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

Provisional counts of the number of total deaths and deaths not involving the coronavirus (COVID-19), between 28 December 2019 and 10 July 2020. This includes deaths disaggregated by age and sex; by region of England, and Wales, and place of death; and for underlying causes of death and deaths involving leading causes.

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

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

COVID-19Plots and analysis relating to the coronavirus pandemic. Includes five sets of plots and associated R code to generate them.1) HeatmapsUpdated every few days - heatmaps of COVID-19 case and death trajectories for Local Authorities (or equivalent) in England, Wales, Scotland, Ireland and Germany.2) All cause mortalityUpdated on Tuesday (for England & Wales), Wednesday (for Scotland) and Friday (for Northern Ireland) - analysis and plots of weekly all-cause deaths in 2020 compared to previous years by country, age, sex and region. Also a set of international comparisons using data from mortality.org3) ExposuresNo longer updated - mapping of potential COVID-19 mortality exposure at local levels (LSOAs) in England based on the age-sex structure of the population and levels of poor health.There is also a Shiny app which creates slightly lower resolution versions of the same plots online, which you can find here: https://victimofmaths.shinyapps.io/covidmapper/, on GitHub https://github.com/VictimOfMaths/COVIDmapper and uploaded to this record4) Index of Multiple Deprivation No longer updated - preliminary analysis of the inequality impacts of COVID-19 based on Local Authority level cases and levels of deprivation. 5) Socioeconomic inequalities. No longer updated (unless ONS release more data) - Analysis of published ONS figures of COVID-19 and other cause mortality in 2020 compared to previous years by deprivation decile.Latest versions of plots and associated analysis can be found on Twitter: https://twitter.com/victimofmathsThis work is described in more detail on the UK Data Service Impact and Innovation Lab blog: https://blog.ukdataservice.ac.uk/visualising-high-risk-areas-for-covid-19-mortality/Adapted from data from the Office for National Statistics licensed under the Open Government Licence v.1.0.http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

NHS UK - COVID-19 Daily Deaths

This section contains information on deaths of patients who have died in hospitals in England and had tested positive for COVID-19 at time of death. All deaths are recorded against the date of death rather than the date the deaths were announced. Interpretation of the figures should take into account the fact that totals by date of death, particularly for most recent days, are likely to be updated in future releases. For example as deaths are confirmed as testing positive for COVID-19, as more post-mortem tests are processed and data from them are validated. Any changes are made clear in the daily files.

These figures do not include deaths outside hospital, such as those in care homes. This approach makes it possible to compile deaths data on a daily basis using up to date figures.

Dataset Content

These figures will be updated at 2pm each day and include confirmed cases reported at 5pm the previous day. 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 original dataset is sourced directly from the NHS source site, this original dataset is then cleaned and converted to a csv format available for inclusion into a Kaggle notebook.

There are 3 files considered within the data :- 1. Fatalities_by_age_uk 2.Fatalities_by_region_uk 3.Fatalities_by_trust_uk

Data runs from March 1st up to the current day. Any discrepancies will be outlined. The first is cumulative for any previous days leading up to of relevance. The following days are not cumulative and represent the updated value for the date under consideration.

A start kernel is provided to demonstrate using the dataset.

Citations

This dataset is sourced from the NHS statistical work areas:- https://www.england.nhs.uk/statistics/statistical-work-areas/

This dataset has been sourced and provided to aid in the following competition:- https://www.kaggle.com/c/covid19-global-forecasting-week-4

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

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

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

The percentage of extra deaths that occurred due to winter, including those that had COVID-19 mentioned on the death certificate. The Excess Winter Mortality (EWM) index is calculated as the number of excess winter deaths divided by the average non-winter deaths, expressed as a percentage. Calculated so that comparisons can be made between sexes, age groups, and regions.

An EWM index of 20 shows that there were 20 percent more deaths in winter compared with the non-winter period. Provisional figures at country and region level are produced for the most recent winter using estimation methods, and so are rounded to the nearest 100 deaths. Data post 2019/20 should be treated with caution due to high numbers of deaths from COVID-19 in the summer period.

For data years 2020/21 onwards, instances where the number of winter deaths compared to non-winter deaths were equal to zero or a negative value, an EWM index is presented. (For earlier years, the EWM index was removed). A zero value for winter deaths compared to non-winter deaths is often affected by rounding, so in these instances, the winter mortality index can either be a positive or negative value. A negative winter mortality index means there were a higher number of deaths in the non-winter periods than the winter period.

Alternatively, figures are available for deaths excluding COVID-19, calculated using all-cause deaths that did not have COVID-19 mentioned on the death certificate.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Background

This Sqlite database contains data publicly available from GOV.UK and can be found here: https://coronavirus.data.gov.uk/. The data is available via a REST API and come data is available in CSV format. However, it can be difficult to pull all this data together, so this Sqlite database contains a number of tables which includes all the data imported via the API.

How was this data generated?

For more information on how to generate this database, and extract and load the data using the REST API, you can use the additional Jupyter Notebooks which can be found in the following Git Repo: https://github.com/happyadam73/c19-notebooks

Currently this data runs up to 25 February 2022.

NOTE: As of 31st January 2022, publish date based cases include all episodes but historic data has not been updated. It is recommended for historical analysis to use specimen date cases. For more details, see: https://coronavirus.data.gov.uk/details/whats-new/record/beb802ac-1ed2-47ac-b314-69a5c3f712b5

Data Dictionary

The following provides a list of all 9 tables and the columns that can be found in each table.

11th January 2020 Change to vaccination data made available by UK gov - now just cumulative number of vaccines delivered are available for both first and second doses. For the devolved nations the cumulative totals are available for the dates from when given, however for the UK as a whole the total doses given is just on the last date of the index, regardless of when those vaccines were given.

4th January 2020 VACCINATION DATA ADDED - New and Cumulative First Dose Vaccination Data added to UK_National_Total_COVID_Dataset.csv and UK_Devolved_Nations_COVID_Dataset.csv

2nd December 2020:

NEW population, land area and population density data added in file NEW_Official_Population_Data_ONS_mid-2019.csv. This data is scraped from the Office for National Statistics and covers the UK, devolved UK nations, regions and local authorities (boroughs).

20th November 2020:

With European governments struggling with a 'second-wave' of rising cases, hospitalisations and deaths resulting from the SARS-CoV-2 virus (COVID-19), I wanted to make a comparative analysis between the data coming out of major European nations since the start of the pandemic.

I started by creating a Sweden COVID-19 dataset and now I'm looking at my own country, the United Kingdom.

The data comes from https://coronavirus.data.gov.uk/ and I used the Developer's Guide to scrape the data, so it was a fairly simple process. The notebook that scapes the data is public and can be found here. Further information about data collection methodologies and definitions can be found here.

The data includes the overall numbers for the UK as a whole, the numbers for each of the devolved UK nations (Eng, Sco, Wal & NI), English Regions and Upper Tier Local Authorities (UTLA) for all of the UK (what we call Boroughs). I have also included a small table with the populations of the 4 devolved UK nations, used to calculate the death rates per 100,000 population.

As I've said for before - I am not an Epidemiologist, Sociologist or even a Data Scientist. I am actually a Mechanical Engineer! The objective here is to improve my data science skills and maybe provide some useful data to the wider community.

Any questions, comments or suggestions are most welcome! I am open to requests and collaborations! Stay Safe!

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

The winter mortality index (WMI) is a measure expressed as a ratio of the difference in all cause mortality during winter months (December to March) compared to the average in the non winter months (the preceding August to November and following April to July).The terminology used to describe this indicator has changed to provide clearer explanation of what the analysis represents. The measures have been renamed to winter deaths compared to non winter deaths (previously excess winter deaths) and winter mortality index (WMI) (previously excess winter mortality index). There have been no methodology changes.

RationaleThe purpose of the winter mortality measure is to compare the number of deaths that occurred in the winter period (December to March) with the average of the non winter periods (August to November and April to July). Winter mortality is not solely a reflection of temperature, but of other factors as well. These include respiratory diseases and pressure on services, which have been more intense than usual during and following the height of the pandemic (1).It is an important measure as it allows users to assess whether policies are having an impact on mortality risks during the winter period (2). (1) Office for National Statistics (ONS), released 19 January 2023, ONS website, statistical bulletin, Winter mortality in England and Wales: 2021 to 2022 (provisional) and 2020 to 2021 (final). (2) Office for National Statistics (ONS), released 19 January 2023, ONS website, QMI, Winter mortality in England and Wales QMI: 19 January 2023Definition of numeratorTotal number of winter deaths for all ages in defined year 20xx/20xx+1 (number of deaths occurring in December in year 20xx and January to March in 20xx plus 1) minus half the number of deaths in the non winter months (preceding August to November in year 20xx and following April to July in year 20xx plus 1) and registered by 31 December 20xx plus 1.Definition of denominatorThe average number of deaths for all ages ( in defined year 20xx/20xx plus 1) occurring in the non winter months, i.e. the total number of deaths occurring in the preceding August to November in year 20xx and the following April to July in year 20xx plus 1 divided by two and registered by 31 December 20xx plus 1.CaveatsIn 2020, the coronavirus (COVID 19) pandemic led to a large increase of deaths mostly in the non-winter months of April to July 2020. This has impacted the WMI for 2019 to 2020. Because we rely on using the difference between deaths occurring in the winter and the average of non winter months; specifically, the scale of COVID 19 deaths during non winter months has fundamentally disturbed the data time series and so data for 2019 to 2020 should be interpreted with caution.The Office for National Statistics (ONS) Annual Births and Mortality Extract is based on registered deaths (Date of registration) and the Winter deaths compared to non winter deaths and WMI calculations are based on the date of death occurrences (Date of death). It is possible that a number of deaths might not have been registered when the data were released and this could vary between areas. This indicator only includes deaths which are registered by the end of the calendar year 20xx plus 1.Data published in the PHOF will differ from published ONS results which uses an extract of mortality data taken approximately five months after the annual ONS mortality extract is taken, in order to give more time for late registrations (for example, deaths that were referred to a coroner) to appear in the data.The WMI will be partly dependent on the proportion of older people in the population as most winter deaths effect older people (there is no standardisation in this calculation by age or any other factor).This winter period was selected as they are the months which over the last 50 years have displayed above average monthly mortality. However, if mortality starts to increase prior to this, for example in November, the number of deaths in the non winter period will increase, which in turn will decrease the estimate of winter deaths compared to non winter deaths.The counts are presented rounded to the nearest 10, in line with how data is presented by the ONS.

Title: Dataset for "Non-linear Relationships between COVID-19 and Non-COVID-19 Mortality by Vaccination Status within Age Groups" Author: Ir. A.J. Oostenbrink, Independent Researcher (ORCID: 0009-0003-3495-9519) Description: This dataset supports the study analyzing non-linear relationships between COVID-19 and non-COVID-19 mortality by vaccination status across age groups, using UK Office for National Statistics (ONS) data from January 2021 to May 2023. It includes age-standardized mortality rates for five vaccination statuses (unvaccinated, one dose, two doses, three doses, four or more doses) across six age groups (18–39, 40–49, 50–59, 60–69, 70–79, 80–89, 90+ years). The dataset covers monthly data on COVID-19 mortality, non-COVID-19 mortality, and all-cause mortality, enabling the examination of selection bias and concentration effects. Key variables include relative risks (RRcov, RRnoncov), vaccine effectiveness (VE) curves, and concentration factors, modeled using a power function (RRcov ∝ (RRnoncov)a). Data were sourced from ONS publications (2022, 2023) and processed in Microsoft Excel. The dataset includes appendices with person-years, mortality rates, and VE visualizations, supporting non-linear modeling and bias correction analyses. Raw data are available upon request, adhering to UK data protection regulations.Keywords: COVID-19, vaccine effectiveness, mortality rates, selection bias, non-linear modeling, ONS dataLicense: [CC BY 4.0]Files: Aggregated mortality data (Excel), Appendices I–VI (visualizations and tables)

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.

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

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.

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 was a fall in the overall number of spells for England from March 2020 due to COVID-19 impacting on activity for England and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for Chelsea and Westminster Hospital NHS Foundation Trust (trust code RQM). Values for this trust are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. Barts Health NHS Trust (trust code R1H), Cambridge University Hospitals NHS Foundation Trust (trust code RGT), Croydon Health Services NHS Trust (trust code RJ6), East and North Hertfordshire NHS Trust (trust code RWH), Epsom and St Helier University Hospitals NHS Trust (trust code RVR), Frimley Health NHS Foundation Trust (trust code RDU), Imperial College Healthcare NHS Trust (trust code RYJ), Manchester University NHS Foundation Trust (trust code R0A), Norfolk and Norwich University Hospitals NHS Foundation Trust (trust code RM1), Sandwell and West Birmingham Hospitals NHS Trust (trust code RXK), and University Hospitals of Derby and Burton NHS Foundation Trust (trust code RTG) are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information is available in the Background Quality Report. 6. On 1 July 2023 Southport and Ormskirk Hospital NHS Trust (trust code RVY) was acquired by St Helens and Knowsley Teaching Hospitals NHS Trust (trust code RBN). The new organisation is known as Mersey and West Lancashire Teaching Hospitals NHS Trust (trust code RBN). This new organisation structure is reflected from this publication onwards. 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.

Background and aimWith the Coronavirus Disease 2019 (COVID-19) pandemic continuing to impact healthcare systems around the world, healthcare providers are attempting to balance resources devoted to COVID-19 patients while minimizing excess mortality overall (both COVID-19 and non-COVID-19 patients). To this end, we conducted a systematic review (SR) to describe the effect of the COVID-19 pandemic on all-cause excess mortality (COVID-19 and non-COVID-19) during the pandemic timeframe compared to non-pandemic times.MethodsWe searched EMBASE, Cochrane Database of SRs, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Cochrane Controlled Trials Register (CENTRAL), from inception (1948) to December 31, 2020. We used a two-stage review process to screen/extract data. We assessed risk of bias using Newcastle-Ottawa Scale (NOS). We used Critical Appraisal and Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology.ResultsOf 11,581 citations, 194 studies met eligibility. Of these studies, 31 had mortality comparisons (n = 433,196,345 participants). Compared to pre-pandemic times, during the COVID-19 pandemic, our meta-analysis demonstrated that COVID-19 mortality had an increased risk difference (RD) of 0.06% (95% CI: 0.06–0.06% p < 0.00001). All-cause mortality also increased [relative risk (RR): 1.53, 95% confidence interval (CI): 1.38–1.70, p < 0.00001] alongside non-COVID-19 mortality (RR: 1.18, 1.07–1.30, p < 0.00001). There was “very low” certainty of evidence through GRADE assessment for all outcomes studied, demonstrating the evidence as uncertain.InterpretationThe COVID-19 pandemic may have caused significant increases in all-cause excess mortality, greater than those accounted for by increases due to COVID-19 mortality alone, although the evidence is uncertain.Systematic review registration[https://www.crd.york.ac.uk/prospero/#recordDetails], identifier [CRD42020201256].

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