Health Burden of COVID-19 and Healthcare Resource Utilisation in England - INvestigation oF cOvid-19 Risk among iMmunocompromised populations

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

[34 paragraphs unchanged] - Limited to Individuals whose date of death is either null or after 1st September 2020 and who's date of birth is before 1st September 2020 Following the publication of results using year 2022 data in the Lancet Regional Health, the study aims to continue assessing the incidence rate ratios of severe COVID-19 outcomes comparing individuals with each of the immunocompromising conditions of interest versus those without. The small sample sizes for some of the subgroups (e.g., organ transplants, stem cell transplants) severely affect the precision of the estimates, resulting in very wide confidence intervals. This loss of precision is further impacted by the decreased COVID-19 incidence in 2023 and 2024, which means a larger sample size is required for years 2023 and 2024 to achieve the same level of precision in the estimates compared with in 2022. This agreement will provide this larger sample size. [20 paragraphs unchanged]

Processing activities

[37 paragraphs unchanged] 1. Restricting the number of subjects: data have been requested for a [7 words unchanged] the entire English population. Stratified sampling will be used to randomly select 25% 50% of population from each age group (i.e., 0–11, 12–17, 18–64, 65–79, ≥80 [33 words unchanged] relatively less common clinical conditions (e.g., with organ transplantation or auto-immune disease). [3 paragraphs unchanged]

Expected measurable benefits

[6 paragraphs unchanged] AMENDMENT Outputs and Benefits [1 paragraph unchanged]

Benefits reported

YIELDED BENEFITS TO DATE [26 paragraphs unchanged]

Unchanged: Expected output.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + Electronic Prescribing and Medicines Administration (EPMA) data in Secondary Care for COVID-19; + NDRS Cancer Consolidated Data Set

Objective for processing

AIM AND PURPOSE AstraZeneca UK Ltd requires access to NHS England data to generate the evidence necessary to understand the unmet need in the prevention and treatment of COVID-19 following the deployment of vaccination campaigns. The overall purpose of this study is to generate the evidence necessary to understand the unmet need in the prevention and treatment of COVID-19 following the deployment of vaccination campaigns. This may help inform the assessment and usage guidance of EVUSHELD, which is a medicine combination for prevention against and treatment of COVID-19 in the most vulnerable people. Although the overall burden of COVID-19 is declining following rollout of vaccination, certain populations like immunocompromised and elderly are still disproportionately impacted. This study continues to provide key contemporary evidence on the burden of COVID-19 in high-risk populations. Furthermore, this continues to inform the assessment and usage guidance of new generations of COVID prophylaxis and treatments,. While the original purpose of this study remains the unchanged, the evolution of the SARS-CoV-2 virus means that the nature of COVID-19 disease burden has shifted. Since the emergence of the Omicron variant, the impact of COVID-19 has reduced in the general population but continues to be significant in vulnerable individuals. To accurately describe the impact of COVID-19 in vulnerable sub-population, the INFORM study aims to analyse granular subgroups. However, given the low number of patients in these subgroups in the current sample, the descriptive tables contain many suppressed cells and consequently, the disease burden of COVID-19 remains unclear among these granular subgroups. In addition, the compulsory rounding of low values can lead to substantial under/over-representations of the data. For example, rounding to the nearest 5 when the raw value for a group is 13 introduces a 20-30% under or overrepresentation. Since obtaining access to data in the NHS secure data environment (SDE) in December 2022, the analyses have produced multiple results highlighting the ongoing impact of COVID-19 on vulnerable groups. These are examples of key insights into the magnitude of this burden and the subjects who bear the brunt of it, derived from comparing immunocompromised patients with non-immunocompromised subjects: On a similar note, patients with solid and haematological cancers remain at a high-risk of severe COVID-19 outcomes. Preliminary findings suggest that the risk of severe COVID-19 (and its impact on underlying disease) varies across cancer subtypes, disease stage at diagnosis and at the time of contracting COVID, and the type and timing of treatments received. The current data provision lacks the granularity needed to robustly assess and measure these variations. Understanding them would enable regulators, health services, physicians and patients to proactively manage these risks with data that are specific to a case’s cancer stage, subtype or treatment. These analyses require the more granular and precise data on disease at presentation and treatments for all cancer patients in the cohort, which is currently being systematically collected and cleaned the by the National Cancer Registration and Analysis Service (NCRAS) and available in the SDE. This request is therefore to include the cancer consolidated dataset compiled under the National Disease Registration Service (NDRS) in the next data update. To support this work, the project has obtained additional support and resourcing from Dr Lennard Lee, Associate professor at the University of Oxford and co-founder of the UK COVID cancer programme, thus enabling direct comparability of our project to previous work for cancer patients. - Patients with haematological malignancies undergoing active treatment had a 14-times higher risk of COVID-19 hospitalisation and 13-times higher risk of COVID-19 related death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (12-times the risk for both hospitalisation and death). The objectives are as follows; - Patients with end-stage kidney disease or on renal replacement therapy (dialysis) had 7-times higher risk of COVID-19 hospitalisation and 6-times higher risk of COVID-19 related death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (6-times the risk for hospitalisation and 5-times the risk for death). OBJECTIVE 1: To estimate the size of populations (pre-defined) in England who potentially are ineligible for vaccine or are at risk of COVID-19 infection following vaccination (remains the same) - Patients with organ transplants had 21-times higher risk of COVID-19 related hospitalisations and death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (19-times the risk for hospitalisation and 23-times the risk for death). OBJECTIVE 2: To estimate incidence of COVID-19, by age group, disease severity, and selected comorbidities (extending data access to continue assessing COVID-19 burden in the endemic phase; additional analyses and rationale are provided below) Clinical experts and other stakeholders participating in the INFORM study (INvestigation oF cOvid-19 Risk among iMmunocompromised populations. https://www.astrazeneca-us.com/media/press-releases/2023/large-real-world-evidence-studies-reveal-disproportionate-burden-of-coivd-19-on-the-immunocompromised.html) consider the findings produced thus far are crucial to support both clinical care and policy decision making. As such, in only three months since the first results started becoming available, they have been incorporated into dossiers for submission to health authorities and into scientific publications for awareness among healthcare providers, patients, and their families. More articles and abstracts for submission to peer-reviewed journals and scientific conferences, respectively, are currently in preparation and more clinical experts continue to join the study. Additionally, the indirect burden of COVID on those outcomes is also assessed in three key components: Examples where the results have been used in submissions to health authorities are: - COVID impact on underlying and/or related diseases, (eg, certain cancers, multiple sclerosis) and on other infectious and bacterial diseases (eg, acute respiratory infections, staphylococcus infections, and clostridium difficile 6-9) - MHRA - application for promising innovative medicine (PIM) / Early Access to Medicines Scheme (EAMS) - Time periods: Throughout the history of SARS-CoV-2, different variants have emerged and will continue to emerge. To obtain the most relevant estimates for healthcare professionals, researchers, and the general public, analyses will focus on more recent time periods defined by relevant and current cut-offs such as the predominance of the omicron variant, quarters or seasons in 2024, etc. For these analyses, cut-off dates for eligibility, lookback, and follow-up periods need to be redefined to generate more current estimates of COVID severe outcomes as time progresses and circumstances evolve. Examples where the results have been used in submissions to scientific publications and conferences include: - The unintended consequences of its treatments: The rollout of COVID-19 vaccines and other treatments has led to safety concerns particularly among vulnerable populations. There is therefore need to understand the background prevalence and incidence of underlying comorbidities that can also be safety concerns. Safety contextualisation has been endorsed by the regulators as an important factor in supporting preparedness activities in the evaluation of safety of COVID-19 interventions. This additional analysis will provide a framework for contextualisation of COVID-19 adverse events of special interest (AESI) by providing background risk in the general population and by age group, sex, disease severity, COVID-19 infection status, selected comorbidities and other subgroups of interest (populations at risk), as appropriate. This analysis will facilitate a more holistic assessment of the burden of COVID-19 on the general population and at-risk groups, by considering the unintended effects of COVID-19 and associated vaccines and therapies. - Acceptance of three oral presentations and three poster presentations: OBJECTIVE 3: To estimate incidence of long COVID-19 syndrome, by age, disease severity, and selected comorbidities (remains the same) Oral presentation at 19th European Geriatric Medicine Society Conference 2023: “Increased risk of severe COVID-19 outcomes in fully vaccinated older adults aged over 65 with comorbidities during Omicron predominance period: initial results from INFORM, a retrospective, observational health cohort database study in England” OBJECTIVE 4: To describe patterns of Health Care Resource Utilisation (HCRU) and cost associated with an episode of COVID-19, stratified by age, selected comorbidities, disease severity and the occurrence (vs. absence) of long COVID-19 syndrome (additional analyses and rationale are provided below) - Oral presentation at the Infectious Disease Conference 2023: “Fully Vaccinated Individuals with Immunocompromised conditions (IC) are Still at Increased Risk of Severe COVID-19 Outcomes from the Omicron Variant – Results From INFORM, a Retrospective Health Database Observational Study in England” Research suggests that apart from the direct impact of COVID-19 on HCRU and mortality, effects are also mediated by the worsening/exacerbating of pre-existing conditions (eg, increased risk of myocardial infarction or heart failure among patients with cardiovascular disease, or of exacerbations among patients with respiratory diseases).2-5 Thus, in order to assess the full burden of COVID-19 (especially in high-risk groups), deaths and other adverse outcomes for pre-existing conditions will also be assessed among patients with and without COVID-19 before, during and after the peak of the pandemic to facilitate comparisons. - Oral presentation at the Infectious Disease Conference 2023: “Increased Risk of COVID-19 Hospitalization and Death in Vaccinated Patients with End-Stage Renal Disease (ESRD) and Dialysis - Results From INFORM, a Retrospective Health Database Observational Study in England” EXPLORATORY OBJECTIVE 1: To identify patients who developed a composite outcome of COVID-19 hospitalisation or COVID-19-related death after vaccination stratified by the number of doses received and explore potential risk factors therefor (unchanged and analyses completed) - Poster presentation at the Infectious Disease Conference 2023: “- Increased Risk of Severe COVID-19 Outcomes Across all Groups of Individuals with Hematological Malignancies, Solid Tumors, and Solid Organ Transplants Compared with the General Population: Initial Results from INFORM, a Retrospective Health Database Observational Study in England EXPLORATORY OBJECTIVE 2: To develop a prediction model to identify risk profiles associated with a composite outcome of COVID-19 hospitalisation or COVID-19-related death after the deployment of vaccination campaign in England, and to estimate the prevalence of subgroups consistent with each identified risk profile (unchanged and analyses completed). - Poster presentation at the International Primary Immunodeficiencies Congress 2023: “Increased Risk of COVID-19-related Hospitalization and Mortality in Vaccinated Individuals with Primary Immunodeficiency Disease: Initial Results from INFORM, a Retrospective Study using English National Health Services Datasets” The following NHS England data will be accessed. - Poster presentation at the American Society of Nephrology 2023: “Despite Vaccination, Risks of COVID-19 Outcomes are Elevated in Patients with End-Stage Renal Disease: Initial Results from INFORM, a Study in England using the National Health Service datasets” • HES (Admitted Patient Care [APC], Critical Care, OP, Accident and Emergency)(and uncurated versions of these datasets): HES data will be used for identifying COVID-19 diagnoses, patient groups of interest, risk factors and risk profiles, and to define disease severity and describe COVID-19 HCRU. - Submission of 1 abstract still under consideration for acceptance: - Abstract submitted to British Geriatric Society Conference 2023: “Risk of severe COVID-19 increases with the number of comorbidities in fully vaccinated individuals aged ≥65: results from INFORM” - Submission of a manuscript to Lancet Regional Health-Europe “Immunocompromised populations are disproportionately impacted by COVID-19 during the Omicron era: Insights from the INFORM study” (accepted for publication) - Publication of the study protocol in the International Standard Randomised Controlled Trial Number (ISRCTN) Registry (https://doi.org/10.1186/ISRCTN53375662) Examples where the results have been used in submissions or presentations to key policy making and scientific bodies include: - UK policy and scientific bodies Data shared with key clinical consultants that advised in the McInnes Report. The report team may convene to critically look at the excellent granularity of data to further explore if more eligible populations should be added to groups that could be eligible for additional protection interventions against COVID-19 severe outcomes. The study team have consulted with several McInnes group expert advisors, and they unequivocally support wider and continuous access. These examples demonstrate the significance of this research and its expected impact on the improved care for patients with immunocompromising conditions, as robust evidence continues to underpin those clinical and policy decisions. OBJECTIVES: OBJECTIVE 1: Current research evidence on vulnerable populations that are not adequately protected by COVID-19 vaccines is fragmented. Research to understand the size and characteristics of these vulnerable populations, especially in the UK, is urgently needed. Objective 1 is to estimate the size of populations (pre-defined) in England that potentially are ineligible for vaccines or are at risk of inadequate response to COVID-19 vaccines. OBJECTIVE 2: Incident COVID-19: Given population level testing ended in the UK in early 2022, the study team now defines an incident COVID-19 case as one that requires medical attention, hospitalisation, ITU admission, or death; estimating incidence rates for hospitalisation, ITU admission and death. Time periods: Throughout the history of SARS-CoV-2, different variants have emerged and will continue to emerge. To obtain the most relevant estimates for healthcare professionals, researchers, and the general public, analyses will focus on more recent time periods defined by relevant and current cut-offs such as the predominance of the omicron variant, quarters or seasons in 2023, etc. For these analyses, cut-off dates for eligibility, lookback, and follow-up periods need to be redefined to generate more current estimates of COVID severe outcomes as time progresses and circumstances evolve. Subgroups: As the pandemic progressed, so did our understanding of risk profiles and the potential effect modifiers that require stratification of analyses. In addition to stratifying analyses by demographics, comorbidities, and vaccination status, stratification by therapies licenced for the treatment of COVID-19 will also be conducted. OBJECTIVE 3: Case definition: The scientific and clinical communities’ understanding of long COVID has evolved since this research project was first devised. Based on current evidence it is no longer accurate to characterise long COVID as a single condition. More accurately, it is likely a heterogenous group of related conditions with varying symptom predominance.1 To ascertain and describe cases of long COVID, phenotypic subgroups of long COVID-19 based on associated new diagnoses (such as arrythmia) and related HCRU (such as cardiology outpatient visits) will be identified. This will allow a more granular understanding of the burden of long COVID-19 on at-risk groups. OBJECTIVE 4: Expanded outcomes: Research suggests that apart from the direct impact of COVID-19 on HCRU and mortality, effects are also mediated by2-5: The worsening/exacerbating of pre-existing conditions (such as increased risk of myocardial infarction or heart failure among patients with cardiovascular disease, or of exacerbations among patients with respiratory diseases) In order to assess the full burden of COVID-19, especially in high-risk groups, deaths, adverse outcomes, healthcare resource use and costs for these immunocompromising and pre-existing conditions will also be assessed among patients with and without COVID-19 and over different time periods before, during and after the peak of the pandemic to facilitate comparisons. Exploratory Objective 1: Exploratory objective 1 is to identify patients who developed a composite outcome of COVID-19 hospitalisation or COVID-19-related death after vaccination, stratified by the number of doses received, and explore potential risk factors thereof. EXPLORATORY OBJECTIVE 2: As COVID-19 moves into the endemic phase, the burden of disease is becoming more confined to vulnerable subgroups, with the general population at very low risk of severe outcomes. For this reason, machine learning analyses will primarily focus on individuals at a higher risk of severe COVID-19 outcomes. This will allow the identification of high-risk clusters amongst the population most affected by COVID-19. Additional Analysis: Given the extent of the pandemic, with most of the UK having been infected at least once, it is likely that SARS-CoV-2 has impacted other infectious and bacterial diseases such as acute respiratory infections, staphylococcus infections, and clostridium difficile.6-9. As such, impact of SARS-CoV-2 on the incidence of these infections will be assessed over time, before and during the pandemic, with an assessment of whether the characteristics of patients infected with these pathogens have changed over the course of the pandemic. To develop a comprehensive account of the burden of a disease, it is important to also examine the unintended consequences of its treatments. Contextualisation has been endorsed by the regulators as an important factor in supporting preparedness activities in the evaluation of safety of COVID-19 products. This additional study objective will provide a framework for contextualisation of adverse events of special interest (AESIs); not only known and potential risks but also any unexpected risks that may arise during COVID-19 product development or after licensure. This additional objective will facilitate estimation of incidence and prevalence rates of AESIs by calendar year over the pre-, during and post-pandemic period, in the general population and by age group, sex, disease severity, COVID-19 infection status, selected comorbidities and other subgroups of interest (populations at risk), as appropriate. This analysis will facilitate a more holistic assessment of the burden of COVID-19 on the general population and at-risk groups, by considering the unwanted effects of therapies. CONTROLELRSHIP: AstraZeneca UK Ltd is the data controller for the study. AZ has been determined to be the data controller, in line with the General Data Protection Regulation definition of data controller which states they are the natural or legal person, public authority, agency or any other body who determines the purposes and means of processing the data [1]. AstraZeneca UK Ltd holds the ultimate decision on how the study should be designed and data should be analysed and as such are listed as Data Controller. They also have, in line with UK GDPR requirements, a) a valid data sharing framework contract, b) adequate security assurance and c) have paid the relevant data protection fee to ICO. [1] https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/controllers-and-processors/what-are-controllers-and-processors/ The aim and objectives are determined by AstraZeneca UK Ltd. AstraZeneca is the sole funder/sponsor for this study. Evidera has been contracted by AstraZeneca UK Ltd to conduct this piece of research, acting as the sole data processor. There are no sub-licences or onwards sharing and therefore, Evidera will be the only entity to process the data. LAWFUL BASIS: Justification of the processing of data AstraZeneca UK Ltd’s lawful basis for processing data under the UK General Data Protection Regulations (UK GDPR) is Article 6(1)(f): “Legitimate interests: the processing is necessary for your legitimate interests or the legitimate interests of a third party, unless there is a good reason to protect the individual’s personal data which overrides those legitimate interests.” Processing personal data is necessary for AstraZeneca’s legitimate interests. The pseudonymised data to which access is requested are proportionate and necessary to achieve those interests. AstraZeneca has completed a legitimate interests assessment (LIA) and is satisfied that the interests of the data subjects do not override AstraZeneca’s legitimate interests; that they would reasonably expect the processing and it would not cause unjustified harm. Additionally, AstraZeneca processes the Special Category Health Data under UK GDPR Article 9(2)(j): "processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject" as the data are required for research purposes in the public interest. COMMERCIAL ELEMENT: The commercial interests of AstraZeneca (AZ) in this project are to better understand unmet needs for research and development purposes, as well as to provide evidence requested by health authorities for the assessment of EVUSHELD and other of COVID prophylaxis and treatments. However, potential indirect benefits of the project to AZ might include: a) if there is a reduction of the number of COVID-19 cases across the study period, AZ can assume that this was partly due to their vaccination programme, since AZ was one of the biggest COVID-19 vaccination suppliers during the pandemic; b) if there is a huge unmet need identified (i.e., many individuals that are ineligible for COVID-19 vaccinations and/or many individuals still at risk for COVID-19, then NICE might be more likely to approve alternative therapies that could be used to treat these groups of patients, if these therapies are shown to be beneficial in clinical trial data and c) Evidera will benefit since they will deepen their knowledge of COVID-19 observational research and therefore additional clients might be more likely to approach them based on their experience in this field. This study also is part of a wider research project that will also generate evidence on the effectiveness and safety of EVUSHELD in routine clinical practice. The next phases of this project will be launched following the administration of the initial doses in prevention and treatment indications. AZ are developing a number of therapies for COVID-19 (including research around EVUSHELD) and therefore payers like NICE and the NHS may more likely approve/reimburse these therapies based on the outputs of this study that would result in financial benefits for AZ. DATA: The requested data are pseudonymised and there is no or minimal risk of patient re-identification. A minimum threshold of five patients will be used for primary and secondary cell suppression in all result-dissemination activities and materials, to secure patients' information is protected as much as possible. The list of datasets requested and justifications for the request are listed below: • HES (Admitted Patient Care [APC], Critical Care, OP, Accident and Emergency): HES data will be used for identifying COVID-19 diagnoses, patient groups of interest, risk factors and risk profiles, and to define disease severity and describe COVID-19 HCRU. Data from 1 September 2015 to present (including baseline and follow-up period) are requested. [9 paragraphs unchanged] • Electronic Prescribing and Medicines Administration (ePMA) will increase the identification of this population of interest and also allow a more holistic analysis of HCRU and associated costs. [1 paragraph unchanged] References • NDRS Cancer Consolidated data- diagnosis information is missing for ~99% of HES outpatient records and ~93% A&E records. AZ frequently relies on diagnosis information in the GP records and hospital admissions to capture cancer population. These data will provide diagnosis and treatment information to characterise cancer subtype, stage, and treatments. 1. Reese JT, Blau H, Casiraghi E, et al. Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes. EBioMedicine. 2023;87:104413. doi:10.1016/j.ebiom.2022.104413. Patients with solid and haematological cancers are at a heightened risk of severe COVID-19 outcomes, and the risk is likely to differ significantly by cancer subtype, disease stage, and treatment (https://doi.org/10.1016/ S1470-2045(22)00202-9). The NDRS Cancer Consolidated Dataset will help improve the identification of cancer populations, characterise their disease (e.g., by stage, subtype) and understand the variations in COVID-19 outcomes among cancer subpopulations. 2. Vasbinder A, Meloche C, Azam TU, et al. Relationship Between Preexisting Cardiovascular Disease and Death and Cardiovascular Outcomes in Critically Ill Patients With COVID-19. Circ Cardiovasc Qual Outcomes. 2022;15(10):e008942. doi:10.1161/CIRCOUTCOMES.122.008942. The level of data will be pseudonymised 3. Bilotta C, Perrone G, Adelfio V, et al. COVID-19 Vaccine-Related Thrombosis: A Systematic Review and Exploratory Analysis. Front Immunol. 2021;12:729251. doi:10.3389/fimmu.2021.729251. The data will be minimised as follows. 4. Paul P, Janjua E, AlSubaie M, et al. Anaphylaxis and Related Events Following COVID-19 Vaccination: A Systematic Review. J Clin Pharmacol. 2022;62(11):1335-1349. doi:10.1002/jcph.2120. - Limited to data between 2015 to latest available 5. Bhandari B, Rayamajhi G, Lamichhane P, Shenoy AK. Adverse Events following Immunization with COVID-19 Vaccines: A Narrative Review. Biomed Res Int. 2022;2022:2911333. doi:10.1155/2022/2911333. - Limited to 50% of the English population 6. Chow EJ, Uyeki TM, Chu HY. The effects of the COVID-19 pandemic on community respiratory virus activity. Nature Reviews Microbiology. 2023;21(3):195-210. doi:10.1038/s41579-022-00807-9. - Limited to Individuals whose date of death is either null or after 1st September 2020 7. Voona S, Abdic H, Montgomery R, et al. Impact of COVID-19 pandemic on prevalence of Clostridioides difficile infection in a UK tertiary centre. Anaerobe. 2022;73:102479. doi:10.1016/j.anaerobe.2021.102479. The lawful basis for processing personal data under the UK GDPR is: 8. Sipos S, Vlad C, Prejbeanu R, et al. Impact of COVID-19 prevention measures on Clostridioides difficile infections in a regional acute care hospital. Exp Ther Med. 2021;22(5):1215. doi:10.3892/etm.2021.10649. Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party. 9. Dar S, Erickson D, Manca C, et al. The impact of COVID on bacterial sepsis. European Journal of Clinical Microbiology & Infectious Diseases. 2023;doi:10.1007/s10096-023-04655-0. Processing personal data is necessary for AstraZeneca’s legitimate interests. The pseudonymised data to which access is requested are proportionate and necessary to achieve those interests. AstraZeneca has completed a legitimate interests assessment (LIA) and is satisfied that the interests of the data subjects do not override AstraZeneca’s legitimate interests; that they would reasonably expect the processing and it would not cause unjustified harm. The lawful basis for processing special category data under the UK GDPR is: Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject. AstraZeneca UK Ltd is the sponsor and the controller organisation responsible for ensuring the data will be processed for the purpose described above The funding is provided by AstraZeneca UK Ltd. Evidera has been contracted by AstraZeneca UK Ltd to conduct this piece of research, acting as the sole data processor, Evidera will be the only entity to process the data. The commercial interests of AstraZeneca (AZ) in this project are to better understand unmet needs for research and development purposes, as well as to provide evidence requested by health authorities for the assessment of EVUSHELD and other of COVID prophylaxis and treatments. However, potential indirect benefits of the project to AZ might include: a) if there is a reduction of the number of COVID-19 cases across the study period, AZ can assume that this was partly due to their vaccination programme, since AZ was one of the biggest COVID-19 vaccination suppliers during the pandemic; b) if there is a huge unmet need identified (i.e., many individuals that are ineligible for COVID-19 vaccinations and/or many individuals still at risk for COVID-19, then NICE might be more likely to approve alternative therapies that could be used to treat these groups of patients, if these therapies are shown to be beneficial in clinical trial data and c) Evidera will benefit since they will deepen their knowledge of COVID-19 observational research and therefore additional clients might be more likely to approach them based on their experience in this field. This study also is part of a wider research project that will also generate evidence on the effectiveness and safety of EVUSHELD in routine clinical practice. The next phases of this project will be launched following the administration of the initial doses in prevention and treatment indications. AZ are developing a number of therapies for COVID-19 (including research around EVUSHELD) and therefore payers like NICE and the NHS may more likely approve/reimburse these therapies based on the outputs of this study that would result in financial benefits for AZ. AZ engages with immunocompromised patients, who are considered to not been adequately protected by COVID-19 vaccines due to their body unable to generate an optimal level of antibodies, to provide feedback on the current and future studies. Patients will provide input during study analysis planning, first results readout and publications. Through the AstraZeneca Patient Centric Group, the study team sought advice and feedback from patients during the protocol and analysis plan development with a focus on targeted populations and outcome definition. At the end of the study, a feedback session is planned to present the study findings to patients Commerical Purpose: Evidera is a business within Pharmaceutical Product Development LLC (PPD), a leading global contract research organisation. Evidera has been contracted by and received funding from AstraZeneca UK Ltd to conduct the current research project. The contracted services include drafting the study protocol and SAP and finalising these according to the review comments received from AstraZeneca, data preparation, data analysis, results reporting and dissemination. There are no other known conflicts of interest. AstraZeneca UK Ltd co-created one of the COVID-19 vaccines which has been widely deployed during the COVID-19 pandemic. The research conducted will not be tied to a specific treatment and therefore there are no expected direct benefits expected to AstraZeneca or Evidera. However, indirect benefits might include: • If the study identifies a reduction in incidence rates since the deployment of COVID-19 vaccination programme, AstraZeneca may benefit from this research demonstrating the benefits of COVID-19 vaccines given AstraZeneca is one of the biggest COVID-19 vaccine suppliers. • If the study identifies there is an unmet need (i.e., many individuals ineligible for the COVID-19 vaccine and/or many individuals still at risk for COVID-19 outcomes), then the NICE might be more likely to approve alternative/additional treatments for COVID-19 as the improvement in health among these affected COVID-19 patients could be substantial, depending on findings from clinical trials. NICE assesses whether the approval of new therapies should be used in the NHS. AstraZeneca has developed or is developing a number of therapies for COVID-19 and therefore payers (NICE/NHS) might be more likely to approve or reimburse these therapies based on this information. • Evidera will benefit from this research since it will deepen its knowledge of COVID-19 observational research and therefore other clients (i.e., pharmaceutical companies) will be more likely to approach them for this type of research. It is also benefitting from the study since AstraZeneca is paying Evidera to conduct the research on its behalf. The primary focus of this study is to enhance understanding of individuals who are ineligible or suboptimal responders of the Oxford-AstraZeneca vaccine that is being administered globally. The incidence of COVID-19 will be assessed as well as the impact COVID-19 has had on the English healthcare system. Results of the studies may identify the unmet needs of the current COVID-19 vaccines being delivered. The commercial interests of AstraZeneca in this project are to better understand unmet needs for research and development purpose. The potential public benefits to healthcare in England are considered to outweigh the potential commercial benefit. AstraZeneca UK Ltd will not suppress findings or receive exclusive access to findings. AZ are developing a number of therapies for COVID-19 (including research around EVUSHELD) and therefore payers like NICE and the NHS may more likely approve/reimburse these therapies based on the outputs of this study that would result in financial benefits for AZ.

Processing activities

There No data will be no flow of data into to NHS England for the purposes of this Data Sharing Agreement (DSA). NHS England will allow Evidera, as AZ data processor, access via NHS England’s Secure Data Environment (SDE) to pseudonymised NHS England will grant access to the Data via the Secure Data Environment (SDE). The SDE is a secure data and research analysis platform. It allows approved researchers with approved projects access to pseudonymised data and industry-leading analytics tools. - HES (APC, ACC, OP, Accident and Emergency); NHS England will provide access to the relevant records from the HES, Emergency Care, Deaths, COVID-19 SGSS, COVID-19 Vaccination Status, GPES GDPPR, Civil Registrations of Deaths, NHSBSA, NDRS Cancer Consolidated dataset and ePMA datasets to Evidera Ltd via NHS England Secure Data Environment (SDE). The Data will contain no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient. - COVID-19 SGSS data; The Data will not be transferred to any other location. - COVID-19 Vaccination Status data; SDE users can request exportation of aggregated analysis results (suppressed and summarised according to the NHSE SDE Disclosure Control rules) subject to review and approval by the NHS England SDE Output Checking team. The SDE Output Checking team will ensure that no output contains information which could be used either on its own or in conjunction with other data to breach an individual's privacy. - Civil Registration – Deaths data; Users must identify themselves via a multi-factor authentication mechanism and are only able to access the datasets detailed within this DSA. The access and use of the system is fully auditable, and all users must comply with the use of the Data as specified in this DSA. - GDPPR Users are only authorised to access the Data specified in this DSA and can utilise a variety of analytical tools available within the SDE platform. Users are not permitted to export record-level data from the SDE. The Data will be stored on servers at NHS England. The Data will be accessed by authorised personnel via remote access. The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract. For remote access: - Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA; - Access controls granting users the minimum level of access required are in place; - Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data; - Multifactor authentication (MFA) is required for remote access; - Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access; - All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy. The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose). Remote processing will be from secure locations within England/Wales. The data will not leave England/Wales at any time. [2 paragraphs unchanged] For GPES GDPPR: [7 paragraphs unchanged] For HES and Mortality data: To protect patient confidentiality, when presenting results calculated from HES record-level data, outputs will contain only aggregate-level data with small numbers suppressed in line with HES Analysis Guide: For HES and Mortality data: To protect patient confidentiality, when presenting results calculated from HES record-level data, outputs will contain only aggregate-level data with small numbers suppressed in line with HES Analysis Guide: [4 paragraphs unchanged] DATA MINIMISATION: Data minimisation efforts were applied to all dimensions of the request as follows: Data minimisation efforts in the current application were applied to all dimensions of the request as follows: [4 paragraphs unchanged]

Expected output

Outputs from this project are expected to be published throughout 2024. 2024 and 2025. Evidera will be conducting all of the data processing and the analysis [77 words unchanged] be provided for each risk factor), the number of new COVID-19 infections requiring medical attendance and incidence of COVID-19 requiring medical attendance/hospitalisation overall and in each time period of interest, the number of new long COVID-19 infections and incidence of long COVID-19, the rate of resource utilisation per patient and per-patient [20 words unchanged] be presented in a study report and sent to AZ for review. Additional results for this study are expected within a year following the extended access to the NHS England-linked datasets. [1 paragraph unchanged] In addition, the study team has an active engagement with charity organisations including the and research communities (King’s College London, COVID Symptom Study Team) for topics like Long COVID is planned. Team). AZ intend to work with Long-COVID clinics in the country to identify [58 words unchanged] will provide input during study analysis planning, first results readout and publications. [2 paragraphs unchanged] These planned outputs will be designed with the intention of including sufficient [47 words unchanged] patients with COVID or long-COVID. The case definition refers to how cases (i.e., COVID and long COVID-19) (eg, COVID) are defined and identified from the requested datasets. The proposed study is descriptive in nature, e.g., estimating the size of populations that are not protected by COVID-19 vaccines. The incidence of COVID-19 and long COVID-19, and COVID-19-related healthcare service use, as opposed to estimating the effectiveness of certain treatments/vaccines. The aim is to understand the current health and economic burden of COVID-19. nature. The plan is to publish results regardless of whether the estimates are high or low.. low. COVID-19 research results need to and will be interpreted in the wider context, e.g., social restrictions and movement, infection rate, vaccination/booster roll-out and availability of an-viral treatments. This study is also exploring whether machine learning based methods can help with identifying risk profiles of vaccinated patients who experienced a composite outcome of COVID-19 hospitalisation or COVID-19-related death. As previously mentioned, machine learning methods will first identify all patients that have a COVID-19 hospitalisation or COVID-19 related death after 14 days of a COVID-19 vaccination (i.e., break through infections). Then clustering methods and supervised learning with nested cross-validation will be used to classify these patients into k clusters with similar characteristics. These results, details on the development of algorithms and lessons learned are also planned to be disseminated.

Expected measurable benefits

As SARS-CoV-2 has evolved, the burden of the disease and therapies to treat COVID-19 have also evolved. Since the original application was approved, AstraZeneca continued to develop new generations of their COVID-19 prophylaxis and treatment, EVUSHELD, including an investigational next generation long-acting antibody AZD3152 (NCT05648110). Results of these analyses hopes to allow policy makers, healthcare professionals, and patients to obtain a more granular and personalised understanding of the risk of severe COVID-19 outcomes, which accounts for comorbidities, treatments, age, and other relevant variables. This information will be made public through manuscript submissions and conference presentations. Benefits from this study are expected to include the following Benefits from this study are expected to include the following: 1. Benefits for regulators (e.g., MHRA): the findings from this study are hoped will support MHRA’s review of AZD3152 and other COVID-19 prophylaxis and treatments for the use among patients who are immunocompromised and other vulnerable populations to supplement the trial evidence, based on which the Conditional Marketing Authorisation in PrEP (pre-exposure prophylaxis) was granted. Furthermore, the results of this study will provide a baseline against which to benchmark the overall impact of the potential use of AZD3152, until data accrual and maturity allow for a contemporaneous comparative effectiveness and safety assessment, following the administration of sufficient doses. Additionally, should the respective clinical trials confirm AZD3152’s safety and efficacy in outpatient and inpatient treatment indications, the results of this study will serve as foundation for the development of the submission dossier to ascertain the most accurate characterisation of the source population in England. 1. Benefits for regulators (e.g., MHRA): the findings from this study are hoped will support MHRA’s review of EVUSHELD and other COVID-19 prophylaxis and treatments for the use among patients who are immunocompromised and other vulnerable populations to supplement the trial evidence, based on which the Conditional Marketing Authorisation in PrEP (pre-exposure prophylaxis) was granted. Furthermore, the results of this study will provide a baseline against which to benchmark the overall impact of the use of EVUSHELD, until data accrual and maturity allow for a contemporaneous comparative effectiveness and safety assessment, following the administration of sufficient doses. Additionally, should the respective clinical trials confirm EVUSHELD’s safety and efficacy in outpatient and inpatient treatment indications, the results of this study will serve as foundation for the development of the submission dossier to ascertain the most accurate characterisation of the source population in England. 2. It is anticipated that there will be benefits for Health Technology Assessment and endorsement bodies such as NICE and the Scottish Medicines Consortium (SMC): During the early scientific advice procedure in which AstraZeneca engaged, NICE requested more accurate information on the expected number of patients that would be eligible for EVUSHELD and other COVID-19 therapies. NICE also recommended that AstraZeneca conduct an observational study to continue identifying which populations do not respond to vaccinations, beyond patients who are immunocompromised, and expressed concern for the dynamic landscape due to the emergence of new variants, which should also be monitored. Lastly, NICE requested that the health-economic model be populated with efficacy data from the phase III trial PROVENT (NCT04625725, please see - https://clinicaltrials.gov/ct2/show/NCT04625725) but the baseline characteristics be adjusted to more accurately reflect the population in England as well as account for the substantial heterogeneity likely to exist in the target population (e.g., in terms of comorbidities, resource use, risk of severe COVID-19). These are the exact research questions that guided the design of the current study. The results from objectives 2 and 3 will be used to adjust the population characteristics for the cost-effectiveness model. Additionally, the patterns of HCRU and costs associated with an episode of COVID-19 will be an important input for the cost-effectiveness model. The accurate count of patients at risk from objective 1 will also be used in the budget impact model. The exploratory objectives to identify and quantify risk profiles with high unmet clinical need will be the basis for sensitivity analyses in both health-economic models. Furthermore, as the pandemic becomes endemic, regulators and policy makers will also benefit from country-specific estimates on the burden of long-COVID-19 to patients and to the healthcare system to be factored in policy decisions. 2. Its is anticipated there will be benefits for Health Technology Assessment (HTA) and endorsement bodies such as NICE and the Scottish Medicines Consortium (SMC): During the early scientific advice procedure in which AstraZeneca engaged, NICE requested more accurate information on the expected number of patients that would be eligible for EVUSHELD and other COVID-19 therapies. NICE also recommended that AstraZeneca conduct an observational study to continue identifying which populations do not respond to vaccinations, beyond patients who are immunocompromised, and expressed concern for the dynamic landscape due to the emergence of new variants, which should also be monitored. Lastly, NICE requested that the health-economic model be populated with efficacy data from the phase III trial PROVENT (NCT04625725, please see - https://clinicaltrials.gov/ct2/show/NCT04625725) but the baseline characteristics be adjusted to more accurately reflect the population in England as well as account for the substantial heterogeneity likely to exist in the target population (e.g., in terms of comorbidities, resource use, risk of severe COVID-19). These are the exact research questions that guided the design of the current study. 3. It is anticipated that there will be benefits for the UK Department of Health and Social Care, clinicians, and healthcare providers: The wide-spread vaccination of the British population has significantly improved the epidemiological situation, thus reducing its pressure on the limited healthcare resources and allowing to plan and act proactively (as opposed to reactively, like during the worst moments of the pandemic). To appropriately plan for the management and administration of resources all agents in the continuum of the healthcare provision will benefit from understanding the nature and magnitude of the outstanding unmet needs in the prevention and treatment of COVID-19. This study will provide these insights. Furthermore, the supply of additional prophylaxis to address some of these needs is expected to be targeted. This study will also provide the evidence on the populations to target to inform those decisions. The results from objectives 2 and 3 will be used to adjust the population characteristics for the cost-effectiveness model. Additionally, the patterns of HCRU and costs associated with an episode of COVID-19 will be an important input for the cost-effectiveness model. The accurate count of patients at risk from objective 1 will also be used in the budget impact model. The exploratory objectives to identify and quantify risk profiles with high unmet clinical need will be the basis for sensitivity analyses in both health-economic models. Furthermore, as the pandemic becomes endemic, regulators and policy makers will also benefit from country-specific estimates on the burden of long-COVID-19 to patients and to the healthcare system to be factored in policy decisions. In order to influence benefits for the health and social care system, the study team will require additional data for a wider cohort to publish outputs from the INFORM study, and support ongoing submissions to HTA and endorsement bodies including NICE, more granular data are required to facilitate the characterization of risk in rare subgroups. 3. It is anticipated that there will be benefits for the UK Department of Health and Social Care, clinicians, and healthcare providers: The wide-spread vaccination of the British population has significantly improved the epidemiological situation, thus reducing its pressure on the limited healthcare resources and allowing to plan and act proactively (as opposed to reactively, like during the worst moments of the pandemic). To appropriately plan for the management and administration of resources all agents in the continuum of the healthcare provision will benefit from understanding the nature and magnitude of the outstanding unmet needs in the prevention and treatment of COVID-19. This study will provide these insights. Furthermore, the supply of EVUSHELD to address some of these needs is limited and it is expected that doses will become available in consecutive batches, which means that priorities will need to be established based on formal criteria. This study will also provide the evidence to inform those decisions. [2 paragraphs unchanged] AMENDMENT Outputs and Benefits As SARS-CoV-2 has evolved, the burden of the disease and therapies to treat COVID-19 have also evolved. Since the original application was approved, AstraZeneca continued to develop new generations of their COVID-19 prophylaxis and treatment, EVUSHELD, including an investigational next generation long-acting antibody AZD3152 (NCT05648110). It is expected that the larger sample size will enable the generation of real world evidence (RWE) that supplement and augment trial data, in a similar fashion to that outlined for EVUSHELD in the original application. The increased sample size and detailed information on cancer patients will allow for a more reliable estimate in smaller at-risk populations. Broadening the outcomes to look at healthcare resource use for other comorbidities that may worsen due to COVID-19 will also help fill evidence gaps on the wider burden for COVID-19. Results of these analyses will allow policy makers, healthcare professionals, and patients to obtain a more granular and personalised understanding of the risk of severe COVID-19 outcomes, which accounts for comorbidities, treatments, age, and other relevant variables. This information will be made public through manuscript submissions and conference presentations.

Benefits reported

The findings of the study thus far have proved to be crucial to support both clinical care and policy decision making. In only three months since the first results started becoming available, they have been incorporated into dossiers for submission to health authorities and into scientific publications for awareness among healthcare providers, patients, and their families. YIELDED BENEFITS TO DATE Since obtaining access to data in the NHS secure data environment (SDE) in December 2022, the analyses have produced multiple results highlighting the ongoing impact of COVID-19 on vulnerable groups. These are examples of key insights into the magnitude of this burden and the subjects who bear the brunt of it, derived from comparing immunocompromised patients with non-immunocompromised subjects: - Patients with haematological malignancies undergoing active treatment had a 14-times higher risk of COVID-19 hospitalisation and 13-times higher risk of COVID-19 related death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (12-times the risk for both hospitalisation and death). - Patients with end-stage kidney disease or on renal replacement therapy (dialysis) had 7-times higher risk of COVID-19 hospitalisation and 6-times higher risk of COVID-19 related death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (6-times the risk for hospitalisation and 5-times the risk for death). - Patients with organ transplants had 21-times higher risk of COVID-19 related hospitalisations and death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (19-times the risk for hospitalisation and 23-times the risk for death). - The study has confirmed the continued risk for severe COVID-19 outcomes in UK vulnerable populations as identified by the Professor McInnes Report which advised the UK Government. Further, potentially expansion populations not highly prioritised by the McInnes report were identified. Clinical experts and other stakeholders participating in the INFORM study consider the findings produced thus far are crucial to support both clinical care and policy decision making. As such, data from the INFORM study has been incorporated into dossiers for submission to health authorities and into scientific publications for awareness among healthcare providers, patients, and their families. Examples where the results have been used in submissions to health authorities are: - MHRA - application for promising innovative medicine (PIM) / Early Access to Medicines Scheme (EAMS) - The burden of disease data from the INFORM study is continually being presented as the basis for global burden of disease in the context of vaccination and emerging SARS-CoV-2 variants. This led to recent data being used in dossiers with the US FDA, EMA. -In the UK, the INFORM study continues to be a key source of identifying at-risk populations and frequency of severe outcomes to aid patient access discussions with NICE for several pharmaceutical COVID-19 drugs unrelated to AstraZeneca. This data has been accepted as a reliable source for assessing severe COVID-19 outcomes in England. Examples where the results have been used in submissions or presentations to key policy making and scientific bodies include: - UK policy and scientific bodies: Data shared with key clinical consultants that advised in the McInnes Report. The report team may convene to critically look at the excellent granularity of data to further explore if more eligible populations should be added to groups that could be eligible for additional protection interventions against COVID-19 severe outcomes. The study team have consulted with several McInnes group expert advisors, and they unequivocally support wider and continuous access. Examples where the results have been used in submissions to scientific publications and conferences include one manuscript publication and 10+ conference oral/poster presentations: - Publication of the study protocol in the International Standard Randomised Controlled Trial Number (ISRCTN) Registry (https://doi.org/10.1186/ISRCTN53375662) - Manuscript publication in Lancet Regional Health-Europe “Immunocompromised populations are disproportionately impacted by COVID-19 during the Omicron era: Insights from the INFORM study” [1 paragraph unchanged] - Two poster presentations and one oral presentation at European Congress of Clinical Microbiology and Infectious Diseases 2024: “Healthcare resource use and overall costs of COVID-19 during the Omicron predominant period in immunocompromised individuals: results from INFORM, a retrospective health database observational study in England”; “Continued increased risk of COVID-19 hospitalisation and death in immunocompromised individuals despite receipt of ≥4 vaccine doses: updated 2023 results from INFORM, a retrospective health database observational study in England”; “Individuals with multiple sclerosis are at high risk for COVID-19 hospitalization and death despite high rates of vaccination: results from the England INFORM study” - Oral presentation at 19th European Geriatric Medicine Society Conference 2023: “Increased risk of severe COVID-19 outcomes in fully vaccinated older adults aged over 65 with comorbidities during Omicron predominance period: initial results from INFORM, a retrospective, observational health cohort database study in England” - Oral presentation at the Infectious Disease Conference 2023: “Fully Vaccinated Individuals with Immunocompromised conditions (IC) are Still at Increased Risk of Severe COVID-19 Outcomes from the Omicron Variant – Results From INFORM, a Retrospective Health Database Observational Study in England” - Oral presentation at the Infectious Disease Conference 2023: “Increased Risk of COVID-19 Hospitalization and Death in Vaccinated Patients with End-Stage Renal Disease (ESRD) and Dialysis - Results From INFORM, a Retrospective Health Database Observational Study in England” - Poster presentation at the Infectious Disease Conference 2023: “- Increased Risk of Severe COVID-19 Outcomes Across all Groups of Individuals with Hematological Malignancies, Solid Tumors, and Solid Organ Transplants Compared with the General Population: Initial Results from INFORM, a Retrospective Health Database Observational Study in England - Poster presentation at the International Primary Immunodeficiencies Congress 2023: “Increased Risk of COVID-19-related Hospitalization and Mortality in Vaccinated Individuals with Primary Immunodeficiency Disease: Initial Results from INFORM, a Retrospective Study using English National Health Services Datasets” - Poster presentation at the American Society of Nephrology 2023: “Despite Vaccination, Risks of COVID-19 Outcomes are Elevated in Patients with End-Stage Renal Disease: Initial Results from INFORM, a Study in England using the National Health Service datasets” - Poster presentation at the British Geriatric Society Conference 2023: “Risk of severe COVID-19 increases with the number of comorbidities in fully vaccinated individuals aged ≥65: results from INFORM” - Oral presentation at the European Union Geriatric Medicine Society 2023: “Increased risk of severe COVID-19 outcomes in fully vaccinated older adults aged over 65 with comorbidities during Omicron predominance period: initial results from INFORM, a retrospective, observational health cohort database study in England” These examples demonstrate the significance of this research and its expected impact on the improved care for patients with immunocompromising conditions, as robust evidence continues to underpin those clinical and policy decisions. Yet, sample size and processing capacity currently hinder certain crucial analyses, which warrant this amendment application.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Data controllers: − NHS ENGLAND

Objective for processing

[2 paragraphs unchanged] The justifications for the proposed study are: Since obtaining access to data in the NHS secure data environment (SDE) in December 2022, the analyses have produced multiple results highlighting the ongoing impact of COVID-19 on vulnerable groups. These are examples of key insights into the magnitude of this burden and the subjects who bear the brunt of it, derived from comparing immunocompromised patients with non-immunocompromised subjects: (1) Current research evidence on vulnerable populations that are not adequately protected by COVID-19 vaccines is fragmented. Research to understand the size and characteristics of these vulnerable populations, especially in the UK, is urgently needed. - Patients with haematological malignancies undergoing active treatment had a 14-times higher risk of COVID-19 hospitalisation and 13-times higher risk of COVID-19 related death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (12-times the risk for both hospitalisation and death). (2) EVUSHELD is an medicine that has been authorised for COVID-19 prevention in the US, UK and many other countries. This product offers (added) protection against COVID-19 for those who are ineligible for COVID-19 vaccines (e.g., severe allergic reaction) or moderately to severely immunocompromised (because their body does not respond well to vaccines to generate an adequate level of antibodies). Regulatory and health assessment agencies (e.g., Medicines and Healthcare Products Regulatory Agency [MHRA], National Institute for Health and Care Excellence [NICE]) require additional real-world evidence to supplement and augment trial data, with the understanding of the magnitude of health and economic burden of COVID-19 on these patients as the first step. This additional information may help relevant agencies inform decisions on priorities among these populations, anticipating health expenditure, and providing guidance on EVUSHELD usage. - Patients with end-stage kidney disease or on renal replacement therapy (dialysis) had 7-times higher risk of COVID-19 hospitalisation and 6-times higher risk of COVID-19 related death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (6-times the risk for hospitalisation and 5-times the risk for death). (3) Considerable research efforts have been devoted to studying the individual risk factors associated with breakthrough infection (e.g., infection despite of vaccination) and/or poor COVID-19 outcomes. However, it is not well understood how the presence or combination of different risk factors may place patients at a greater risk of poor COVID-19 outcomes. This study will leverage machine learning methods and use a data-driven approach to identify clusters of patients who experience severe COVID-19 outcomes following the national vaccination programme. - Patients with organ transplants had 21-times higher risk of COVID-19 related hospitalisations and death, after adjusting for age and sex. The risk remained high even among those with three or more vaccine doses (19-times the risk for hospitalisation and 23-times the risk for death). Firstly, amongst patients that experience a COVID-19 hospitalisation or COVID-19 related death after 14 days of a COVID-19 vaccination (i.e., breakthrough infections), a clustering algorithm (e.g., k-means) will be used to identify patients that exhibit similar characteristics. Then, tree-based supervised learning methods (e.g., random forest and gradient boosting machine) will be applied with nested cross-validation to train models that can be used for classifying patients into the identified k clusters and to test their performance. Clinical experts and other stakeholders participating in the INFORM study (INvestigation oF cOvid-19 Risk among iMmunocompromised populations. https://www.astrazeneca-us.com/media/press-releases/2023/large-real-world-evidence-studies-reveal-disproportionate-burden-of-coivd-19-on-the-immunocompromised.html) consider the findings produced thus far are crucial to support both clinical care and policy decision making. As such, in only three months since the first results started becoming available, they have been incorporated into dossiers for submission to health authorities and into scientific publications for awareness among healthcare providers, patients, and their families. More articles and abstracts for submission to peer-reviewed journals and scientific conferences, respectively, are currently in preparation and more clinical experts continue to join the study. SHapely Additive exPlanations (SHAP) values will be used to explain the output of the machine learning model. The final, trained models will be applied to the study population and each individual will be classified into one of the k clusters. Within each cluster, the number (%) of patients who have experienced the composite outcome of interest will be tabulated. The clusters with a high percentage of patients experiencing the composite outcome are considered to be the groups at high risk of breakthrough COVID-19 hospitalisation or COVID-19-related death. Examples where the results have been used in submissions to health authorities are: Details on these justifications are provided as follows: - MHRA - application for promising innovative medicine (PIM) / Early Access to Medicines Scheme (EAMS) The key vulnerable populations that are not well protected by existing vaccines are those who are immunocompromised, either due to underlying medical conditions (e.g., autoimmune diseases) or treatment (e.g., chemotherapy drugs for cancer treatment, immunosuppressants after organ transplantation). Research has shown that these patients have suboptimal immunological response to vaccines—their bodies are unable to generate an adequate level of antibodies following vaccination. Therefore, they have a higher risk of SARS-CoV-2 infection and experience increased disease burden and poor COVID-19 outcomes compared with other populations. Considerable research efforts have been devoted to analyse these specific vulnerable groups and specific risk factors for breakthrough infection and/or poor COVID-19 outcomes, though the evidence is fragmented due to heterogeneity (encompassing several different types of conditions and treatments) and multi-comorbidities. Uncertainty remains around risk profiles that have not been robustly ascertained or validated, and the actual size of the population that would benefit from EVUSHELD in prophylaxis and/or treatment indications, as well as the burden averted by its use, remain unknown. Examples where the results have been used in submissions to scientific publications and conferences include: On 17 March 2022, EVUSHELD became the first medicine authorised for COVID-19 prevention in vulnerable populations (i.e., ineligible for COVID-19 vaccines, or with sub-optional response to COVID-19 vaccines) by the UK MHRA. After meeting the UK regulatory standards of safety, quality, and effectiveness, the MHRA issued a Conditional Marketing Authorisation (CMA) in Great Britain. The decision was endorsed by the government’s Commission on Human Medicines, after carefully reviewing the evidence generated in several clinical trials conducted to assess the safety and efficacy of EVUSHELD in different populations. Additionally, AstraZeneca has also engaged the scientific-advice services offered by NICE, to optimise the evidence generation activities in anticipation for its technology appraisal expected later in 2022. Furthermore, the EVUSHELD clinical development programme includes other indications for outpatient (OP) and inpatient treatment of patients with impaired immune function and others at risk of progression to severe disease (including multiple conditions such as cardiovascular disease, chronic obstructive pulmonary disease and asthma, cancer, diabetes, obesity). All of these agencies concur with the need for additional evidence to supplement and augment trial data. Quantifying these populations, understanding their experience with the disease in the different phases of the pandemic, and assessing the magnitude of their health and economic burdens is the first step to inform decisions on priorities among these populations, anticipating health expenditure, and providing guidance on EVUSHELD usage and place in therapy. Soon after the first doses become available, additional evidence generation efforts will follow, to confirm effectiveness in routine care, investigate safety, and follow the impact of the emergence of viral variants on EVUSHELD effectiveness and safety. - Acceptance of three oral presentations and three poster presentations: The current study under consideration is part of this evidence generation program. The first step will be to identify and quantify the populations that would benefit from prophylaxis and/or treatment with EVUSHELD in England (i.e., those ineligible for COVID-19 vaccines due to contraindication and those who are immunocompromised), as well as describe the health and economic burdens of COVID-19 during the pre-vaccination and vaccination periods, stratified by age, disease severity, and selected comorbidities. Oral presentation at 19th European Geriatric Medicine Society Conference 2023: “Increased risk of severe COVID-19 outcomes in fully vaccinated older adults aged over 65 with comorbidities during Omicron predominance period: initial results from INFORM, a retrospective, observational health cohort database study in England” For more information on government authorisation of EVUSHELD, please see: https://www.gov.uk/government/publications/regulatory-approval-of-evusheld-tixagevimabcilgavimab. - Oral presentation at the Infectious Disease Conference 2023: “Fully Vaccinated Individuals with Immunocompromised conditions (IC) are Still at Increased Risk of Severe COVID-19 Outcomes from the Omicron Variant – Results From INFORM, a Retrospective Health Database Observational Study in England” For more information on EVUSHELD clinical trials, please see ClinicalTrials.gov, studies NCT04625725 NCT04625972, NCT04518410, NCT04723394. NCT04501978, and NCT04315948. - Oral presentation at the Infectious Disease Conference 2023: “Increased Risk of COVID-19 Hospitalization and Death in Vaccinated Patients with End-Stage Renal Disease (ESRD) and Dialysis - Results From INFORM, a Retrospective Health Database Observational Study in England” The core study objectives are to: - Poster presentation at the Infectious Disease Conference 2023: “- Increased Risk of Severe COVID-19 Outcomes Across all Groups of Individuals with Hematological Malignancies, Solid Tumors, and Solid Organ Transplants Compared with the General Population: Initial Results from INFORM, a Retrospective Health Database Observational Study in England 1. Estimate the size of populations (pre-defined) in England that potentially are ineligible for vaccines or are at risk of inadequate response to COVID-19 vaccines - Poster presentation at the International Primary Immunodeficiencies Congress 2023: “Increased Risk of COVID-19-related Hospitalization and Mortality in Vaccinated Individuals with Primary Immunodeficiency Disease: Initial Results from INFORM, a Retrospective Study using English National Health Services Datasets” 2. Estimate incidence of COVID-19 by age group, disease severity, and selected comorbidities - Poster presentation at the American Society of Nephrology 2023: “Despite Vaccination, Risks of COVID-19 Outcomes are Elevated in Patients with End-Stage Renal Disease: Initial Results from INFORM, a Study in England using the National Health Service datasets” 3. Estimate incidence of long-COVID-19 by age, disease severity, and selected comorbidities - Submission of 1 abstract still under consideration for acceptance: 4.Describe patterns of healthcare resource utilisation (HCRU) and costs associated with an episode of COVID-19, stratified by age, selected comorbidities, disease severity, and the occurrence (vs. absence) of long-COVID-19 - Abstract submitted to British Geriatric Society Conference 2023: “Risk of severe COVID-19 increases with the number of comorbidities in fully vaccinated individuals aged ≥65: results from INFORM” The exploratory objectives are to: - Submission of a manuscript to Lancet Regional Health-Europe “Immunocompromised populations are disproportionately impacted by COVID-19 during the Omicron era: Insights from the INFORM study” (accepted for publication) 1. Identify patients who developed a composite outcome of COVID-19 hospitalisation or COVID-19-related death after vaccination, stratified by the number of doses received, and explore potential risk factors thereof - Publication of the study protocol in the International Standard Randomised Controlled Trial Number (ISRCTN) Registry (https://doi.org/10.1186/ISRCTN53375662) 2. Develop a prediction model to identify risk profiles associated with a composite outcome of COVID-19 hospitalisation or COVID-19-related death after the deployment of the vaccination campaign in England, and to estimate the prevalence of subgroups consistent with each identified risk profile. Examples where the results have been used in submissions or presentations to key policy making and scientific bodies include: The study team has chosen to register the study with International Standard Randomised Controlled Trial Number (ISRCTN) registry voluntarily. The study is registered, and the protocol is publicly available here: https://www.isrctn.com/ISRCTN53375662. ISRCTN, is one of the few platforms listed in NICE real-world evidence framework document (www.nice.org.uk/corporate/ecd9) that can be considered for protocol registration. - UK policy and scientific bodies Data shared with key clinical consultants that advised in the McInnes Report. The report team may convene to critically look at the excellent granularity of data to further explore if more eligible populations should be added to groups that could be eligible for additional protection interventions against COVID-19 severe outcomes. The study team have consulted with several McInnes group expert advisors, and they unequivocally support wider and continuous access. These examples demonstrate the significance of this research and its expected impact on the improved care for patients with immunocompromising conditions, as robust evidence continues to underpin those clinical and policy decisions. OBJECTIVES: OBJECTIVE 1: Current research evidence on vulnerable populations that are not adequately protected by COVID-19 vaccines is fragmented. Research to understand the size and characteristics of these vulnerable populations, especially in the UK, is urgently needed. Objective 1 is to estimate the size of populations (pre-defined) in England that potentially are ineligible for vaccines or are at risk of inadequate response to COVID-19 vaccines. OBJECTIVE 2: Incident COVID-19: Given population level testing ended in the UK in early 2022, the study team now defines an incident COVID-19 case as one that requires medical attention, hospitalisation, ITU admission, or death; estimating incidence rates for hospitalisation, ITU admission and death. Time periods: Throughout the history of SARS-CoV-2, different variants have emerged and will continue to emerge. To obtain the most relevant estimates for healthcare professionals, researchers, and the general public, analyses will focus on more recent time periods defined by relevant and current cut-offs such as the predominance of the omicron variant, quarters or seasons in 2023, etc. For these analyses, cut-off dates for eligibility, lookback, and follow-up periods need to be redefined to generate more current estimates of COVID severe outcomes as time progresses and circumstances evolve. Subgroups: As the pandemic progressed, so did our understanding of risk profiles and the potential effect modifiers that require stratification of analyses. In addition to stratifying analyses by demographics, comorbidities, and vaccination status, stratification by therapies licenced for the treatment of COVID-19 will also be conducted. OBJECTIVE 3: Case definition: The scientific and clinical communities’ understanding of long COVID has evolved since this research project was first devised. Based on current evidence it is no longer accurate to characterise long COVID as a single condition. More accurately, it is likely a heterogenous group of related conditions with varying symptom predominance.1 To ascertain and describe cases of long COVID, phenotypic subgroups of long COVID-19 based on associated new diagnoses (such as arrythmia) and related HCRU (such as cardiology outpatient visits) will be identified. This will allow a more granular understanding of the burden of long COVID-19 on at-risk groups. OBJECTIVE 4: Expanded outcomes: Research suggests that apart from the direct impact of COVID-19 on HCRU and mortality, effects are also mediated by2-5: The worsening/exacerbating of pre-existing conditions (such as increased risk of myocardial infarction or heart failure among patients with cardiovascular disease, or of exacerbations among patients with respiratory diseases) In order to assess the full burden of COVID-19, especially in high-risk groups, deaths, adverse outcomes, healthcare resource use and costs for these immunocompromising and pre-existing conditions will also be assessed among patients with and without COVID-19 and over different time periods before, during and after the peak of the pandemic to facilitate comparisons. Exploratory Objective 1: Exploratory objective 1 is to identify patients who developed a composite outcome of COVID-19 hospitalisation or COVID-19-related death after vaccination, stratified by the number of doses received, and explore potential risk factors thereof. EXPLORATORY OBJECTIVE 2: As COVID-19 moves into the endemic phase, the burden of disease is becoming more confined to vulnerable subgroups, with the general population at very low risk of severe outcomes. For this reason, machine learning analyses will primarily focus on individuals at a higher risk of severe COVID-19 outcomes. This will allow the identification of high-risk clusters amongst the population most affected by COVID-19. Additional Analysis: Given the extent of the pandemic, with most of the UK having been infected at least once, it is likely that SARS-CoV-2 has impacted other infectious and bacterial diseases such as acute respiratory infections, staphylococcus infections, and clostridium difficile.6-9. As such, impact of SARS-CoV-2 on the incidence of these infections will be assessed over time, before and during the pandemic, with an assessment of whether the characteristics of patients infected with these pathogens have changed over the course of the pandemic. To develop a comprehensive account of the burden of a disease, it is important to also examine the unintended consequences of its treatments. Contextualisation has been endorsed by the regulators as an important factor in supporting preparedness activities in the evaluation of safety of COVID-19 products. This additional study objective will provide a framework for contextualisation of adverse events of special interest (AESIs); not only known and potential risks but also any unexpected risks that may arise during COVID-19 product development or after licensure. This additional objective will facilitate estimation of incidence and prevalence rates of AESIs by calendar year over the pre-, during and post-pandemic period, in the general population and by age group, sex, disease severity, COVID-19 infection status, selected comorbidities and other subgroups of interest (populations at risk), as appropriate. This analysis will facilitate a more holistic assessment of the burden of COVID-19 on the general population and at-risk groups, by considering the unwanted effects of therapies. CONTROLELRSHIP: AstraZeneca UK Ltd is the data controller for the study. AZ has been determined to be the data controller, in line with the General Data Protection Regulation definition of data controller which states they are the natural or legal person, public authority, agency or any other body who determines the purposes and means of processing the data [1]. AstraZeneca UK Ltd holds the ultimate decision on how the study should be designed and data should be analysed and as such are listed as Data Controller. They also have, in line with UK GDPR requirements, a) a valid data sharing framework contract, b) adequate security assurance and c) have paid the relevant data protection fee to ICO. [1] https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/controllers-and-processors/what-are-controllers-and-processors/ The aim and objectives are determined by AstraZeneca UK Ltd. AstraZeneca is the sole funder/sponsor for this study. Evidera has been contracted by AstraZeneca UK Ltd to conduct this piece of research, acting as the sole data processor. There are no sub-licences or onwards sharing and therefore, Evidera will be the only entity to process the data. LAWFUL BASIS: [2 paragraphs unchanged] Processing personal data is necessary for AstraZeneca’s legitimate interests. The pseudonymised data [39 words unchanged] would reasonably expect the processing and it would not cause unjustified harm. The data subjects' interests and fundamental rights are protected through appropriate minimisation of fields and patient records being processed; pseudonymisation to minimise any risk of identifying individuals; protection of the data in a secure environment, and guaranteeing secure destruction at any stage at the request of National Health Service (NHS) Digital or after a defined period upon completion of the project. NHS Digital has assessed AstraZeneca’s LIA and is satisfied that all requirements are met. [1 paragraph unchanged] If the study identifies an increasing COVID-19 incidence since the onset of the COVID-19 vaccination programme, governments might make the decision to administer more vaccinations as part of their booster programme. Some of these vaccinations will be AstraZeneca vaccines. If the study identifies there is a high unmet need (i.e., many individuals ineligible for the COVID-19 and/or many individuals still at risk for COVID-19 outcomes), then UK payers might be more likely to approve or purchase alternative prevention or treatment products. EVUSHELD is a neutralising monoclonal medicine that has been developed by AstraZeneca and approved for pre-exposure prophylaxis use in vulnerable populations, therefore payers might be more likely to reimburse these therapies based on this information or approve it for additional treatment indication. COMMERCIAL ELEMENT: COHORT: The commercial interests of AstraZeneca (AZ) in this project are to better understand unmet needs for research and development purposes, as well as to provide evidence requested by health authorities for the assessment of EVUSHELD and other of COVID prophylaxis and treatments. However, potential indirect benefits of the project to AZ might include: a) if there is a reduction of the number of COVID-19 cases across the study period, AZ can assume that this was partly due to their vaccination programme, since AZ was one of the biggest COVID-19 vaccination suppliers during the pandemic; b) if there is a huge unmet need identified (i.e., many individuals that are ineligible for COVID-19 vaccinations and/or many individuals still at risk for COVID-19, then NICE might be more likely to approve alternative therapies that could be used to treat these groups of patients, if these therapies are shown to be beneficial in clinical trial data and c) Evidera will benefit since they will deepen their knowledge of COVID-19 observational research and therefore additional clients might be more likely to approach them based on their experience in this field. This study also is part of a wider research project that will also generate evidence on the effectiveness and safety of EVUSHELD in routine clinical practice. The next phases of this project will be launched following the administration of the initial doses in prevention and treatment indications. AZ are developing a number of therapies for COVID-19 (including research around EVUSHELD) and therefore payers like NICE and the NHS may more likely approve/reimburse these therapies based on the outputs of this study that would result in financial benefits for AZ. The overall study population will consist of 25% of the population in England who were alive as of 1 September 2020 and present within NHS Digital's Personal Demographics Service data product. This selection will be performed through stratified sampling by age group, i.e., within each age group ( <12, 12–17, 18–64, 65–79, ≥80 years), a random sample of 25% of the individuals will be drawn. This pragmatic, stratified sampling approach is taken to minimise the amount of data requested at the same time ensure the reduced sample is still generally representative of the English population through random sampling. The planned data analyses include estimating the incidence of COVID-19 by age and comorbidities of interest (e.g., objective 2). To estimate the minimum sample size required to power this study, Evidera examined the subgroup expected to have fewest patients, which are the individuals who received a recent stem cell transplant. This is one of the key immunocompromised population subgroups of interest, given their potentially inadequate serologic response to vaccines and high morbidity and mortality risk following COVID-19 infection. Yet, the evidence on their relative risk of in comparison with the general population is unclear [1]. According to estimates published by Eurostat in the Euro SDMX Metadata Structure (ESMS), in 2019 approximately 3,650 patients received a stem cell transplant in the UK [2]. A random sample of 25% of the English population would result in approximately 766 patients who received a stem cell transplant in the year prior to 1 September 2020 (a period that is used to consider patients who are at risk of being immunocompromised due to the use of immunosuppressants) (3,650 * 84% UK population is in England * 25% random sampling = 766.5). Assuming a COVID-19 event rate of 0.004 per person-month in the general population (recent national statistics indicate the case rate ranges from 0.002 to 0.006 per person-month), a sample size of 750 subjects in a single arm provides 92.4% power to detect a 2-fold increase in the risk of SARS-CoV-2 infection (relative risk=2), 99.9% power to detect a 3-fold increase in infection risk (relative risk=3) with a type I error rate of 5% (using WebPower package in R). [1] https://www.sciencedirect.com/science/article/pii/S2666636722001580 [2] Extracted on June 26th, 2022 from https://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do In other words, in the England population, randomly picking every fourth individual with a stem cell transplant, there approximately would be 767 individuals. Assumed that out of 1000 such individuals follow-up for 1 month each, 4 will develop COVID-19, it can be estimated that in this selected population of individuals with stem cell transplant, 3 out of 767 individuals will develop COVID-19 in 1 month. Given the interest in understanding whether there is a difference in the rate at which the stem cell transplant group experiences COVID-19 infection (relative to the comparator group such as individuals without a stem cell transplant), at least 750 individuals in each group are required to be able to detect a hypothesised 2-fold difference between the rates of COVID-19 between the two groups, so that at least 92% sure of being able to detect such a difference between the two groups. No control or treatment group is planned for this study, but stratified analyses are foreseen, to understand variations in magnitude of the health and economic burdens across several subgroups, as well as in different phases of the pandemic. The goal is to have a representative sample of patients in England so that estimates are more generalisable to the entire population of England. If they have a record in any of the requested datasets for the stated periods, this will be pseudonymised with a unique identification (ID) number that is common across the datasets and released to Evidera, which will apply filters to the datasets to identify the appropriate study population for each of the objectives as described above. Since there is substantial variation in the incidence of COVID-19 and long-COVID-19 and HCRU patterns across regions and sociodemographic factors, this study seeks to use data from a substantial portion of the English population (about 25% through stratified random sampling by age group and region stratum) to provide an accurate estimate of the overall incidence rates and HCRU associated with COVID-19. This is also needed to ensure an adequate sample size to support further stratified analyses, by age, comorbidities, long-COVID-19 status, and disease severity. There are two periods used in this study: a five-year baseline period from 1 September 2015 to 31 August 2020, and a follow-up period from 1 September 2020 to present. The baseline period will be used to identify pre-existing conditions and potential risk factors, acute and chronic conditions, as well as certain immunosuppressive treatments, which is of vital importance to this study. Chronic conditions tend to be under-recorded in administrative healthcare datasets. A recent study (Rosenlund et al., 2020), suggested the optimal period for capturing chronic comorbidities is three to five years. Additionally, vulnerable populations, especially patients who have received transplants, are immunosuppressed, or oncology patients continue to experience complications associated with these diagnoses and treatments many years after. Therefore, a longer look-back period is necessary and required to capture these patients. - Objective 1 will identify all individuals in the study sample with (1) contraindications to the vaccine; (2) limited safety data available (as a result of being typically excluded from clinical trials with real-world safety data not yet published); and/or (3) elevated risk of suboptimal response. Criteria for selection will be assessed during the five-year baseline period using Hospital Episode Statistics (HES) and Research and Medicines Dispensed in Primary Care datasets and three-year baseline period using General Practice Extraction Service (GPES) Data for Pandemic Planning (GDPPR; rationale and details are provided in data minimisation section below). - Objective 2 will identify all individuals who developed their first SARS-CoV-2 infection during infection identification period (1 September 2020 – end of study period). Individuals who did not develop a SARS-CoV-2 infection will also be included in the analysis as they are important for estimating the total person-time at risk of developing infections for the estimation of incidence rate of COVID-19. - Objective 3 is similar to Objective 2 but focuses on long COVID-19 as the outcome as opposite to SARS-CoV-2 infections. - Objective 4 describes HCRU and costs incurred among patients with COVID-19. Exploratory objective 1 and 2 include all vaccinated subjects and explore risk factors associated with breakthrough infections (i.e., escaping from the immunity acquired from COVID-19 vaccines) as well as identify cluster of patients who are most vulnerable to breakthrough infection and describe their risk profiles using machine learning methods. How the data requested will achieve the aim identified is detailed below: • For the first objective, pre-defined lists of diagnosis codes will be used to search in patients’ health records (GDPPR and HES) in the baseline period to identify patients who meet the definition of potentially ineligible for COVID-19 vaccines or at potential risk of breakthrough infection following vaccination. • For the second and third objectives, incidence rates of COVID-19 and long-COVID-19 (identified using diagnosis codes in GDPPR and HES and positive test results in SGSS) will be estimated. The numerators will be the number of COVID-19 infections and the number of patients with long-COVID-19, respectively. The denominator will the total person-time at risk. The analysis will be further stratified by age group, COVID-19 severity, and selected comorbidities. • For the fourth objective, HCRU associated with COVID-19 infection will be estimated and relevant costs will be calculated. In the exploratory objectives, patient characteristics and vaccination status in combination of COVID-19 severe outcomes information will be used to explore risk factors and risk profiles of those who are potentially ineligible for COVID-19 vaccines or at risk of breakthrough infection, including using machine learning-based prediction models. For more information, please see: https://www.gov.uk/government/publications/third-primary-covid-19-vaccine-dose-for-people-who-are-immunosuppressed-jcvi-advice/joint-committee-on-vaccination-and-immunisation-jcvi-advice-on-third-primary-dose-vaccination [14 paragraphs unchanged] How will the data requested achieve the aim identified? References The dossiers that AstraZeneca has submitted to the MHRA, the government’s Commission on Human Medicines, contain evidence generated in clinical trials and estimates based on the literature and aggregated data from the US, European Union (EU), Israel, and other geographies, though with limited coverage in the UK. The dossiers will also be submitted to NICE later in 2022. This study will provide UK-specific accurate, population-based, and precise results on the number of patients still at risk in England, the burden to the British healthcare system, and the pattern of risk-factor clustering in the country to identify certain risk profiles that combine determinants at the individual (e.g., comorbidities, treatments, age), regional (e.g., deprivation index, transmission rates, healthcare provision), and national levels (e.g., phases of the pandemic pertaining to vaccination deployment, circulating variants). UK-specific evidence will be relayed to the health authorities as well as the clinical community and the general public to close the aforementioned gaps. 1. Reese JT, Blau H, Casiraghi E, et al. Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes. EBioMedicine. 2023;87:104413. doi:10.1016/j.ebiom.2022.104413. DATA MINIMISATION: 2. Vasbinder A, Meloche C, Azam TU, et al. Relationship Between Preexisting Cardiovascular Disease and Death and Cardiovascular Outcomes in Critically Ill Patients With COVID-19. Circ Cardiovasc Qual Outcomes. 2022;15(10):e008942. doi:10.1161/CIRCOUTCOMES.122.008942. Data minimisation efforts in the current application were applied to all dimensions of the request as follows: 3. Bilotta C, Perrone G, Adelfio V, et al. COVID-19 Vaccine-Related Thrombosis: A Systematic Review and Exploratory Analysis. Front Immunol. 2021;12:729251. doi:10.3389/fimmu.2021.729251. 1. Restricting the number of subjects: data have been requested for a subset of the English population rather than the entire English population. Stratified sampling will be used to randomly select 25% of population from each age (i.e., 0–11, 12–17, 18–64, 65–79, ≥80 years) and region (i.e., nine regions in England) stratum. This random sampling within each age and region stratum ensures the study sample is representative of the English population while minimising the amount of data being requested with the ability to capture patients with relatively less common clinical conditions (e.g., with organ transplantation or auto-immune disease). 4. Paul P, Janjua E, AlSubaie M, et al. Anaphylaxis and Related Events Following COVID-19 Vaccination: A Systematic Review. J Clin Pharmacol. 2022;62(11):1335-1349. doi:10.1002/jcph.2120. 2. Restricting the number of years: for the GDPPR data product, baseline data requested have been reduced to three instead of five year. Baseline data are important to identify patients with pre-existing conditions of interest, most of which are primary or secondary immunosuppression. Since most of these patients would have a relevant specialist visit or hospitalisation recorded in HES, this additional restriction was taken to minimise the amount of GDPPR data being requested and is not expected to impact the accuracy of the characterisation of the population under consideration. 5. Bhandari B, Rayamajhi G, Lamichhane P, Shenoy AK. Adverse Events following Immunization with COVID-19 Vaccines: A Narrative Review. Biomed Res Int. 2022;2022:2911333. doi:10.1155/2022/2911333. 3. Restricting the number of data products: Certain data products requested in the original application have been removed. Such is the case of the “Secondary Use Service Payment by Result” (SUS), and the “Electronic Prescribing and Medicines Administration” (EPMA) datasets. 6. Chow EJ, Uyeki TM, Chu HY. The effects of the COVID-19 pandemic on community respiratory virus activity. Nature Reviews Microbiology. 2023;21(3):195-210. doi:10.1038/s41579-022-00807-9. 4. Restricting the number of fields/variables: To minimise the number of fields being requested, for each data product, fields were reviewed individually. Only those fields that are considered to be necessary to address study objectives are selected and requested. 7. Voona S, Abdic H, Montgomery R, et al. Impact of COVID-19 pandemic on prevalence of Clostridioides difficile infection in a UK tertiary centre. Anaerobe. 2022;73:102479. doi:10.1016/j.anaerobe.2021.102479. CONTROLLERSHIP: 8. Sipos S, Vlad C, Prejbeanu R, et al. Impact of COVID-19 prevention measures on Clostridioides difficile infections in a regional acute care hospital. Exp Ther Med. 2021;22(5):1215. doi:10.3892/etm.2021.10649. AstraZeneca UK Ltd is the data controller for the study. AZ has been determined to be the data controller, in line with the General Data Protection Regulation definition of data controller which states they are the natural or legal person, public authority, agency or any other body who determines the purposes and means of processing the data [1]. AstraZeneca UK Ltd holds the ultimate decision on how the study should be designed and data should be analysed and as such are listed as Data Controller . They also have, in line with UK GDPR requirements, a) a valid data sharing framework contract, b) adequate security assurance and c) have paid the relevant data protection fee to ICO. 9. Dar S, Erickson D, Manca C, et al. The impact of COVID on bacterial sepsis. European Journal of Clinical Microbiology & Infectious Diseases. 2023;doi:10.1007/s10096-023-04655-0. [1] https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/controllers-and-processors/what-are-controllers-and-processors/ The aim and objectives are determined by AstraZeneca UK Ltd. AstraZeneca is the sole funder/sponsor for this study. AstraZeneca UK Ltd and the University of Oxford co-created one of the COVID-19 vaccines that has been widely deployed during the COVID-19 pandemic, and AstraZeneca is the sponsor and holder of the marketing authorisation for EVUSHELD, a product that combines two long-acting antibody (tixagevimab and cilgavimab), for the prevention and treatment of patients who are immunocompromised and other high-risk populations. A focus of the proposed study is to enhance understanding of the disease and its burden in individuals who are ineligible for or are potential suboptimal responders of available COVID-19 vaccines and whether these individuals can benefit from additional preventative or treatment interventions. Evidera has been contracted by AstraZeneca UK Ltd to conduct this piece of research, acting as the sole data processor. There are no sub-licences or onwards sharing and therefore, Evidera will be the only entity to store and process the data. Evidera, under AstraZeneca UK Ltd instruction, assessed available data sources for executing this study and is executing the study. This includes (1) drafting the study protocol and finalising it according to the review comments received from AstraZeneca UK Ltd; (2) submitting the data application to NHS Digital; (3) drafting a statistical analysis plan (SAP) and finalising it according to the review comments received from AstraZeneca UK Ltd; (4) analysing data in accordance with the SAP; and (5) interpreting and disseminating study results with input from AstraZeneca UK Ltd. Evidera work under the instruction of AstraZeneca UK Ltd and will only proceed to data analysis stage once approval has been received from AstraZeneca UK Ltd and as such Evidera is considered. The principal investigator (PI) at Evidera will be leading the execution of the abovementioned contracted research activities. The PI is based in Sweden and the main study team is based in the UK. The PI will not have access to the raw data at any time during the duration of this study. Th PI will have access to aggregated summary statistics and analysis outputs. The Health and Social Care Information Centre (NHS Digital) is listed as a joint Data Controller, where it is managing the system and providing data hosting services of data specified in the Data Sharing Agreement (with sole responsibility for responding to data subject access requests it receives, management of impacts and events on the system, planning and system development and changes); NHS Digital do not determine the aims and objectives of the purpose of the project described in DARS-NIC-561357-X0F3N. NHS Digital shall, in relation to the Data, process that Data only in accordance with the requirements to host Data in the SDE and Customer’s instruction unless NHS Digital is required to do otherwise by law. If it is so required, NHS Digital shall promptly notify the Cust

Processing activities

There will be no flow of data into NHS Digital. England NHS Digital England will allow Evidera, as AZ data processor, access via NHS Digitals England’s Secure Data Environment (SDE) to pseudonymised [4 paragraphs unchanged] - NHS BSA (Medicines Dispensed in Primary Care) data, [1 paragraph unchanged] Evidera will perform data preparation and analysis in accordance with the study [61 words unchanged] hospitalisations. Evidera will be conducting all data analyses, data processing, and data management. management within the SDE. Once the analysis has been conducted, the aggregated results with a small number suppression applied will be sent to AstraZeneca UK Ltd for review. At no stage will the patient-level data be sent to AstraZeneca UK Ltd or anyone outside of Evidera. Evidera will be conducting all data analyses, data processing, and data management within the SDE. Once the analysis has been conducted, the aggregated results will be submitted to the NHSE safe outputs service who will check for appropriate suppression and rounding, and approve outputs for release. Once aggregated outputs are approved for release, they will be shared with AZ. Data will only be processed and analysed by substantive employees of Evidera. The data processing will only be conducted by an analyst who is familiar with the data and who has substantial experience of analysing UK data. All core study members are adequately trained in data protection and confidentiality. [19 paragraphs unchanged]

Expected output

The initial results for this study are expected within a year following the access to the NHS Digital-linked datasets. Outputs from this project are expected to be published throughout 2024. Evidera will be conducting all of the data processing and the analysis. analysis within the secure data environment. They will send aggregated results that will be in the format of [34 words unchanged] number and percentage of patient demographics and clinical characteristics identified at baseline), the number and percentage of patients identified as ineligible for COVID-19 vaccine (different row will be provided for each ineligibility criteria), the number and percentage of patients at risk of COVID-19 infection (different [51 words unchanged] aggregated data with secondary suppression of cells will be send to AZ. At no point will the patient level data be transferred from Evidera to AZ. The results will also be presented in a study report and sent to AZ for review. [4 paragraphs unchanged] Based on an assumed data delivery date in Nov 2022, Evidera estimates to complete data analysis in Jan 2023 and study report in August/September 2023. Once study report has been drafted, manuscripts will be prepared for submission to peer-reviewed journals and abstracts for conference presentation in Q3/Q4 2023. These planned outputs will be designed with the intention of including sufficient information on methods to ensure research transparency and reproducibility. All types of results, including those sometimes seemed as unfavourable, will be published along with key code lists used for case definitions. The code lists refer to the SNOMED (https://termbrowser.nhs.uk/) and ICD-10 (https://icd.who.int/browse10/2019/en#/ ) diagnosis codes for identifying patients with COVID or long-COVID. The case definition refers to how cases (i.e., COVID and long COVID-19) are defined and identified from the requested datasets. The proposed study is descriptive in nature, e.g., estimating the size of populations that are not protected by COVID-19 vaccines. The incidence of COVID-19 and long COVID-19, and COVID-19-related healthcare service use, as opposed to estimating the effectiveness of certain treatments/vaccines. The aim is to understand the current health and economic burden of COVID-19. The plan is to publish results regardless of whether the estimates are high or low.. COVID-19 research results need to and will be interpreted in the wider context, e.g., social restrictions and movement, infection rate, vaccination/booster roll-out and availability of an-viral treatments. These planned outputs will be designed with the intention of including sufficient information on methods to ensure research transparency and reproducibility. All types of results, including those sometimes seemed as unfavourable, will be published along with key code list used for case definition. The code lists refer to the SNOMED (https://termbrowser.nhs.uk/) and ICD-10 (https://icd.who.int/browse10/2019/en#/ ) diagnosis codes for identifying patients with COVID or long-COVID. The case definition refers to how cases (i.e., COVID and long COVID-19) are defined and identified from the requested datasets. The proposed study is descriptive in nature, e.g., estimating the size of populations that are not protected by COVID-19 vaccines. The incidence of COVID-19 and long COVID-19, and COVID-19-related healthcare service use, as opposed to estimating the effectiveness of certain treatments/vaccines. The aim is to understand the current health and economic burden of COVID-19. The plan is to publish results regardless of whether the estimates are high or low. With that said, given the data published on COVID dashboard (https://coronavirus.data.gov.uk/), it is unlikely to be low/unfavourable. COVID-19 research results need to and will be interpreted in the wider context, e.g., social restrictions and movement, infection rate, vaccination/booster roll-out and availability of an-viral treatments. [1 paragraph unchanged]

Expected measurable benefits

Benefits from this study are expected to include the following As SARS-CoV-2 has evolved, the burden of the disease and therapies to treat COVID-19 have also evolved. Since the original application was approved, AstraZeneca continued to develop new generations of their COVID-19 prophylaxis and treatment, EVUSHELD, including an investigational next generation long-acting antibody AZD3152 (NCT05648110). Results of these analyses hopes to allow policy makers, healthcare professionals, and patients to obtain a more granular and personalised understanding of the risk of severe COVID-19 outcomes, which accounts for comorbidities, treatments, age, and other relevant variables. This information will be made public through manuscript submissions and conference presentations. 1. Benefits for regulators (e.g., MHRA): the findings from this study are hoped will support MHRA’s review of EVUSHELD for the use among patients who are immunocompromised and other vulnerable populations to supplement the trial evidence, based on which the Conditional Marketing Authorisation in PrEP (pre-exposure prophylaxis) was granted. Furthermore, the results of this study will provide a baseline against which to benchmark the overall impact of the use of EVUSHELD, until data accrual and maturity allow for a contemporaneous comparative effectiveness and safety assessment, following the administration of sufficient doses. Additionally, should the respective clinical trials confirm EVUSHELD’s safety and efficacy in outpatient and inpatient treatment indications, the results of this study will serve as foundation for the development of the submission dossier to ascertain the most accurate characterisation of the source population in England. Benefits from this study are expected to include the following: 2. Its is anticipated that there will be benefits for Health Technology Assessment and endorsement bodies such as NICE and the Scottish Medicines Consortium (SMC): During the early scientific advice procedure in which AstraZeneca engaged, NICE requested more accurate information on the expected number of patients that would be eligible for EVUSHELD use. NICE also recommended that AstraZeneca conduct an observational study to continue identifying which populations do not respond to vaccinations, beyond patients who are immunocompromised, and expressed concern for the dynamic landscape due to the emergence of new variants, which should also be monitored. Lastly, NICE requested that the health-economic model be populated with efficacy data from the phase III trial PROVENT (NCT04625725, please see - https://clinicaltrials.gov/ct2/show/NCT04625725) but the baseline characteristics be adjusted to more accurately reflect the population in England as well as account for the substantial heterogeneity likely to exist in the target population (e.g., in terms of comorbidities, resource use, risk of severe COVID-19). These are the exact research questions that guided the design of the current study. The results from objectives 2 and 3 will be used to adjust the population characteristics for the cost-effectiveness model. Additionally, the patterns of HCRU and costs associated with an episode of COVID-19 will be an important input for the cost-effectiveness model. The accurate count of patients at risk from objective 1 will also be used in the budget impact model. The exploratory objectives to identify and quantify risk profiles with high unmet clinical need will be the basis for sensitivity analyses in both health-economic models. Furthermore, as the pandemic becomes endemic, regulators and policy makers will also benefit from country-specific estimates on the burden of long-COVID-19 to patients and to the healthcare system to be factored in policy decisions. 1. Benefits for regulators (e.g., MHRA): the findings from this study are hoped will support MHRA’s review of EVUSHELD and other COVID-19 prophylaxis and treatments for the use among patients who are immunocompromised and other vulnerable populations to supplement the trial evidence, based on which the Conditional Marketing Authorisation in PrEP (pre-exposure prophylaxis) was granted. Furthermore, the results of this study will provide a baseline against which to benchmark the overall impact of the use of EVUSHELD, until data accrual and maturity allow for a contemporaneous comparative effectiveness and safety assessment, following the administration of sufficient doses. Additionally, should the respective clinical trials confirm EVUSHELD’s safety and efficacy in outpatient and inpatient treatment indications, the results of this study will serve as foundation for the development of the submission dossier to ascertain the most accurate characterisation of the source population in England. 2. Its is anticipated there will be benefits for Health Technology Assessment (HTA) and endorsement bodies such as NICE and the Scottish Medicines Consortium (SMC): During the early scientific advice procedure in which AstraZeneca engaged, NICE requested more accurate information on the expected number of patients that would be eligible for EVUSHELD and other COVID-19 therapies. NICE also recommended that AstraZeneca conduct an observational study to continue identifying which populations do not respond to vaccinations, beyond patients who are immunocompromised, and expressed concern for the dynamic landscape due to the emergence of new variants, which should also be monitored. Lastly, NICE requested that the health-economic model be populated with efficacy data from the phase III trial PROVENT (NCT04625725, please see - https://clinicaltrials.gov/ct2/show/NCT04625725) but the baseline characteristics be adjusted to more accurately reflect the population in England as well as account for the substantial heterogeneity likely to exist in the target population (e.g., in terms of comorbidities, resource use, risk of severe COVID-19). These are the exact research questions that guided the design of the current study. The results from objectives 2 and 3 will be used to adjust the population characteristics for the cost-effectiveness model. Additionally, the patterns of HCRU and costs associated with an episode of COVID-19 will be an important input for the cost-effectiveness model. The accurate count of patients at risk from objective 1 will also be used in the budget impact model. The exploratory objectives to identify and quantify risk profiles with high unmet clinical need will be the basis for sensitivity analyses in both health-economic models. Furthermore, as the pandemic becomes endemic, regulators and policy makers will also benefit from country-specific estimates on the burden of long-COVID-19 to patients and to the healthcare system to be factored in policy decisions. In order to influence benefits for the health and social care system, the study team will require additional data for a wider cohort to publish outputs from the INFORM study, and support ongoing submissions to HTA and endorsement bodies including NICE, more granular data are required to facilitate the characterization of risk in rare subgroups. [3 paragraphs unchanged]

Benefits reported

Yielded Benefits is not a requirement for new applications. The findings of the study thus far have proved to be crucial to support both clinical care and policy decision making. In only three months since the first results started becoming available, they have been incorporated into dossiers for submission to health authorities and into scientific publications for awareness among healthcare providers, patients, and their families. More articles and abstracts for submission to peer-reviewed journals and scientific conferences, respectively, are currently in preparation and more clinical experts continue to join the study.