Provisional counts of the number of care home resident deaths registered in England and Wales, by region, including deaths involving coronavirus (COVID-19), in the latest weeks for which data are available.

As of May 1 2020, there were over 23 thousand more deaths in care homes in England and Wales than there were on the same date in 2019, with 12.5 thousand of these caused by Coronavirus (COVID-19) and 10.6 thousand due to other causes.

Provisional counts of deaths in care homes caused by coronavirus (COVID-19) by local authority. Published by the Office for National Statistics and Care Quality Commission.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, 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.

In the week ending August 27, 2021, there were 10,268 deaths in England and Wales with just over 4.5 thousand taking place in Hospitals. Between April 10 and April 24 of 2020 there were over 15 thousand deaths occurring in care homes, due to the Coronavirus pandemic.

The study will be expanding to other providers and care homes across England and will provide a detailed picture of prevalence, seroprevalence, transmission and potential immunity over time.By testing around 6500 staff and 5000 residents across >100 care homes in England, we will estimate the proportion who have been infected with COVID-19 in the past and have antibodies, and the proportion who are infected now. These tests will be repeated over time to learn how COVID-19 spreads in care homes and how long the antibody response lasts and whether this helps to prevent re-infection with the virus. In those who are currently infected, we will also collect information on who is experiencing symptoms to help us to understand how this affects spread of infection within care homes. We will find out about how infection spreads between care homes, the community and hospitals by linking the information we collect to national data on hospital admissions and deaths.

N.B.: The data within the VIVALDI 2 dataset is being examined and cleaned to improve its quality, this is ongoing work.

Model estimates of deaths involving the coronavirus (COVID-19) by ethnic group for people in care homes in England.

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%. Number of deaths Proportion of deaths Week ending Hospital Care home Home Other Hospital Care home Home Other 06 Mar 2020 1 1 0 0 50% 50% 0% 0% 13 Mar 2020 13 0 4 0 76% 0% 24% 0% 20 Mar 2020 148 9 11 0 88% 5% 7% 0% 27 Mar 2020 610 45 53 14 84% 6% 7% 2% 03 Apr 2020 1,215 132 143 27 80% 9% 9% 2% 10 Apr 2020 1,495 282 162 32 76% 14% 8% 2% 17 Apr 2020 1,076 295 101 29 72% 20% 7% 2% 24 Apr 2020 669 210 72 35 68% 21% 7% 4% 01 May 2020 348 125 43 15 66% 24% 8% 3% 08 May 2020 261 93 29 16 65% 23% 7% 4% 15 May 2020 152 51 22 5 66% 22% 10% 2% 22 May 2020 93 51 10 3 59% 32% 6% 2% 29 May 2020 62 25 7 6 62% 25% 7% 6% 05 Jun 2020 53 23 4 1 65% 28% 5% 1% 12 Jun 2020 27 11 9 3 54% 22% 18% 6% 19 Jun 2020 22 7 6 2 59% 19% 16% 5% 26 Jun 2020 14 14 5 1 41% 41% 15% 3% 03 Jul 2020 10 5 2 5 45% 23% 9% 23% 10 Jul 2020 15 3 0 1 79% 16% 0% 5% 17 Jul 2020 8 7 2 0 47% 41% 12% 0% 24 Jul 2020 15 1 0 2 83% 6% 0% 11% 31 Jul 2020 6 2 1 0 67% 22% 11% 0% 07 Aug 2020 6 2 0 1 67% 22% 0% 11% 14 Aug 2020 7 4 2 1 50% 29% 14% 7% 21 Aug 2020 4 0 0 0 100% 0% 0% 0% 28 Aug 2020 1 2 0 0 33% 67% 0% 0% 04 Sep 2020 3 0 1 0 75% 0% 25% 0% 11 Sep 2020 7 2 0 1 70% 20% 0% 10% 18 Sep 2020 9 2 1 0 75% 17% 8% 0% 25 Sep 2020 23 3 3 0 79% 10% 10% 0% 02 Oct 2020 27 3 2 0 84% 9% 6% 0% 09 Oct 2020 36 3 3 0 86% 7% 7% 0% 16 Oct 2020 41 0 2 0 95% 0% 5% 0% 23 Oct 2020 47 4 4 0 85% 7% 7% 0% 30 Oct 2020 91 3 5 1 91% 3% 5% 1% 06 Nov 2020 93 7 5 2 87% 7% 5% 2% 13 Nov 2020 109 11 10 2 83% 8% 8% 2% 20 Nov 2020 162 5 8 4 91% 3% 4% 2% 27 Nov 2020 175 8 14 5 87% 4% 7% 2% 04 Dec 2020 190 10 13 10 85% 4% 6% 4% 11 Dec 2020 199 9 13 6 88% 4% 6% 3% 18 Dec 2020 267 15 25 4 86% 5% 8% 1% 25 Dec 2020 403 30 43 7 83% 6% 9% 1% 01 Jan 2021 677 35 109 28 80% 4% 13% 3% 08 Jan 2021 959 73 167 36 78% 6% 14% 3% 15 Jan 2021 1,125 84 165 39 80% 6% 12% 3% 22 Jan 2021 1,163 96 142 43 81% 7% 10% 3% 29 Jan 2021 863 82 101 28 80% 8% 9% 3% 05 Feb 2021 605 70 59 38 78% 9% 8% 5% 12 Feb 2021 439 29 49 14 83% 5% 9% 3% 19 Feb 2021 338 29 33 12 82% 7% 8% 3% 26 Feb 2021 214 19 19 11 81% 7% 7% 4% 05 Mar 2021 141 11 19 5 80% 6% 11% 3% 12 Mar 2021 99 9 7 1 85% 8% 6% 1% 19 Mar 2021 65 10 1 1 84% 13% 1% 1% 26 Mar 2021 41 9 4 2 73% 16% 7% 4% 02 Apr 2021 35 5 4 0 80% 11% 9% 0% 09 Apr 2021 29 2 3 0 85% 6% 9% 0% 16 Apr 2021 24 6 2 0 75% 19% 6% 0% 23 Apr 2021 14 1 0 0 93% 7% 0% 0% 30 Apr 2021 13 1 1 0 87% 7% 7% 0% 07 May 2021 14 3 0 0 82% 18% 0% 0% 14 May 2021 6 2 0 0 75% 25% 0% 0% 21 May 2021 8 1 1 0 80% 10% 10% 0% 28 May 2021 11 1 2 1 73% 7% 13% 7% 04 Jun 2021 9 0 0 0 100% 0% 0% 0% 11 Jun 2021 11 3 0 0 79% 21% 0% 0% 18 Jun 2021 11 4 2 1 61% 22% 11% 6% 25 Jun 2021 10 0 0 1 91% 0% 0% 9% 02 Jul 2021 14 1 2 0 82% 6% 12% 0% 09 Jul 2021 12 1 4 1 67% 6% 22% 6% 16 Jul 2021 18 3 2 0 78% 13% 9% 0% 23 Jul 2021 48 0 7 1 86% 0% 12% 2% 30 Jul 2021 49 2 4 4 83% 3% 7% 7% 06 Aug 2021 66 1 9 1 86% 1% 12% 1% 13 Aug 2021 60 1 12 1 81% 1% 16% 1% 20 Aug 2021 84 1 5 1 92% 1% 5% 1% 27 Aug 2021 78 3 10 3 83% 3% 11% 3% 03 Sep 2021 85 3 7 1 89% 3% 7% 1% 10 Sep 2021 83 2 10 2 86% 2% 10% 2% 17 Sep 2021 65 2 9 1 84% 3% 12% 1% 24 Sep 2021 76 5 5 0 88% 6% 6% 0% 01 Oct 2021 88 2 15 1 83% 2% 14% 1% 08 Oct 2021 65 2 7 1 87% 3% 9% 1% 15 Oct 2021 62 1 9 4 82% 1% 12% 5% 22 Oct 2021 64 2 11 2 81% 3% 14% 3% 29 Oct 2021 66 3 11 1 81% 4% 14% 1% 05 Nov 2021 67 3 10 5 79% 4% 12% 6% 12 Nov 2021 84 2 12 1 85% 2% 12% 1% 19 Nov 2021 63 2 2 0 94% 3% 3% 0% 26 Nov 2021 68 2 8 0 87% 3% 10% 0% 03 Dec 2021 72 2 10 1 85% 2% 12% 1% 10 Dec 2021 81 3 12 4 81% 3% 12% 4% 17 Dec 2021 91 1 12 3 85% 1% 11% 3% 24 Dec 2021 101 8 15 3 80% 6% 12% 2% 31 Dec 2021 129 11 19 6 78% 7% 12% 4% 07 Jan 2022 178 18 19 4 81% 8% 9% 2% 14 Jan 2022 194 23 16 14 79% 9% 6% 6% 21 Jan 2022 165 25 11 4 80% 12% 5% 2% 28 Jan 2022 119 20 13 5 76% 13% 8% 3% 04 Feb 2022 97 13 8 2 81% 11% 7% 2% 11 Feb 2022 51 10 6 6 70% 14% 8% 8% 18 Feb 2022 62 6 9 3 78% 8% 11% 4% 25 Feb 2022 55 2 2 1 92% 3% 3% 2% 04 Mar 2022 47 2 2 2 89% 4% 4% 4% 11 Mar 2022 48 3 4 0 87% 5% 7% 0% 18 Mar 2022 60 7 8 4 76% 9% 10% 5% 25 Mar 2022 51 11 5 2 74% 16% 7% 3% 01 Apr 2022 60 8 5 2 80% 11% 7% 3% 08 Apr 2022 78 4 7 3 85% 4% 8% 3% 15 Apr 2022 74 6 6 3 83% 7% 7% 3% 22 Apr 2022 58 10 7 6 72% 12% 9% 7% 29 Apr 2022 39 8 3 4 72% 15% 6% 7% 06 May 2022 44 3 4 0 86% 6% 8% 0% 13 May 2022 29 2 4 2 78% 5% 11% 5% 20 May 2022 16 4 0 2 73% 18% 0% 9% 27 May 2022 34 3 3 1 83% 7% 7% 2% 03 Jun 2022 18 1 1 0 90% 5% 5% 0% 10 Jun 2022 18 1 3 0 82% 5% 14% 0% 17 Jun 2022 22 1 2 0 88% 4% 8% 0% 24 Jun 2022 33 2 3 1 85% 5% 8% 3% 01 Jul 2022 33 2 2 0 89% 5% 5% 0% 08 Jul 2022 51 4 4 4 81% 6% 6% 6% 15 Jul 2022 60 5 4 2 85% 7% 6% 3% 22 Jul 2022 71 9 10 3 76% 10% 11% 3% 29 Jul 2022 48 7 9 0 75% 11% 14% 0% 05 Aug 2022 35 1 3 4 81% 2% 7% 9% Total 18,924 2,390 2,152 634 79% 10% 9% 3% Comparison with all cause mortality Comparison of data sources Note on data sources NHS England provides numbers of patients who have died in hospitals in England and had tested positive for COVID-19, and from 25 April, the number of patients where COVID-19 is mentioned on the death certificate and no positive COVID-19 test result was received. Figures are updated each day at 2pm with deaths reported up to 5pm the previous day. There is a delay between the occurrence of a death to it being captured in the

In 2021, there were 15,200 residential adult social care homes in England, these establishments provide care and support for older and disabled people. That year, there were 11,900 non-residential adult care homes in England. Over the provided time interval the number of residential care homes decreased, while the number of non-residential care homes has increased since 2009.

As a result of the Coronavirus (COVID-19), there were over 15 thousand deaths in care homes in England and Wales between April 10 and April 24, 2020.

Provisional counts of the number of deaths involving the coronavirus (COVID-19) within the care sector registered from 14 March 2020 to 21 January 2022.

Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. The COVID-19 pandemic has wider impacts on individuals' health, and their use of healthcare services, than those that occur as the direct result of infection. Reasons for this may include: * Individuals being reluctant to use health services because they do not want to burden the NHS or are anxious about the risk of infection. * The health service delaying preventative and non-urgent care such as some screening services and planned surgery. * Other indirect effects of interventions to control COVID-19, such as mental or physical consequences of distancing measures. This dataset provides information on trend data regarding the wider impact of the pandemic on the number of deaths in Scotland, derived from the National Records of Scotland (NRS) weekly deaths registration data. Data show recent trends in deaths (2020), whether COVID or non-COVID related, and historic trends for comparison (five-year average, 2015-2019). The recent trend data are shown by age group and sex, and the national data are also shown by broad area deprivation category (Scottish Index of Multiple Deprivation, SIMD). This data is also available on the COVID-19 Wider Impact Dashboard. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications.

Estimates of the risk of hospital admission for coronavirus (COVID-19) and death involving COVID-19 by vaccination status, overall and by age group, using anonymised linked data from Census 2021. Experimental Statistics.

Outcome definitions

For this analysis, we define a death as involving COVID-19 if either of the ICD-10 codes U07.1 (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified) is mentioned on the death certificate. Information on cause of death coding is available in the User Guide to Mortality Statistics. We use date of occurrance rather than date of registration to give the date of the death.

We define COVID-109 hospitalisation as an inpatient episode in Hospital Episode Statistics where the primary diagnosis was COVID-19, identified by the ICD-19 codes (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified). Where an individual had experienced more than one COVID-19 hospitalisation, the earliest that occurred within the study period was used. We define the date of COVID-19 hospitalisation as the start of the hospital episode.

ICD-10 code

U07.1 :

COVID-19, virus identified

U07.2:

COVID-19, virus not identified

Vaccination status is defined by the dose and the time since the last dose received

Unvaccinated:

no vaccination to less than 21 days post first dose

First dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post first dose or less than 21 days post second dose

First dose 3+ months:

more than or equal to 91 days post first dose to less than 21 days post second dose

Second dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post second dose or less than 21 days post third dose

Second dose 3-6 months:

more than or equal to 91 days post second dose to earliest of less than 182 days post second dose or less than 21 days post third dose

Second dose 6+ months:

more than or equal to 182 days post second dose to less than 21 days post third dose

Third dose 21 days to 3 months:

more than or equal to 21 days post third dose to less than 91 days post third dose

Third dose 3+ months:

more than or equal to 91 days post third dose

Model adjustments

Three sets of model adjustments were used

Age adjusted:

age (as a natural spline)

Age, socio-demographics adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status)

Fully adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status), plus health-related characteristics (disability, self-reported health, care home residency, number of QCovid comorbidities (grouped), BMI category, frailty flag and hospitalisation within the last 21 days.

Age

Age in years is defined on the Census day 2021 (21 March 2021). Age is included in the model as a natural spline with boundary knots at the 10th and 90th centiles and internal knots at the 25th, 50th and 75th centiles. The positions of the knots are calculated separately for the overall model and for each age group for the stratified model.

BackgroundThe COVID-19 pandemic has been a devastating and enduring mass-bereavement event, with uniquely difficult sets of circumstances experienced by people bereaved at this time. However, little is known about the long-term consequences of these experiences, including the prevalence of Prolonged Grief Disorder (PGD) and other conditions in pandemic-bereaved populations.MethodsA longitudinal survey of people bereaved in the UK between 16 March 2020 and 2 January 2021, with data collected at baseline (n = 711), c. 8 (n = 383), 13 (n = 295), and 25 (n = 185) months post-bereavement. Using measures of Prolonged Grief Disorder (PGD) (Traumatic Grief Inventory), grief vulnerability (Adult Attitude to Grief Scale), and social support (Inventory of Social Support), this analysis examines how participant characteristics, characteristics of the deceased and pandemic-related circumstances (e.g., restricted visiting, social isolation, social support) are associated with grief outcomes, with a focus on symptoms of PGD.ResultsAt baseline, 628 (88.6%) of participants were female, with a mean age of 49.5 (SD 12.9). 311 (43.8%) deaths were from confirmed/suspected COVID-19. Sample demographics were relatively stable across time points. 34.6% of participants met the cut-off for indicated PGD at c. 13 months bereaved and 28.6% at final follow-up. Social isolation and loneliness in early bereavement and lack of social support over time strongly contributed to higher levels of prolonged grief symptoms, while feeling well supported by healthcare professionals following the death was associated with reduced levels of prolonged grief symptoms. Characteristics of the deceased most strongly associated with lower levels of prolonged grief symptoms, were a more distant relationship (e.g., death of a grandparent), an expected death and death occurring in a care-home. Participant characteristics associated with higher levels of prolonged grief symptoms included low level of formal education and existence of medical conditions.ConclusionResults suggest higher than expected levels of PGD compared with pre-pandemic times, with important implications for bereavement policy, provision and practice now (e.g., strengthening of social and specialist support) and in preparedness for future pandemics and mass-bereavement events (e.g., guidance on infection control measures and rapid support responses).

This open data publication has moved to COVID-19 Statistical Data in Scotland (from 02/11/2022) Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. This dataset provides information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. There is a large amount of data being regularly published regarding COVID-19 (for example, Coronavirus in Scotland - Scottish Government and Deaths involving coronavirus in Scotland - National Records of Scotland. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications. Data visualisation is available to view in the interactive dashboard accompanying the COVID-19 Statistical Report. Please note information on COVID-19 in children and young people of educational age, education staff and educational settings is presented in a new COVID-19 Education Surveillance dataset going forward.

Occupational registration data was linked to anonymised electronic health records maintained by the Secure Anonymised Information Linkage (SAIL) Databank in a privacy-protecting trusted research environment. We examined records for all linked care workers from 1st March 2016 to 30th November 2021.

Domiciliary Care Workers (DCWs) are employed in both public and private sectors to support adults at home. The support they provide varies but often includes personal care, which demands close contact between care worker and the person being supported. Since the start of the COVID-19 pandemic, people working across the care sectors in England and Wales have experienced higher rates of death involving COVID-19 infection. Social care workers, in both residential and domiciliary care settings, have been particularly badly affected, with rates of death involving COVID-19 approximately double that for health care workers.

We do not fully understand the full impact on domiciliary care worker mortality, how COVID-19 has affected worker health more broadly, and the risk factors which contribute to these. Existing evidence on deaths from the ONS relies on occupational classification. However, for many individuals reported as dying with some COVID-19 involvement, information on occupation is missing (18% and 40% missing for males and females respectively). The impact of COVID-19 on the health of domiciliary care workers (DCWs) is therefore likely to be considerable, including on COVID-19 infection itself, mental health, and respiratory illnesses. We aim to generate rapid high-quality evidence based on the views of care workers and by linking care workers' registration data to routine health data. We can use this information to inform public health interventions for safer working practice and additional support for care workers.

Our study will use a combination of research methods. We will use existing administrative data involving carer professional registration records as well as health care records. Our analysis of these data will be guided in part by qualitative interviews that we will conduct with domiciliary care workers in Wales. The interviews will address the experiences of care workers during the course of the pandemic.

Registration data for care workers in Wales will be securely transferred from the regulatory body, Social Care Wales (SCW) to the Secured Anonymised Information Linkage (SAIL) Databank at Swansea University. These data will be combined with anonymised health records made available from the SAIL databank. Information which could be used to identify individual care workers will be removed in this process. We expect that this will create a research database of all domiciliary care workers in Wales, approximately 17,000 individuals. From this group we will also identify about 30 care workers to be approached via SCW to take part in a qualitative interview. The interview sample will be chosen so that it includes workers from a variety of backgrounds.

In our analysis, we will describe the socio-demographic characteristics of the group of care workers in the research database, for example, their average age. We will establish the number of care workers with both suspected and confirmed COVID-19 infection. Will explore how infection with COVID-19 has impacted on key health outcomes, including whether workers were admitted to hospital or died. We will also explore the health of care workers before and during COVID-19 pandemic. We will use the information gained from interviews with care workers to guide the way we analyse the health records of the care workers. Finally, we will examine how well the results from our analysis of care workers in Wales can be used inform what may be happening for workers in other countries in the UK.

To ensure that our findings will be of most use to those working in social care, we will work with an Implementation Reference Group. The group will include key stakeholders such as representatives from regulators from across the UK. Working with this group, we will provide rapid recommendations to drive public health initiatives for care worker safety. This may include changes in working practices and longer-term service planning to support care worker health needs.

There were 667,479 deaths in the United Kingdom in 2021, compared with 689,629 in 2020. Between 2003 and 2011, the annual number of deaths in the UK fell from 612,085 to just over 552,232. Since 2011 however, the annual number of annual deaths in the United Kingdom has steadily grown, with the number recorded in 2020, the highest since 1918 when there were 715,246 deaths. Both of these spikes in the number of deaths can be attributed to infectious disease pandemics. The great influenza pandemic of 1918, which was at its height towards the end of World War One, and the COVID-19 pandemic, which caused a large number of deaths in 2020.  Impact of the COVID-19 pandemic The weekly death figures for England and Wales highlight the tragic toll of the COVID-19 pandemic. In two weeks in April of 2020, there were 22,351 and 21,997 deaths respectively, almost 12,000 excess deaths in each of those weeks. Although hospitals were the most common location of these deaths, a significant number of these deaths also took place in care homes, with 7,911 deaths taking place in care homes for the week ending April 24, 2020, far higher than usual. By the summer of 2020, the number of deaths in England and Wales reached more usual levels, before a second wave of excess deaths hit the country in early 2021. Although subsequent waves of COVID-19 cases resulted in far fewer deaths, the number of excess deaths remained elevated throughout 2022. Long-term life expectancy trends As of 2022 the life expectancy for men in the United Kingdom was 78.57, and almost 82.57 for women, compared with life expectancies of 75 for men and 80 for women in 2002. In historical terms, this is a major improvement in relation to the mid 18th century, when the overall life expectancy was just under 39 years. Between 2011 and 2017, improvements in life expectancy in the UK did start to decline, and have gone into reverse since 2018/20. Between 2020 and 2022 for example, life expectancy for men in the UK has fallen by over 37 weeks, and by almost 23 weeks for women, when compared with the previous year.

Overall CFR as of 27/09/2021 in each region of England, using the backward method and PHE data.

This qualitative sub-study was embedded in the broader data linkage OSCAR study which aimed to assess the health impact of working during the COVID-19 pandemic upon domiciliary care workers (DCWs) in Wales, UK. The qualitative study aimed to explore care worker experiences during the pandemic. We explored factors that may have varied the risk of exposure to COVID-19 as well as adverse health and wellbeing outcomes. Registered DCWs working in Wales were invited to take part in a semi-structured telephone interview. In total, 24 DCWs were interviewed between February and July 2021. Emergent themes were identified through a process of inductive analysis using thematic coding. Several emergent themes related to risk of exposure to COVID-19. General changes to the role of the DCW during the course of the pandemic were identified. Practical challenges for DCWs in the workplace were also reported. These included reports of staff shortages, clients and families not following safety procedures, initial shortages of personal protective equipment (PPE), problems with standard use PPE, client difficulty with PPE and the management of rapid antigen testing. A general lack of government/employer preparation for a pandemic was described. This included the reorganisation of staff clients and services, sub-optimal information for many DCWs, COVID-19 training and the need for improved practical instruction and limited official standard risk assessments specifically for DCWs. Pressures to attend work and DCW’s perception of COVID-19 risk and vaccination were reported.

Domiciliary Care Workers (DCWs) are employed in both public and private sectors to support adults at home. The support they provide varies but often includes personal care, which demands close contact between care worker and the person being supported. Since the start of the COVID-19 pandemic, people working across the care sectors in England and Wales have experienced higher rates of death involving COVID-19 infection. Social care workers, in both residential and domiciliary care settings, have been particularly badly affected, with rates of death involving COVID-19 approximately double that for health care workers.

We do not fully understand the full impact on domiciliary care worker mortality, how COVID-19 has affected worker health more broadly, and the risk factors which contribute to these. Existing evidence on deaths from the ONS relies on occupational classification. However, for many individuals reported as dying with some COVID-19 involvement, information on occupation is missing (18% and 40% missing for males and females respectively). The impact of COVID-19 on the health of domiciliary care workers (DCWs) is therefore likely to be considerable, including on COVID-19 infection itself, mental health, and respiratory illnesses. We aim to generate rapid high-quality evidence based on the views of care workers and by linking care workers' registration data to routine health data. We can use this information to inform public health interventions for safer working practice and additional support for care workers.

Our study will use a combination of research methods. We will use existing administrative data involving carer professional registration records as well as health care records. Our analysis of these data will be guided in part by qualitative interviews that we will conduct with domiciliary care workers in Wales. The interviews will address the experiences of care workers during the course of the pandemic.

Registration data for care workers in Wales will be securely transferred from the regulatory body, Social Care Wales (SCW) to the Secured Anonymised Information Linkage (SAIL) Databank at Swansea University. These data will be combined with anonymised health records made available from the SAIL databank. Information which could be used to identify individual care workers will be removed in this process. We expect that this will create a research database of all domiciliary care workers in Wales, approximately 17,000 individuals. From this group we will also identify about 30 care workers to be approached via SCW to take part in a qualitative interview. The interview sample will be chosen so that it includes workers from a variety of backgrounds.

In our analysis, we will describe the socio-demographic characteristics of the group of care workers in the research database, for example, their average age. We will establish the number of care workers with both suspected and confirmed COVID-19 infection. Will explore how infection with COVID-19 has impacted on key health outcomes, including whether workers were admitted to hospital or died. We will also explore the health of care workers before and during COVID-19 pandemic. We will use the information gained from interviews with care workers to guide the way we analyse the health records of the care workers. Finally, we will examine how well the results from our analysis of care workers in...

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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.

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.