The number of deaths registered in England and Wales due to and involving coronavirus (COVID-19). Breakdowns include age, sex, region, local authority, Middle-layer Super Output Area (MSOA), indices of deprivation and place of death. Includes age-specific and age-standardised mortality rates.

Pre-existing conditions of people who died due to COVID-19, broken down by country, broad age group, and place of death occurrence, usual residents of England and Wales.

The Public Health Research Database (PHRD) is a linked asset which currently includes Census 2011 data; Mortality Data; Hospital Episode Statistics (HES); GP Extraction Service (GPES) Data for Pandemic Planning and Research data. Researchers may apply for these datasets individually or any combination of the current 4 datasets.

The purpose of this dataset is to enable analysis of deaths involving COVID-19 by multiple factors such as ethnicity, religion, disability and known comorbidities as well as age, sex, socioeconomic and marital status at subnational levels. 2011 Census data for usual residents of England and Wales, who were not known to have died by 1 January 2020, linked to death registrations for deaths registered between 1 January 2020 and 8 March 2021 on NHS number. The data exclude individuals who entered the UK in the year before the Census took place (due to their high propensity to have left the UK prior to the study period), and those over 100 years of age at the time of the Census, even if their death was not linked. The dataset contains all individuals who died (any cause) during the study period, and a 5% simple random sample of those still alive at the end of the study period. For usual residents of England, the dataset also contains comorbidity flags derived from linked Hospital Episode Statistics data from April 2017 to December 2019 and GP Extraction Service Data from 2015-2019.

Provisional counts of the number of deaths registered in England and Wales, by age, sex, region and Index of Multiple Deprivation (IMD), in the latest weeks for which data are available.

Provisional counts of the number of deaths registered in England and Wales, including deaths involving coronavirus (COVID-19), by local authority, health board and place of death in the latest weeks for which data are available. The occurrence tabs in the 2021 edition of this dataset were updated for the last time on 25 October 2022.

As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

Due to changes in the collection and availability of data on COVID-19, this dataset is no longer updated. Latest information about COVID-19 is available via the UKHSA data dashboard. The UK government publish daily data, updated weekly, on COVID-19 cases, vaccinations, hospital admissions and deaths. This note provides a summary of the key data for London from this release. Data are published through the UK Coronavirus Dashboard, last updated on 23 March 2023. This update contains: Data on the number of cases identified daily through Pillar 1 and Pillar 2 testing at the national, regional and local authority level Data on the number of people who have been vaccinated against COVID-19 Data on the number of COVID-19 patients in Hospital Data on the number of people who have died within 28 days of a COVID-19 diagnosis Data for London and London boroughs and data disaggregated by age group Data on weekly deaths related to COVID-19, published by the Office for National Statistics and NHS, is also available. Key Points On 23 March 2023 the daily number of people tested positive for COVID-19 in London was reported as 2,775 On 23 March 2023 it was newly reported that 94 people in London died within 28 days of a positive COVID-19 test The total number of COVID-19 cases identified in London to date is 3,146,752 comprising 15.2 percent of the England total of 20,714,868 cases In the most recent week of complete data (12 March 2023 - 18 March 2023) 2,951 new cases were identified in London, a rate of 33 cases per 100,000 population. This compares with 2,883 cases and a rate of 32 for the previous week In England as a whole, 29,426 new cases were identified in the most recent week of data, a rate of 52 cases per 100,000 population. This compares with 26,368 cases and a rate of 47 for the previous week Up to and including 22 March 2023 6,452,895 people in London had received the first dose of a COVID-19 vaccine and 6,068,578 had received two doses Up to and including 22 March 2023 4,435,586 people in London had received either a third vaccine dose or a booster dose On 22 March 2023 there were 1,370 COVID-19 patients in London hospitals. This compares with 1,426 patients on 15 March 2023. On 22 March 2023 there were 70 COVID-19 patients in mechanical ventilation beds in London hospitals. This compares with 72 patients on 15 March 2023. Update: From 1st July updates are weekly From Friday 1 July 2022, this page will be updated weekly rather than daily. This change results from a change to the UK government COVID-19 Dashboard which will move to weekly reporting. Weekly updates will be published every Thursday. Daily data up to the most recent available will continue to be added in each weekly update. Data summary 리소스 CSV phe_vaccines_age_london_boroughs.csv CSV 다운로드 phe_vaccines_age_london_boroughs.csv CSV phe_healthcare_admissions_age.csv CSV 다운로드

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

PIONEER: Deeply-phenotyped hospital COVID patients: severity, acuity, therapies, outcomes Dataset number 4.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 6 million cases& more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS)& death. There is a pressing need for tools to stratify patients, to identify those at greatest risk. Acuity scores are composite scores which help identify patients who are more unwell to support & prioritise clinical care. There are no validated acuity scores for COVID-19 & it is unclear whether standard tools are accurate enough to provide this support. This secondary care COVID dataset contains granular demographic, morbidity, serial acuity and outcome data to inform risk prediction tools in COVID-19.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 & 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – May 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes but also primary care records& clinic letters. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT, MRI, ultrasound).

Available supplementary data: Health data preceding & following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

PIONEER: The impact of ethnicity and multi-morbidity on COVID-related outcomes; a primary care supplemented hospitalised dataset Dataset number 3.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 65million cases and more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) and death. Evidence suggests that older patients, those from some ethnic minority groups and those with multiple long-term health conditions have worse outcomes. This secondary care COVID dataset contains granular demographic and morbidity data, supplemented from primary care records, to add to the understanding of patient factors on disease outcomes.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 and 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – May 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes but also primary care records and clinic letters. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT, MRI, ultrasound).

Available supplementary data: Health data preceding and following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

OMOP dataset: Hospital COVID patients: severity, acuity, therapies, outcomes Dataset number 2.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 6 million cases & more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) & death. There is a pressing need for tools to stratify patients, to identify those at greatest risk. Acuity scores are composite scores which help identify patients who are more unwell to support & prioritise clinical care. There are no validated acuity scores for COVID-19 & it is unclear whether standard tools are accurate enough to provide this support. This secondary care COVID OMOP dataset contains granular demographic, morbidity, serial acuity and outcome data to inform risk prediction tools in COVID-19.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 & 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date. This is a subset of data in OMOP format.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – August 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.

Available supplementary data: Health data preceding & following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data. Further OMOP data available as an additional service.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Provisional deaths registration data for single year of age and average age of death (median and mean) of persons whose death involved coronavirus (COVID-19), England and Wales. Includes deaths due to COVID-19 and breakdowns by sex.

This indicator is designed to accompany the SHMI publication. The SHMI includes all deaths reported of patients who were admitted to non-specialist acute trusts in England and either died while in hospital or within 30 days of discharge. Deaths related to COVID-19 are excluded from the SHMI. A contextual indicator on the percentage of deaths reported in the SHMI which occurred in hospital and the percentage which occurred outside of hospital is produced to support the interpretation of the SHMI. Notes: 1. For discharges in the reporting period April 2024 - July 2024, almost all of the records for Wirral University Teaching Hospital NHS Foundation Trust (trust code RBL) have been submitted without an NHS number. This will have affected the linkage of the HES data to the ONS death registrations data and may have resulted in a smaller number of deaths occurring outside hospital within 30 days of discharge being identified for this trust than would have otherwise been the case. The results for this trust should therefore be interpreted with caution. This issue was only discovered after publication and this note was added on 20/12/2024. 2. There is a shortfall in the number of records for North Middlesex University Hospital NHS Trust (trust code RAP), Northumbria Healthcare NHS Foundation Trust (trust code RTF), and The Shrewsbury and Telford Hospital NHS Trust (trust code RXW). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 3. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

Background. Chronic obstructive pulmonary disease (COPD) is a debilitating lung condition characterised by progressive lung function limitation. COPD is an umbrella term and encompasses a spectrum of pathophysiologies including chronic bronchitis, small airways disease and emphysema. COPD caused an estimated 3 million deaths worldwide in 2016, and is estimated to be the third leading cause of death worldwide. The British Lung Foundation (BLF) estimates that the disease costs the NHS around £1.9 billion per year. COPD is therefore a significant public health challenge. This dataset explores the impact of hospitalisation in patients with COPD during the COVID pandemic.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. The West Midlands has a high prevalence of COPD, reflecting the high rates of smoking and industrial exposure. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All hospitalised patients admitted to UHB during the COVID-19 pandemic first wave, curated to focus on COPD. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes ICD-10 & SNOMED-CT codes pertaining to COPD and COPD exacerbations, as well as all co-morbid conditions. Serial, structured data pertaining to process of care (timings, staff grades, specialty review, wards), presenting complaint, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, nebulisers, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT).

Available supplementary data: More extensive data including wave 2 patients in non-OMOP form. Ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

These indicators are designed to accompany the SHMI publication. The SHMI methodology does not make any adjustment for deprivation. This is because adjusting for deprivation might create the impression that a higher death rate for those who are more deprived is acceptable. Patient records are assigned to 1 of 5 deprivation groups (called quintiles) using the Index of Multiple Deprivation (IMD). The deprivation quintile cannot be calculated for some records e.g. because the patient's postcode is unknown or they are not resident in England. Contextual indicators on the percentage of provider spells and deaths reported in the SHMI belonging to each deprivation quintile are produced to support the interpretation of the SHMI. Notes: 1. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. Activity that is being coded as COVID-19, and therefore excluded, is monitored in the contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there was a fall in the overall number of spells from March 2020 due to COVID-19 impacting on activity for England and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for County Durham and Darlington NHS Foundation Trust (trust code RXP), East Lancashire Hospitals NHS Trust (trust code RXR), Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1), King’s College Hospital NHS Foundation Trust (trust code RJZ) and The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 6. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

Provisional counts of the number of deaths and age-standardised mortality rates involving the coronavirus (COVID-19), by occupational groups, for deaths registered between 9 March and 28 December 2020 in England and Wales. Figures are provided for males and females.

Adjusted odds ratios with 95% confidence interval from multivariable logistic regression model with GEE for the outcome COVID-19 mortality.

Abstract copyright UK Data Service and data collection copyright owner. The UCL COVID-19 Social Study at University College London (UCL) was launched on 21 March 2020. Led by Dr Daisy Fancourt and Professor Andrew Steptoe from the Department of Behavioural Science and Health, the team designed the study to track in real-time the psychological and social impact of the virus across the UK. The study quickly became the largest in the country, growing to over 70,000 participants and providing rare and privileged insight into the effects of the pandemic on people’s daily lives. Through our participants’ remarkable two-year commitment to the study, 1.2 million surveys were collected over 105 weeks, and over 100 scientific papers and 44 public reports were published. During COVID-19, population mental health has been affected both by the intensity of the pandemic (cases and death rates), but also by lockdowns and restrictions themselves. Worsening mental health coincided with higher rates of COVID-19, tighter restrictions, and the weeks leading up to lockdowns. Mental health then generally improved during lockdowns and most people were able to adapt and manage their well-being. However, a significant proportion of the population suffered disproportionately to the rest, and stay-at-home orders harmed those who were already financially, socially, or medically vulnerable. Socioeconomic factors, including low SEP, low income, and low educational attainment, continued to be associated with worse experiences of the pandemic. Outcomes for these groups were worse throughout many measures including mental health and wellbeing; financial struggles;self-harm and suicide risk; risk of contracting COVID-19 and developing long Covid; and vaccine resistance and hesitancy. These inequalities existed before the pandemic and were further exacerbated by COVID-19, and such groups remain particularly vulnerable to the future effects of the pandemic and other national crises.Further information, including reports and publications, can be found on the UCL COVID-19 Social Study website. Main Topics: The study asked baseline questions on the following: Demographics, including year of birth, sex, ethnicity, relationship status, country of dwelling, urban/rural dwelling, type of accommodation, housing tenure, number of adults and children in the household, household income, education, employment status, pet ownership, and personality. Health and health behaviours, including pre-existing physical health conditions, diagnosed mental health conditions, pregnancy, smoking, alcohol consumption, physical activity, caring responsibilities, usual social behaviours, and social network size. It also asked repeated questions at every wave on the following: COVID-19 status, including whether the respondent had had COVID-19, whether they had come into likely contact with COVID-19, current isolation status and motivations for isolation, length of isolation, length of time not leaving the home, length of time not contacting others, trust in government, trust in the health service, adherence to health advice, and experience of adverse events due to COVID-19 (including severe illness within the family, bereavement, redundancy, or financial difficulties). Mental health, including wellbeing, depression, anxiety, which factors were causing stress, sleep quality, loneliness, social isolation, and changes in health behaviours such as smoking, drinking and exercise. How people were spending their time whilst in isolation, including questions on working, functional household activities, care, and schooling of any children in the household, hobbies, and relaxation. Certain waves of the study also included one-off modules on topics including volunteering behaviours, locus of control, frustrations and expectations, coping styles, fear of COVID-19, resilience, arts and creative engagement, life events, weight, gambling behaviours, mental health diagnosis, use of financial support, faith and religion, relationships, neighbourhood satisfaction, healthcare usage, discrimination experiences, life changes, optimism, long COVID and COVID-19 vaccination.

The Care in Funerals project drew upon 67 semi-structured qualitative interviews with 68 individuals who had been bereaved, and/or worked or volunteered in deathcare and funeral provision in the UK during the COVID-19 pandemic. Interviews explored their experiences during the pandemic, evaluations of what was good and what was less good, how they responded, and suggestions of what might be improved going forward. They also examined what interviewees understood by the term 'care' in relation to funerals.

All participants gave informed consent to participate. Interviews had a mean length of one hour, and were conducted using video calling software or, in some cases, telephone, between April 2021 and April 2022.

This dataset consists of 63 transcripts (two interviewees were interviewed together in one case) all of which have had identifying details removed such that the participants cannot be identified. Four transcripts have been withheld as permission was not granted by participants for their inclusion in a data repository.

Funeral provision in the UK was significantly disrupted when COVID-19 infection control policies constrained how and by whom bodies could be attended to and moved to burial/cremation sites; how funeral directors and celebrants could communicate with bereaved families; and possibilities for gathering for funerals, mourning and memorialising activities. The regulations generated significant distress and perceptions of injustice. They also prompted the development of new funeral practices - inviting important questions about funeral provision. Our interdisciplinary research starts from a recognition of funeral provision as a form of care (and set of caring practices) oriented towards people who have died and their bereaved family, friends and communities. It addresses neglected ethical aspects of funeral provision, including, in the context of COVID-19, questions of fairness and the moral dimensions of distress evident in family members' and funeral directors' worries about not fulfilling important responsibilities, or doing wrong, to those who have died or been bereaved. Our ethical analyses will be grounded in an ethnographic examination of changed practices and experiences that includes: (1) analysis of funeral artefacts, including online films, tribute pages, and written accounts; (2) interviews with diverse bereaved family members, funeral directors and celebrants. We will attend carefully to what people consider good and right (or not) and why in different circumstances. We will develop practical ethical analyses of post-death care that address tensions between different purposes of funerals and diverse perspectives on post-death responsibilities. Discussion events with key stakeholders will inform the development of resources for future policy and practice.