following data controllers to the application:

The National Institute for Health and Care Excellence (NICE)

The current members of the consortium who are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

University of Liverpool

Swansea University

The National Institute for Health and Care Excellence (NICE)

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Imperial College London

Keele University

Kings College London

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Manchester

University of Oxford

The outputs of each piece of work will be reported to SAGE and equivalent bodies in the devolved nations as well as (especially in WP 2.4) to NICE, MHRA and Scottish Medicine Consortium, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the British Heart Foundation (it is anticipated that outputs will inform the clinical management of patients with different types of cardiovascular disease presenting with COVID-19 disease and cardiovascular prevention strategies for patients with COVID-19 and no prior cardiovascular disease).

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (CVD-COVID-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with pre-existing cardiovascular disease have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to cardiovascular conditions per se (heart attack, heart failure, stroke etc.); their risk factors (e.g., age, obesity, raised blood pressure or cholesterol, diet and lifestyle) or medications (e.g. drugs to reduce blood pressure); or combinations of these. Understanding which patients with cardiovascular diseases are affected and why will be a major step towards developing strategies to reduce their risk.

Just as important as the effects of cardiovascular disease, and its risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on cardiovascular disease. The direct impacts include acute life-threatening complications, such as heart attacks, strokes and clots in the legs and lungs. In addition, since COVID-19 increases both inflammation and the risk of blood clots, there may be an increased risk of heart attack, stroke and other cardiovascular events in the medium and long term. However, the nature and extent of these direct effects is far from fully understood.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of cardiovascular diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke have declined dramatically, while patients who do present to hospital are frequently arriving too late to receive acute treatments proven to improve outcomes (e.g., clot removal or clot busting treatments) or after preventable complications have developed. Anecdotal reports from clinicians suggest that referrals to specialist outpatient services of patients with milder symptoms (e.g., mini strokes and angina), who would benefit from treatment to reduce the risk of more serious vascular events, have also plummeted. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK, HDR UK) is working in partnership with NHS Digital to establish a Cardiovascular Disease Trusted Research Environment (CVD TRE) [service] for England to enable analyses of linked, nationally collated healthcare datasets. This project is entitled CVD COVID UK. It will:

• Enable timely research on the effects/impacts of cardiovascular disease on COVID-19, and the direct and indirect impacts of COVID-19 on cardiovascular diseases

• Coordinate similar approaches across the four nations of the UK

• Future proof an enduring CVD TRE service post-Covid19

Coordinated by the BHF Data Science Centre, the CVD COVID UK research group which will be made up by proposes to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1) What are the effects of cardiovascular diseases, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2) What is the direct impact of SARS-CoV-2 infection on acute cardiovascular complications and on medium and longer term cardiovascular risk?

3) What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of cardiovascular diseases?

The work would be organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

Identify relevant datasets and required dataset linkages across the UK. Coordinate applications for relevant approvals and access. Coordinate specialist inputs from cardiologists, stroke physicians, vascular surgeons and other relevant clinical groups. Coordinate reporting to SAGE and equivalent bodies in the devolved nations via established HDR UK processes.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

• WP 2.1 Indirect impact of COVID-19 on cardiovascular diseases: Time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic

• WP 2.2 Influence/associations of cardiovascular conditions on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death)

• WP 2.3 Influence/associations of cardiovascular risk factors on COVID-19 outcomes

• WP 2.4 Influence/associations of cardiovascular medications on COVID-19 outcomes

• WP 2.5 Direct impact of COVID-19 disease on cardiovascular disease occurrence, re-occurrence and outcomes in short, medium and long term

WP3: Public, patient and professional involvement and communications:

Work with existing HDR UK and BHF public, patient and professional panels to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

AMENDMENT REQUEST

An amendment has been made to add the following data controllers to the application:

University of Liverpool

Swansea University

The current members of the consortium who are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

University of Liverpool

Swansea University

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Imperial College London

Keele University

Kings College London

London School of Hygiene and Tropical Medicine

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Manchester

University of Oxford

The outputs of each piece of work will be reported to SAGE and equivalent bodies in the devolved nations as well as (especially in WP 2.4) to NICE, MHRA and Scottish Medicine Consortium, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the British Heart Foundation (it is anticipated that . Outputs will inform the clinical management of patients with different types of cardiovascular disease presenting with COVID-19 disease and cardiovascular prevention strategies for patients with COVID-19 and no prior cardiovascular disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (CVD-COVID-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years. Patients with pre-existing cardiovascular disease have a disproportionately elevated risk of symptomatic infection and mortality. The reasons are not fully understood but could be due to cardiovascular conditions per se (heart attack, heart failure, stroke etc.); their risk factors (e.g., age, obesity, raised blood pressure or cholesterol, diet and lifestyle) or medications (e.g. drugs to reduce blood pressure); or combinations of these. Understanding which patients with cardiovascular diseases are affected and why will be a major step towards developing strategies to reduce their risk.

Just as important as the effects of cardiovascular disease, and its risk factors and medications, on COVID-19 disease, are the direct and indirect impacts of COVID-19 on cardiovascular disease. The direct impacts include acute life-threatening complications, such as heart attacks, strokes and clots in the legs and lungs. In addition, since COVID-19 increases both inflammation and the risk of blood clots, there may be an increased risk of heart attack, stroke and other cardiovascular events in the medium and long term. However, the nature and extent of these direct effects is far from fully understood.

Crucially, there are also indirect impacts on the presentation, diagnosis, management and prognosis of cardiovascular diseases resulting from the response by governments and health services to the COVID-19 pandemic. For example, in the UK and elsewhere, the numbers of people attending hospital with acute myocardial infarction and stroke have declined dramatically, while patients who do present to hospital are frequently arriving too late to receive acute treatments proven to improve outcomes (e.g., clot removal or clot busting treatments) or after preventable complications have developed. Anecdotal reports from clinicians suggest that referrals to specialist outpatient services of patients with milder symptoms (e.g., mini strokes and angina), who would benefit from treatment to reduce the risk of more serious vascular events, have also plummeted. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between countries), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

The British Heart Foundation (BHF) Data Science Centre (which is embedded within Health Data Research UK, HDR UK) is working in partnership with NHS Digital to establish a Cardiovascular Disease Trusted Research Environment (CVD TRE) [service] for England to enable analyses of linked, nationally collated healthcare datasets. This project is entitled CVD COVID UK. It will:

• Enable timely research on the effects/impacts of cardiovascular disease on COVID-19, and the direct and indirect impacts of COVID-19 on cardiovascular diseases

• Coordinate similar approaches across the four nations of the UK

• Future proof an enduring CVD TRE service post-Covid19

Coordinated by the BHF Data Science Centre, the CVD COVID UK research group which will be made up by proposes to interrogate nationally collated, population level, linked healthcare datasets across the UK population to address the following questions:

1) What are the effects of cardiovascular diseases, their risk factors and medications on susceptibility to and outcomes from COVID-19 disease?

2) What is the direct impact of SARS-CoV-2 infection on acute cardiovascular complications and on medium and longer term cardiovascular risk?

3) What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of cardiovascular diseases?

The work would be organised into work packages (WPs) as follows:

WP 1: Coordination (led by BHF Data Science Centre):

Identify relevant datasets and required dataset linkages across the UK. Coordinate applications for relevant approvals and access. Coordinate specialist inputs from cardiologists, stroke physicians, vascular surgeons and other relevant clinical groups. Coordinate reporting to SAGE and equivalent bodies in the devolved nations via established HDR UK processes.

WP 2: Analyses:

Refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses.

• WP 2.1 Indirect impact of COVID-19 on cardiovascular diseases: Time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic

• WP 2.2 Influence/associations of cardiovascular conditions on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death)

• WP 2.3 Influence/associations of cardiovascular risk factors on COVID-19 outcomes

• WP 2.4 Influence/associations of cardiovascular medications on COVID-19 outcomes

• WP 2.5 Direct impact of COVID-19 disease on cardiovascular disease occurrence, re-occurrence and outcomes in short, medium and long term

WP3: Public, patient and professional involvement and communications:

Work with existing HDR UK and BHF public, patient and professional panels to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

A consortium of organisations as listed below are the data controllers and substantive employees of these organisations will have access to the record level data within the TRE:

University College London

University of Bristol

University of Cambridge

University of Leicester

A future amendment will be made to add the following as data controllers. These organisations will not have access to the data within the TRE until the agreement has been amended:

Imperial College London

Keele University

Kings College London

London School of Hygiene and Tropical Medicine

Swansea University

University of Aberdeen

University of Dundee

University of Edinburgh

University of Leeds

University of Liverpool

University of Manchester

University of Oxford

The outputs of each piece of work will be reported to SAGE and equivalent bodies in the devolved nations as well as (especially in WP 2.4) to NICE, MHRA and Scottish Medicine Consortium, so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK and the British Heart Foundation (it is anticipated that . Outputs will inform the clinical management of patients with different types of cardiovascular disease presenting with COVID-19 disease and cardiovascular prevention strategies for patients with COVID-19 and no prior cardiovascular disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of the collaborative group (CVD-COVID-UK) with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

Yielded Benefits is not a requirement for new applications.