In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. As of December 2023, the South East had the highest number of confirmed first episode cases of the virus in the UK with 3,180,101 registered cases, while London had 2,947,727 confirmed first-time cases. Overall, there has been 24,243,393 confirmed cases of COVID-19 in the UK as of January 13, 2023.

COVID deaths in the UK COVID-19 was responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK had the highest death toll from coronavirus in western Europe. The incidence of deaths in the UK was 297.8 per 100,000 population as January 13, 2023.

Current infection rate in Europe The infection rate in the UK was 43.3 cases per 100,000 population in the last seven days as of March 13, 2023. Austria had the highest rate at 224 cases per 100,000 in the last week.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Due to changes in the collection and availability of data on COVID-19, this dataset is no longer updated.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

As of January 12, 2023, COVID-19 has been responsible for 202,157 deaths in the UK overall. The North West of England has been the most affected area in terms of deaths at 28,116, followed by the South East of England with 26,221 coronavirus deaths. Furthermore, there have been 22,264 mortalities in London as a result of COVID-19.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

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.

Although an international chain, its base and the majority of Pret a Manger (Pret) stores are in the UK and in London in particular. The continual development and communication strategies that the company has undertaken in this market have demonstrated both the long-term strategies that foodservice operators need to build on in order to comply with consumer demands and lifestyles but also the short-term engagement opportunities that are vital in maintaining and inspiring a loyal consumer base, especially during the developing coronavirus pandemic. Read More

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 has been a fall in the overall number of spells due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Further information is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for this trust should therefore be interpreted with caution. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.

For the week ending March 7, 2025, weekly deaths in England and Wales were 124 below the number expected, compared with 460 fewer than expected in the previous week. In late 2022, and through early 2023, excess deaths were elevated for a number of weeks, with the excess deaths figure for the week ending January 13, 2023, the highest since February 2021. In the middle of April 2020, at the height of the Coronavirus (COVID-19) pandemic, there were almost 12,000 excess deaths a week recorded in England and Wales. It was not until two months later, in the week ending June 19, 2020, that the number of deaths began to be lower than the five-year average for the corresponding week. Most deaths since 1918 in 2020 In 2020, there were 689,629 deaths in the United Kingdom, making that year the deadliest since 1918, at the height of the Spanish influenza pandemic. As seen in the excess death figures, April 2020 was by far the worst month in terms of deaths during the pandemic. The weekly number of deaths for weeks 16 and 17 of that year were 22,351, and 21,997 respectively. Although the number of deaths fell to more usual levels for the rest of that year, a winter wave of the disease led to a high number of deaths in January 2021, with 18,676 deaths recorded in the fourth week of that year. For the whole of 2021, there were 667,479 deaths in the UK, 22,150 fewer than in 2020. Life expectancy in the UK goes into reverse In 2022, life expectancy at birth for women in the UK was 82.6 years, while for men it was 78.6 years. This was the lowest life expectancy in the country for ten years, and came after life expectancy improvements stalled throughout the 2010s, and then declined from 2020 onwards. There is also quite a significant regional difference in life expectancy in the UK. In the London borough of Kensington and Chelsea, for example, the life expectancy for men was 81.5 years, and 86.5 years for women. By contrast, in Blackpool, in North West England, male life expectancy was just 73.1 years, while for women life expectancy was lowest in Glasgow, at 78 years.

These indicators are designed to accompany the SHMI publication. 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. There has been a fall in the number of spells for some trusts due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Contextual indicators on the number of provider spells which are excluded from the SHMI due to them being related to COVID-19 and on the number of provider spells as a percentage of pre-pandemic activity (January 2019 – December 2019) are produced to support the interpretation of the SHMI. These indicators are being published as experimental statistics. Experimental statistics are official statistics which are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. Notes: 1. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. Maidstone and Tunbridge Wells NHS Trust (trust code RWF) has submitted a number of records with a patient classification of ‘day case’ or ‘regular day attender’ and an intended management value of ‘patient to stay in hospital for at least one night’. This mismatch has resulted in the patient classification being updated to ‘ordinary admission’ by the Hospital Episode Statistics (HES) data cleaning rules. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for these trusts should therefore be interpreted with caution. 2. There is a shortfall in the number of records for Royal Free London NHS Foundation Trust (trust code RAL) and Northern Care Alliance NHS Foundation Trust (trust code RM3). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 3. A proposed merger between Northern Devon Healthcare NHS Trust (trust code RBZ) and Royal Devon and Exeter NHS Foundation Trust (trust code RH8) was due to take place on 1 April 2022. The new trust name and code is yet to be confirmed. Please note that separate indicator values have been produced for these organisations for this publication. When we receive confirmation of the new trust name and code we will reflect the new organisation structure within future publications. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.

This report and dataset were commissioned by the Greater London Authority, and produced by Centric Lab to uncover the work of community groups that connect with environmental issues in Hackney, Newham, Tower Hamlets and Waltham Forest.

These four boroughs were selected as they have some of the highest representation of multi-ethnic low income communities who were greatly affected by the coronavirus pandemic. Many reports highlighted the role of environmental pollutants and structural deprivation as a determinant of Covid-19 infection and impact.

As evidenced in this report communities demonstrate numerous and diverse capabilities in tackling the structural challenges of modern day London. This report highlights the different community groups committed to improving the lives of their families, neighbours, and future generations who grace the place they call home. The Mayor of London’s Engaging Londoners in Recovery Programme 2021-2023 sets out an agenda to champion this intellect and capacity to help deliver bottom-up led change in policy such as that of a Green New Deal for London.

This report was produced in late 2021 and early 2022 when ‘Plan B’ Covid-19 restrictions were in place for most of its duration. This project was a desktop study and focused on working remotely. All data was gathered through online means and digital communications. This means that despite collating the amazing work of 143 organisations there’s a chance some were missed due to low digital visibility.

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. 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 has been a fall in the overall number of spells due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Further information is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for this trust should therefore be interpreted with caution. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.

The inequities of the COVID-19 pandemic were clear by April 2020 when data showed that despite being just 3.5% of the population in England, Black people comprised 5.8% of those who died from the virus; whereas White people, comprising 85.3% of the population, were 73.6% of those who died. The disproportionate impact continued with, for example, over-policing: 32% of stop and search in the year ending March 2021 were of Black, Asian and Minority Ethnic (BAME) males aged 15-34, despite them being just 2.6% of the population.

The emergency measures introduced to govern the pandemic worked together to create a damaging cycle affecting Black, Asian and Minority Ethnic families and communities of all ages. Key-workers – often stopped by police on their way to provide essential services – could not furlough or work from home to avoid infection, nor support their children in home-schooling. Children in high-occupancy homes lacked adequate space and/ or equipment to learn; such homes also lacked leisure space for key workers to restore themselves after extended hours at work. Over-policing instilled fear across the generations and deterred BAME people – including the mobile elderly - from leaving crowded homes for legitimate exercise, and those that did faced the risk of receiving a Fixed Penalty Notice and a criminal record.

These insights arose from research by Co-POWeR into the synergistic effects of emergency measures on policing, child welfare, caring, physical activity and nutrition. Using community engagement, a survey with 1000 participants and interviews, focus groups, participatory workshops and community testimony days with over 400 people in total, we explored the combined impact of COVID-19 and discrimination on wellbeing and resilience across BAME FC in the UK. This policy note crystallises our findings into a framework of recommendations relating to arts and media communications, systems and structures, community and individual well-being and resilience. We promote long term actions rather than short term reactions.

In brief, we conclude that ignoring race, gender and class when tackling a pandemic can undermine not only wellbeing across Black, Asian and Minority Ethnic families and communities (BAME FC) but also their levels of trust in government. A framework to protect wellbeing and resilience in BAME FC during public health emergencies was developed by Co-POWeR to ensure that laws and guidance adopted are culturally competent.

Two viruses - COVID-19 and discrimination - are currently killing in the UK (Solanke 2020), especially within BAMEFC who are hardest hit. Survivors face ongoing damage to wellbeing and resilience, in terms of physical and mental health as well as social, cultural and economic (non-medical) consequences. Psychosocial (ADCS 2020; The Children's Society 2020)/ physical trauma of those diseased and deceased, disproportionate job-loss (Hu 2020) multigenerational housing, disrupted care chains (Rai 2016) lack of access to culture, education and exercise, poor nutrition, 'over-policing' (BigBrotherWatch 2020) hit BAMEFC severely. Local 'lockdowns' illustrate how easily BAMEFC become subject to stigmatization and discrimination through 'mis-infodemics' (IOM 2020). The impact of these viruses cause long-term poor outcomes. While systemic deficiencies have stimulated BAMEFC agency, producing solidarity under emergency, BAMEFC vulnerability remains, requiring official support. The issues are complex thus we focus on the interlinked and 'intersectional nature of forms of exclusion and disadvantage', operationalised through the idea of a 'cycle of wellbeing and resilience' (CWAR) which recognises how COVID-19 places significant stress upon BAMEFC structures and the impact of COVID-19 and discrimination on different BAMEFC cohorts across the UK, in whose lives existing health inequalities are compounded by a myriad of structural inequalities. Given the prevalence of multi-generational households, BAMEFC are likely to experience these as a complex of jostling over-lapping stressors: over-policed unemployed young adults are more likely to live with keyworkers using public transport to attend jobs in the front line, serving elders as formal/informal carers, neglecting their health thus exacerbating co-morbidities and struggling to feed children who are unable to attend school, resulting in nutritional and digital deprivation. Historical research shows race/class dimensions to national emergencies (e.g. Hurricane Katrina) but most research focuses on the COVID-19 experience of white families/communities. Co-POWeR recommendations will emerge from culturally and racially sensitive social science research on wellbeing and resilience providing context as an essential strand for the success of biomedical and policy interventions (e.g. vaccines, mass testing). We will enhance official decision-making through strengthening cultural competence in ongoing responses to COVID-19 thereby...

Abstract copyright UK Data Service and data collection copyright owner.

The Health Survey for England (HSE) is a series of surveys designed to monitor trends in the nation's health. It was commissioned by NHS Digital and carried out by the Joint Health Surveys Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health at University College London.
The aims of the HSE series are:

• to provide annual data about the nation’s health;
• to estimate the proportion of people in England with specified health conditions;
• to estimate the prevalence of certain risk factors associated with these conditions;
• to examine differences between population subgroups in their likelihood of having specific conditions or risk factors;
• to assess the frequency with which particular combinations of risk factors are found, and which groups these combinations most commonly occur;
• to monitor progress towards selected health targets
• since 1995, to measure the height of children at different ages, replacing the National Study of Health and Growth;
• since 1995, monitor the prevalence of overweight and obesity in children.

The survey includes a number of core questions every year but also focuses on different health issues at each wave. Topics are revisited at appropriate intervals in order to monitor change.

Further information about the series may be found on the NHS Digital Health Survey for England; health, social care and lifestyles webpage, the NatCen Social Research NatCen Health Survey for England webpage and the University College London Health and Social Surveys Research Group UCL Health Survey for England webpage.

Changes to the HSE from 2015:
Users should note that from 2015 survey onwards, only the individual data file is available under standard End User Licence (EUL). The household data file is now only included in the Special Licence (SL) version, released from 2015 onwards. In addition, the SL individual file contains all the variables included in the HSE EUL dataset, plus others, including variables removed from the EUL version after the NHS Digital disclosure review. The SL HSE is subject to more restrictive access conditions than the EUL version (see Access information). Users are advised to obtain the EUL version to see if it meets their needs before considering an application for the SL version.

COVID-19 and the HSE:
Due to the COVID-19 pandemic, the HSE 2020 survey was stopped in March 2020 and never re-started. There was no publication that year. The survey resumed in 2021, albeit with an amended methodology. The full HSE resumed in 2022, with an extended fieldwork period. Due to this, the decision was taken not to progress with the 2023 survey, to maximise the 2022 survey response and enable more robust reporting of data. See the NHS Digital Health Survey for England - Health, social care and lifestyles webpage for more details.

The 2021 HSE included additional topics on physical activity, wellbeing (including loneliness), and gambling. The survey also provided updates on repeated core topics, including general health, long-standing illness, smoking and drinking.

Main Topics:

Core topics

• General health
• Longstanding illness
• Smoking
• Average weekly alcohol consumption
• Drinking (heaviest day in last week)
• Consent to data linkage (NHS central register, HES)
• Socio-economic information: sex, age, income, education, employment etc
• Prescribed medications (nurse)

Additional topics

• Social care receipt and provision
• Provision of unpaid care
• Dental health
• Use of GP and counselling services
• Eating disorders

Measurements

• Height and weight
• Blood pressure (nurse)
• Waist and hip circumference (nurse)
• Blood sample for cholesterol, glycated haemoglobin (nurse)
• Saliva sample (nurse)

Parameter tuning in the UK case.

Abstract copyright UK Data Service and data collection copyright owner.

The English Longitudinal Study of Ageing (ELSA) study is a longitudinal survey of ageing and quality of life among older people that explores the dynamic relationships between health and functioning, social networks and participation, and economic position as people plan for, move into and progress beyond retirement. The main objectives of ELSA are to:

• construct waves of accessible and well-documented panel data;
• provide these data in a convenient and timely fashion to the scientific and policy research community;
• describe health trajectories, disability and healthy life expectancy in a representative sample of the English population aged 50 and over;
• examine the relationship between economic position and health;
• nvestigate the determinants of economic position in older age;
• describe the timing of retirement and post-retirement labour market activity; and
• understand the relationships between social support, household structure and the transfer of assets.

Further information may be found on the the ELSA project website or the Natcen Social Research: ELSA web pages.

Health conditions research with ELSA - June 2021

The ELSA Data team have found some issues with historical data measuring health conditions. If you are intending to do any analysis looking at the following health conditions, then please contact the ELSA Data team at NatCen on elsadata@natcen.ac.uk for advice on how you should approach your analysis. The affected conditions are: eye conditions (glaucoma; diabetic eye disease; macular degeneration; cataract), CVD conditions (high blood pressure; angina; heart attack; Congestive Heart Failure; heart murmur; abnormal heart rhythm; diabetes; stroke; high cholesterol; other heart trouble) and chronic health conditions (chronic lung disease; asthma; arthritis; osteoporosis; cancer; Parkinson's Disease; emotional, nervous or psychiatric problems; Alzheimer's Disease; dementia; malignant blood disorder; multiple sclerosis or motor neurone disease).

Special Licence Data:

Special Licence Access versions of ELSA have more restrictive access conditions than versions available under the standard End User Licence (see 'Access' section below). Users are advised to obtain the latest edition of SN 5050 (the End User Licence version) before making an application for Special Licence data, to see whether that is suitable for their needs. A separate application must be made for each Special Licence study.

Special Licence Access versions of ELSA include:

• Primary data from Wave 8 onwards (SN 8346) includes all the variables in the EUL primary dataset (SN 5050) as well as year and month of birth, consolidated ethnicity and country of birth, marital status, and more detailed medical history variables.
• Wave 8 Pension Age Data (SN 8375) includes all the variables in the EUL pension age data (SN 5050) as well as year and age reached state pension age variables.
• Wave 8 Sexual Self-Completion Data (SN 8376) includes sensitive variables from the sexual self-completion questionnaire.
• Wave 3 (2007) Harmonized Life History (SN 8831) includes retrospective information on previous histories, specifically, detailed data on previous partnership, children, residential, health, and work histories.
• Detailed geographical identifier files for Waves 1-10 which are grouped by identifier held under SN 8429 (Local Authority District Pre-2009 Boundaries), SN 8439 (Local Authority District Post-2009 Boundaries), SN 8430 (Local Authority Type Pre-2009 Boundaries), SN 8441 (Local Authority Type Post-2009 Boundaries), SN 8431 (Quintile Index of Multiple Deprivation Score), SN 8432 (Quintile Population Density for Postcode Sectors), SN 8433 (Census 2001 Rural-Urban Indicators), SN 8437 (Census 2011 Rural-Urban Indicators).

Where boundary changes have occurred, the geographic identifier has been split into two separate studies to reduce the risk of disclosure. Users are also only allowed one version of each identifier:

• either SN 8429 (Local Authority District Pre-2009 Boundaries) or SN 8439 (Local Authority District Post-2009 Boundaries)
• either SN 8430 (Local Authority Type Pre-2009 Boundaries) or SN 8441(Local Authority Type Post-2009 Boundaries)
• either SN 8433 (Census 2001 Rural-Urban Indicators) or SN 8437 (Census 2011 Rural-Urban Indicators)

ELSA Wave 6 and Wave 8 Self-Completion Questionnaires included an open-ended question where respondents could add any other comments they may wish to note down. These responses have been transcribed and anonymised. Researchers can request access to these transcribed responses for research purposes by contacting the...

The SHMI is the ratio between the actual number of patients who die following hospitalisation at the trust and the number that would be expected to die on the basis of average England figures, given the characteristics of the patients treated there. It includes deaths which occurred in hospital and deaths which occurred outside of hospital within 30 days (inclusive) of discharge. Deaths related to COVID-19 are excluded from the SHMI. The SHMI gives an indication for each non-specialist acute NHS trust in England whether the observed number of deaths within 30 days of discharge from hospital was 'higher than expected' (SHMI banding=1), 'as expected' (SHMI banding=2) or 'lower than expected' (SHMI banding=3) when compared to the national baseline. Trusts may be located at multiple sites and may be responsible for 1 or more hospitals. A breakdown of the data by site of treatment is also provided. The SHMI is composed of 142 different diagnosis groups and these are aggregated to calculate the overall SHMI value for each trust. The number of finished provider spells, observed deaths and expected deaths at diagnosis group level for each trust is available in the SHMI diagnosis group breakdown files. For a subset of diagnosis groups, an indication of whether the observed number of deaths within 30 days of discharge from hospital was 'higher than expected', 'as expected' or 'lower than expected' when compared to the national baseline is also provided. Details of the 142 diagnosis groups can be found in Appendix A of the SHMI specification. 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 has been a fall in the overall number of spells due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Further information is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. Maidstone and Tunbridge Wells NHS Trust (trust code RWF) has submitted a number of records with a patient classification of ‘day case’ or ‘regular day attender’ and an intended management value of ‘patient to stay in hospital for at least one night’. This mismatch has resulted in the patient classification being updated to ‘ordinary admission’ by the Hospital Episode Statistics (HES) data cleaning rules. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for these trusts should therefore be interpreted with caution. 4. There is a shortfall in the number of records for Royal Free London NHS Foundation Trust (trust code RAL). Values for this trust are based on incomplete data and should therefore be interpreted with caution. 5. On 1st April 2022 Northern Devon Healthcare NHS Trust (trust code RBZ) merged with Royal Devon and Exeter NHS Foundation Trust (trust code RH8). The new trust is called Royal Devon University Healthcare NHS Foundation Trust (trust code RH8). This new organisation structure is reflected from this publication onwards. 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.

Between 1953 and 2021, the death rate of the United Kingdom fluctuated between a high of 12.2 deaths per 1,000 people in 1962 and a low of 8.7 in 2011. From 2011 onwards, the death rate creeped up slightly and, in 2020, reached 10.3 deaths per 1,000 people. In 2021, the most recent year provided here, the death rate was ten, a decline from 2020 but still higher than in almost every year in the twenty-first century. The recent spike in the death rate corresponds to the emergence of the COVID-19 pandemic in the UK, with the first cases recorded in early 2020. Most deaths since 1918 in 2020 In 2020, there were 689,629 deaths in the United Kingdom, the highest in more than a century. Although there were fewer deaths in 2021, at 667,479, this was still far higher than in recent years. When looking at the weekly deaths in England and Wales for this time period, two periods stand out for reporting far more deaths than usual. The first period was between weeks 13 and 22 of 2020, which saw two weeks in late April report more than 20,000 deaths. Excess deaths for the week ending April 17, 2020, were 11,854, and 11,539 for the following week. Another wave of deaths occurred in January 2021, when there were more than 18,000 deaths per week between weeks three and five of that year. Improvements to life expectancy slowing Between 2020 and 2022, life expectancy in the United Kingdom was approximately 82.57 years for women and 78.57 years for men. Compared with life expectancy in 1980/82 this marked an increase of around six years for women and almost eight years for men. Despite these long-term developments, improvements to life expectancy have been slowing in recent years, and have declined since 2017/19. As of 2022, the country with the highest life expectancy in the World was Japan, which was 84.5 years, followed by South Korea, at 83.6 years.

These indicators are designed to accompany the SHMI publication. The SHMI methodology does not make any adjustment for patients who are recorded as receiving palliative care. This is because there is considerable variation between trusts in the way that palliative care is recorded. Contextual indicators on the percentage of provider spells and deaths reported in the SHMI where palliative care was recorded at either treatment or specialty level 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 has been a fall in the overall number of spells due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Further information is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for this trust should therefore be interpreted with caution. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.

Abstract copyright UK Data Service and data collection copyright owner.

The Health Survey for England (HSE) is a series of surveys designed to monitor trends in the nation's health. It was commissioned by NHS Digital and carried out by the Joint Health Surveys Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health at University College London.
The aims of the HSE series are:

• to provide annual data about the nation's health;
• to estimate the proportion of people in England with specified health conditions;
• to estimate the prevalence of certain risk factors associated with these conditions;
• to examine differences between population subgroups in their likelihood of having specific conditions or risk factors;
• to assess the frequency with which particular combinations of risk factors are found, and which groups these combinations most commonly occur;
• to monitor progress towards selected health targets
• since 1995, to measure the height of children at different ages, replacing the National Study of Health and Growth;
• since 1995, monitor the prevalence of overweight and obesity in children.

The survey includes a number of core questions every year but also focuses on different health issues at each wave. Topics are revisited at appropriate intervals in order to monitor change.

Further information about the series may be found on the NHS Digital Health Survey for England; health, social care and lifestyles webpage, the NatCen Social Research NatCen Health Survey for England webpage and the University College London Health and Social Surveys Research Group UCL Health Survey for England webpage.

Changes to the HSE from 2015:
Users should note that from 2015 survey onwards, only the individual data file is available under standard End User Licence (EUL). The household data file is now only included in the Special Licence (SL) version, released from 2015 onwards. In addition, the SL individual file contains all the variables included in the HSE EUL dataset, plus others, including variables removed from the EUL version after the NHS Digital disclosure review. The SL version of the dataset contains variables with a higher disclosure risk or are more sensitive than those included in the EUL version and is subject to more restrictive access conditions (see Access information). Users are advised to obtain the EUL version to see if it meets their needs before considering an application for the SL version.

COVID-19 and the HSE:
Due to the COVID-19 pandemic, the HSE 2020 survey was stopped in March 2020 and never re-started. There was no publication that year. The survey resumed in 2021, albeit with an amended methodology. The full HSE resumed in 2022, with an extended fieldwork period. Due to this, the decision was taken not to progress with the 2023 survey, to maximise the 2022 survey response and enable more robust reporting of data. See the NHS Digital Health Survey for England - Health, social care and lifestyles webpage for more details.

The Health Survey for England, 2017 EUL version is available from the UK Data Archive under SN 8488.
Main Topics:

The data covers the following:

Core topics:                        

• General health
• Longstanding illness
• Average weekly alcohol consumption
• Smoking
• Drinking (heaviest day in last week)
• Fruit and vegetable consumption
• Consent to data linkage (NHS central register, HES)
• Socio-economic information: sex, age, income, education, employment
• Prescribed medications (nurse)

Additional topics:

• Physical activity...

These indicators are designed to accompany the SHMI publication. As well as information on the main condition the patient is in hospital for (the primary diagnosis), the SHMI data contain up to 19 secondary diagnosis codes for other conditions the patient is suffering from. This information is used to calculate the expected number of deaths. 'Depth of coding' is defined as the number of secondary diagnosis codes for each record in the data. A higher mean depth of coding may indicate a higher proportion of patients with multiple conditions and/or comorbidities, but may also be due to differences in coding practices between trusts. Contextual indicators on the mean depth of coding for elective and non-elective admissions 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 has been a fall in the overall number of spells due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Further information is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. Maidstone and Tunbridge Wells NHS Trust (trust code RWF) has submitted a number of records with a patient classification of ‘day case’ or ‘regular day attender’ and an intended management value of ‘patient to stay in hospital for at least one night’. This mismatch has resulted in the patient classification being updated to ‘ordinary admission’ by the Hospital Episode Statistics (HES) data cleaning rules. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for these trusts should therefore be interpreted with caution. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.