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.

In early-February, 2020, the first cases of the coronavirus (COVID-19) were reported in the United Kingdom (UK). The number of cases in the UK has since risen to 24,243,393, with 1,062 new cases reported on January 13, 2023. The highest daily figure since the beginning of the pandemic was on January 6, 2022 at 275,646 cases.

COVID deaths in the UK COVID-19 has so far been responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK has one of the highest death toll from COVID-19 in Europe. As of January 13, the incidence of deaths in the UK is 298 per 100,000 population.

Regional breakdown The South East has the highest amount of cases in the country with 3,123,050 confirmed cases as of January 11. London and the North West have 2,912,859 and 2,580,090 cases respectively.

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

On March 4, 2020, the first death as a result of coronavirus (COVID-19) was recorded in the United Kingdom (UK). The number of deaths in the UK has increased significantly since then. As of January 13, 2023, the number of confirmed deaths due to coronavirus in the UK amounted to 202,157. On January 21, 2021, 1,370 deaths were recorded, which was the highest total in single day in the UK since the outbreak began.

Number of deaths among highest in Europe
The UK has had the highest number of deaths from coronavirus in western Europe. In terms of rate of coronavirus deaths, the UK has recorded 297.8 deaths per 100,000 population.

Cases in the UK The number of confirmed cases of coronavirus in the UK was 24,243,393 as of January 13, 2023. The South East has the highest number of first-episode confirmed cases of the virus in the UK with 3,123,050 cases, while London and the North West have 2,912,859 and 2,580,090 confirmed cases respectively. As of January 16, the UK has had 50 new cases per 100,000 in the last seven days.

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 page will no longer be updated. The webpage will no longer be available as of 11 May 2023. On-going, reliable sources of data for COVID-19 are available via the COVID-19 dashboard, Office for National Statistics, and the UKHSA

This page provides a weekly summary of data on deaths related to COVID-19 published by NHS England and the Office for National Statistics. More frequent reporting on COVID-19 deaths is now available here, alongside data on cases, hospitalisations, and vaccinations. This update contains data on deaths related to COVID-19 from:

NHS England COVID-19 Daily Deaths - last updated on 28 June 2022 with data up to and including 27 June 2022.


ONS weekly deaths by Local Authority - last updated on 16 August 2022 with data up to and including 05 August 2022.

Summary notes about each these sources are provided at the end of this document.

Note on interpreting deaths data: statistics from the available sources differ in definition, timing and completeness. It is important to understand these differences when interpreting the data or comparing between sources.

Weekly Key Points

An additional 24 deaths in London hospitals of patients who had tested positive for COVID-19 and an additional 5 where COVID-19 was mentioned on the death certificate were announced in the week ending 27 June 2022. This compares with 40 and 3 for the previous week. A total of 306 deaths in hospitals of patients who had tested positive for COVID-19 and 27 where COVID-19 was mentioned on the death certificate were announced for England as whole. This compares with 301 and 26 for the previous week. The total number of COVID-19 deaths reported in London hospitals of patients who had tested positive for COVID-19 is now 19,102. The total number of deaths in London hospitals where COVID-19 was mentioned on the death certificate is now 1,590. This compares to figures of 119,237 and 8,197 for English hospitals as a whole. Due to the delay between death occurrence and reporting, the estimated number of deaths to this point will be revised upwards over coming days These figures do not include deaths that occurred outside of hospitals. Data from ONS has indicated that the majority (79%) of COVID-19 deaths in London have taken place in hospitals.

Recently announced deaths in Hospitals

21 June 22 June 23 June 24 June 25 June 26 June 27 June London No positive test 0 0 1 4 0 0 0 London Positive test 3 7 2 10 0 0 2 Rest of England No positive test 2 6 4 4 0 0 6 Rest of England Positive test 47 49 41 58 6 0 81

16 May 23 May 30 May 06 June 13 June 20 June 27 June London No positive test 14 3 4 0 4 3 5 London Positive test 45 34 55 20 62 40 24 Rest of England No positive test 41 58 33 23 47 23 22 Rest of England Positive test 456 375 266 218 254 261 282 Deaths by date of occurrence

21 June 22 June 23 June 24 June 25 June 26 June 27 June London 20,683 20,686 20,690 20,691 20,692 20,692 20,692 Rest of England 106,604 106,635 106,679 106,697 106,713 106,733 106,742 Interpreting the data The data published by NHS England are incomplete due to:

delays in the occurrence and subsequent reporting of deaths deaths occurring outside of hospitals not being included

The total deaths reported up to a given point are therefore less than the actual number that have occurred by the same point. Delays in reporting NHS provide the following guidance regarding the delay between occurrence and reporting of deaths: Confirmation of COVID-19 diagnosis, death notification and reporting in central figures can take up to several days and the hospitals providing the data are under significant operational pressure. This means that the totals reported at 5pm on each day may not include all deaths that occurred on that day or on recent prior days. The data published by NHS England for reporting periods from April 1st onward includes both date of occurrence and date of reporting and so it is possible to illustrate the distribution of these reporting delays. This data shows that approximately 10% of COVID-19 deaths occurring in London hospitals are included in the reporting period ending on the same day, and that approximately two-thirds of deaths were reported by two days after the date of occurrence.

Deaths outside of hospitals The data published by NHS England does not include deaths that occur outside of hospitals, i.e. those in homes, hospices, and care homes. ONS have published data for deaths by place of occurrence. This shows that, up to 05 August, 79% of deaths in London recorded as involving COVID-19 occurred in hospitals (this compares with 44% for all causes of death). This would suggest that the NHS England data may underestimate overall deaths from COVID-19 by around 20%.

Comparison of data sources

Note on data sources

NHS England provides numbers of patients who have died in hos

Vaccinations in London Between 8 December 2020 and 15 September 2021 5,838,305 1st doses and 5,232,885 2nd doses have been administered to London residents.

Differences in vaccine roll out between London and the Rest of England London Rest of England Priority Group Vaccinations given Percentage vaccinated Vaccinations given Percentage vaccinated Group 1 Older Adult Care Home Residents 21,883 95% 275,964 96% Older Adult Care Home Staff 29,405 85% 381,637 88% Group 2 80+ years 251,021 83% 2,368,284 93% Health Care Worker 174,944 99% 1,139,243 100%* Group 3 75 - 79 years 177,665 90% 1,796,408 99% Group 4 70 - 74 years 252,609 90% 2,454,381 97% Clinically Extremely Vulnerable 278,967 88% 1,850,485 95% Group 5 65 - 69 years 285,768 90% 2,381,250 97% Group 6 At Risk or Carer (Under 65) 983,379 78% 6,093,082 88% Younger Adult Care Home Residents 3,822 92% 30,321 93% Group 7 60 - 64 years 373,327 92% 2,748,412 98% Group 8 55 - 59 years 465,276 91% 3,152,412 97% Group 9 50 - 54 years 510,132 90% 3,141,219 95% Data as at 15 September 2021 for age based groups and as at 12 September 2021 for non-age based groups * The number who have received their first dose exceeds the latest official estimate of the population for this group There is considerable uncertainty in the population denominators used to calculate the percentage vaccinated. Comparing implied vaccination rates for multiple sources of denominators provides some indication of uncertainty in the true values. Confidence is higher where the results from multiple sources agree more closely. Because the denominator sources are not fully independent of one another, users should interpret the range of values across sources as indicating the minimum range of uncertainty in the true value. The following datasets can be used to estimate vaccine uptake by age group for London:

ONS 2020 mid-year estimates (MYE). This is the population estimate used for age groups throughout the rest of the analysis.


Number of people ages 18 and over on the National Immunisation Management Service (NIMS)


ONS Public Health Data Asset (PHDA) dataset. This is a linked dataset combining the 2011 Census, the General Practice Extraction Service (GPES) data for pandemic planning and research and the Hospital Episode Statistics (HES). This data covers a subset of the population.

Vaccine roll out in London by Ethnic Group Understanding how vaccine uptake varies across different ethnic groups in London is complicated by two issues:

Ethnicity information for recipients is unavailable for a very large number of the vaccinations that have been delivered. As a result, estimates of vaccine uptake by ethnic group are highly sensitive to the assumptions about and treatment of the Unknown group in calculations of rates.

For vaccinations given to people aged 50 and over in London nearly 10% do not have ethnicity information available,

The accuracy of available population denominators by ethnic group is limited. Because ethnicity information is not captured in official estimates of births, deaths, and migration, the available population denominators typically rely on projecting forward patterns captured in the 2011 Census. Subsequent changes to these patterns, particularly with respect to international migration, leads to increasing uncertainty in the accuracy of denominators sources as we move further away from 2011.

Comparing estimated population sizes and implied vaccination rates for multiple sources of denominators provides some indication of uncertainty in the true values. Confidence is higher where the results from multiple sources agree more closely. Because the denominator sources are not fully independent of one another, users should interpret the range of values across sources as indicating the minimum range of uncertainty in the true value. The following population estimates are available by Ethnic group for London:

GLA Ethnic group population projections - 2016 as at 2021


ONS Population Denominators produced for Race Disparity Audit as at 2018


ETHPOP population projections produced by the University of Leeds as at 2020

Antibody prevalence estimates As part of the ONS Coronavirus (COVID-19) Infection Survey ONS publish a modelled estimate of the percent of the adult population testing positive for antibodies to Coronavirus by region. Antibodies can be generated by vaccination or previous infection.

Vaccine effects on cases, hospitalisations and deaths When the vaccine roll out began in December 2020 coronavirus cases, hospital admissions and deaths were rising steeply. The peak of infections came in London in early January 2021, before reducing during the national lockdown and as the vaccine roll out progressed. As the vaccine roll out began in older age groups the effect of vaccinations can be separated from the effect of national lockdown by comparing changes in cases, admissions and deaths

This mapping tool enables you to see how COVID-19 deaths in your area may relate to factors in the local population, which research has shown are associated with COVID-19 mortality. It maps COVID-19 deaths rates for small areas of London (known as MSOAs) and enables you to compare these to a number of other factors including the Index of Multiple Deprivation, the age and ethnicity of the local population, extent of pre-existing health conditions in the local population, and occupational data. Research has shown that the mortality risk from COVID-19 is higher for people of older age groups, for men, for people with pre-existing health conditions, and for people from BAME backgrounds. London boroughs had some of the highest mortality rates from COVID-19 based on data to April 17th 2020, based on data from the Office for National Statistics (ONS). Analysis from the ONS has also shown how mortality is also related to socio-economic issues such as occupations classified ‘at risk’ and area deprivation. There is much about COVID-19-related mortality that is still not fully understood, including the intersection between the different factors e.g. relationship between BAME groups and occupation. On their own, none of these individual factors correlate strongly with deaths for these small areas. This is most likely because the most relevant factors will vary from area to area. In some cases it may relate to the age of the population, in others it may relate to the prevalence of underlying health conditions, area deprivation or the proportion of the population working in ‘at risk occupations’, and in some cases a combination of these or none of them. Further descriptive analysis of the factors in this tool can be found here: https://data.london.gov.uk/dataset/covid-19--socio-economic-risk-factors-briefing

Context:

The fate of the world changed in 2020.

Daily activities were impacted, impeded, and wouldn't be the same forever.

In partnership with Microsoft and the University of Oxford, A Tale of Two Cities is a Data AI hackathon that aims to address trends during and after the pandemic.

I will present my work at this hackathon through my association with the University of Oxford as an AI Tutor for the Artificial Intelligence: Cloud and Edge Implementations course.

Acknowledgments:

I'd like to thank the original authors of these data sources!

Relevant data was extracted from these sources and split into two phases: - COVID era (before 1st February, 2022), and - Post COVID era (after 1st February, 2022)

This helped me to compare trends in New York and London over time. https://i.imgur.com/KFRaB51.png" alt="">

As of October 3, 2023, there were 2,189,008 confirmed cases of coronavirus (COVID-19) in Scotland. The Greater Glasgow and Clyde health board has the highest amount of confirmed cases at 514,117, although this is also the most populated part of Scotland. The Lothian health board has 368,930 confirmed cases which contains Edinburgh, the capital city of Scotland.

Situation in the rest of the UK Across the whole of the UK there have been 24,243,393 confirmed cases of coronavirus as of January 2023. Scotland currently has fewer cases than four regions in England. As of December 2023, the South East has the highest number of confirmed first-episode cases of the virus in the UK with 3,180,101 registered cases, while London and the North West have 2,947,7271 and 2,621,449 confirmed cases, respectively.

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

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

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.

COVID-19 causes significant mortality in elderly and vulnerable people and spreads easily in care homes where one in seven individuals aged > 85 years live. However, there is no surveillance for infection in care homes, nor are there systems (or research studies) monitoring the impact of the pandemic on individuals or systems. Usual practices are disrupted during the pandemic, and care home staff are taking on new and unfamiliar roles, such as advanced care planning. Understanding the nature of these changes is critical to mitigate the impact of COVID-19 on residents, relatives and staff. 20 care homes staff members were interviewed using semi-structured interviews.

The COVID-19 pandemic poses a substantial risk to elderly and vulnerable care home residents and COVID-19 can spread rapidly in care homes. We have national, daily data on people with COVID-19 and deaths, but there is no similar data for care homes. This makes it difficult to know the scale of the problem, and plan how to keep care home residents safe. We also want to understand the impact of COVID-19 on care home staff and residents. Researchers from University College London (UCL) will measure the number of cases of COVID-19 in care homes, using data from Four Seasons Healthcare, a large care home chain. FSHC remove residents' names and addresses before sending the dataset to UCL, protecting resident's confidentiality. Since we cannot visit care homes during the pandemic, we will hold virtual (online) discussion meetings with care home stakeholders (staff, residents, relatives, General Practice teams) every 6-8 weeks, to learn rapid lessons about managing COVID-19 in care homes and identify pragmatic solutions. Our findings will be shared with FHSC, GPs and Public Health England, patients and the public, and support the national response to COVID-19. Patients and the public will be involved in all stages of the research.

This is an indicator designed to accompany the Summary Hospital-level Mortality Indicator (SHMI). 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. This indicator shows the number of provider spells which are coded as COVID-19, and therefore excluded from the SHMI, as a percentage of all provider spells in the SHMI (prior to the exclusion). This indicator is being published as an experimental statistic. 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. Please note that there has been a fall in the number of spells for most trusts between this publication and the previous SHMI publication, ranging from 0 per cent to 5 per cent. This is due to COVID-19 impacting on activity from March 2020 onwards and appears to be an accurate reflection of hospital activity rather than a case of missing data. 2. The data for St Helens and Knowsley Teaching Hospitals NHS Trust (trust code RBN) has incomplete information on secondary conditions that the patients suffers from, and this will have affected the calculation of this indicator. Values for this trust should therefore be interpreted with caution. Please note, this issue was not identified until after this publication was initially released on 13th May 2021. Data quality notices were later added to this publication in July 2021. 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 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 Mid Cheshire Hospitals NHS Foundation Trust (trust code RBT), meaning that values for this trust are based on incomplete data and should therefore be interpreted with caution. 5. We recommend that values for Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1) are interpreted with caution as there is a possible shortfall in the number of records which is currently under investigation. 6. On 1 April 2021 Western Sussex Hospitals NHS Foundation Trust (trust code RYR) merged with Brighton and Sussex University Hospitals NHS Trust (trust code RXH). The new trust is called University Hospitals Sussex NHS Foundation Trust (trust code RYR). However, as we received notification of this change after data processing for this publication began, separate indicator values have been produced for this publication. The next publication in this series will reflect the updated organisation structure. 7. 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.

Russia had over 23 million COVID-19 cases as of October 22, 2023. Over the past week, that figure increased by nearly 20 thousand. Russia had the 10th-highest number of coronavirus (COVID-19) cases worldwide. Debate about COVID-19 deaths in Russia The number of deaths from the disease was lower than in other countries most affected by the pandemic. Several foreign media sources, including New York Times and Financial Times, published articles suggesting that the official statistics on the COVID-19 death toll in Russia could be lowered. A narrow definition of a death from COVID-19 and a general increase in mortality in Moscow were pointed out while suggesting why actual death figures could be higher than reported. Russian explanation of lower COVID-19 deaths Experts and lawmakers from Russia provided several answers to the accusations. Among them were the fact that Russians timely reported symptoms to doctors, a high number of tests conducted, as well as a higher herd immunity of the population compared to other countries. In a letter to the New York Times, Moscow’s health department head argued that even if all the additional death cases in the Russian capital in April 2020 were categorized as caused by the COVID-19, the city’s mortality rate from the disease would still be lower than in cities like New York or London.For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This is a summary report on the economic impact of COVID-19 on London’s small and medium enterprises (SMEs). It presents a uniquely granular and timely analysis of the impacts on London’s SMEs by sectoral, financial, employment, and risk indicators and includes deep dive case studies on the economic impact on the Night Time Economy, high streets and town centres, and the Culture and Creative industries. The analysis was undertaken on a pro bono basis by Bloomberg Associates, for and in close collaboration with the GLA providing guidance and direction. Partners supporting Bloomberg Associates included Slalom, Burning Glass Technologies, DueDil and CK Delta. It leverages a combination of public and private data from a range of financial, economic, behavioural, sociographic and demographic sources and complements the macro-economic scenarios for the London economy. The study was conducted between March 2020 and June 2020 and leverages the most updated data that was available at the time. It is important to note that new data and evidence constantly emerges and could be integrated in a potential future iteration of this work. The report has sought to: Illustrate the impact of the pandemic on London’s SMEs and local employment and improve understanding of the scale and scope of the economic challenges that London faces in recovery. Demonstrate the application of “bottom-up” and localised data to create a more complete, granular picture of overall economic impact Show the intersection of impact by sectors and geographies, exploring the relationship between these two factors to demonstrate the risk hot spots across Greater London. If you have any comments or questions related to the report, please email GLA Economics

This dataset supports the thesis titled: Domain-Specific Modelling Languages for Participatory Agent-Based Modelling in HealthcareThis is a dataset showing the core data output collected from executing our first case study ABM.

The COVID Symptom Tracker (https://covid.joinzoe.com/) mobile application was designed by doctors and scientists at King's College London, Guys and St Thomas’ Hospitals working in partnership with ZOE Global Ltd – a health science company.

This research is led by Dr Tim Spector, professor of genetic epidemiology at King’s College London and director of TwinsUK a scientific study of 15,000 identical and non-identical twins, which has been running for nearly three decades.

The dataset schema includes:

Demographic Information (Year of Birth, Gender, Height, Weight, Postcode) Health Screening Questions (Activity, Heart Disease, Diabetes, Lung Disease, Smoking Status, Kidney Disease, Chemotherapy, Immunosuppressants, Corticosteroids, Blood Pressure Medications, Previous COVID, COVID Symptoms, Needs Help, Housebound Problems, Help Availability, Mobility Aid) COVID Testing Conducted How You Feel? Symptom Description Location Information (Home, Hospital, Back From Hospital) Treatment Received The data is hosted within the SAIL Databank, a trusted research environment facilitating remote access to health, social care, and administrative data for various national organisations.

The process for requesting access to the data is dependent on your use case. SAIL is currently expediting all requests that feed directly into the response to the COVID-19 national emergency, and therefore requests from NHS or Government institutions, or organisations working alongside such care providers and policymakers to feed intelligence directly back into the national response, are being expedited with a ~48-hour governance turnaround for such applications once made. Please make enquiries using the link at the bottom of the page which will go the SAIL Databank team, or to Chris Orton at c.orton@swansea.ac.uk

SAIL is welcoming requests from other organisations and for longer-term academic study on the dataset, but please note if this is not directly relevant to the emergency research being carried out which directly interfaces with national responding agencies, there may be an access delay whilst priority use cases are serviced.

Please note: the CVST dataset in SAIL has not been updated since 01/11/2023.

This dataset requires additional governance approvals from the data provider before data can be provisioned to a SAIL project.

REal-time Assessment of Community Transmission (REACT-2) started in May 2020 to determine the prevalence of and trends in antibodies levels in study participants. This study involves approximately 150,000 unique people who use a finger prick test over 6 week periods, with additional information collected on contact with known cases to assess an infection point prevalence at national, regional and local levels. Within REACT 2 there is also a study on usability and efficacy of different tests.

Imperial College London is leading a major programme of home testing for COVID-19 to track the progress of the infection across England. Called REACT, the programme was commissioned by the Department of Health and Social Care, and is being carried out in partnership with Imperial College Healthcare NHS Trust and Ipsos MORI.

REACT-2 is a world largest surveillance study undertaken in England that examines the prevalence of antibodies in the community. The study focusses on finger prick self-testing at home by individuals aged 18 or over.The findings will provide the government with a better understanding of the use of antibody tests at home as well as assess the trends in antibody levels and how they vary across different population subgroups. This will inform government policies to protect health and save lives.

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 https://www.covidsocialstudy.org/">UCL COVID-19 Social Study website.