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

The COVID-19 Health Inequalities Monitoring in England (CHIME) tool brings together data relating to the direct impacts of coronavirus (COVID-19) on factors such as mortality rates, hospital admissions, confirmed cases and vaccinations.

By presenting inequality breakdowns - including by age, sex, ethnic group, level of deprivation and region - the tool provides a single point of access to:

• show how inequalities have changed during the course of the pandemic and what the current cumulative picture is
• bring together data in one tool to enable users to access and use the intelligence more easily
• provide indicators with a consistent methodology across different data sets to facilitate understanding
• support users to identify and address inequalities within their areas, and identify priority areas for recovery

In the March 2023 update, data has been updated for deaths, hospital admissions and vaccinations. Data on inequalities in vaccination uptake within upper tier local authorities has been added to the tool for the first time. This replaces data for lower tier local authorities, published in December 2022, allowing the reporting of a wider range of inequality breakdowns within these areas.

Please send any questions or comments to PHA-OHID@dhsc.gov.uk

In a survey carried out in the United Kingdom in September 2021, five percent of respondents said that they had encountered news or information about the coronavirus that they believed to be false or misleading ** times or more per day in the last week. This marked an increase of *** percent from the share who said the same in the survey wave held in September 2020. Meanwhile, ** percent of respondents believed they had seen fake news about COVID-19 a few times a week in September 2021.

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

The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

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

Project Overview This portion of the COVID DIARIES project provides full bibliographic information (including original and permanent links) to media items related to the COVID-19 vaccination program, published on the official websites of 20 major U.S. news outlets, including television networks, magazines, and newspapers. It spans the period from December 2020, when states began implementing Phase 1a of the vaccine allocation plan, through September 2021, when vaccines became widely available to all adults and were frequently mandated. News items were collected to preserve a contemporaneous record of how the vaccination effort was discussed across national media. The dataset enables researchers to analyze media communication strategies during a nationwide public health emergency, with the broader aim of informing more effective public health messaging through mass media. This project represents a collaborative effort between the Yale School of Medicine and the Tobin Center for Economic Policy. Data and Data Collection Overview This collection comprises 5,383 unique publication links from 20 major news outlets—including television networks, magazines, and newspapers—published between December 1, 2020, and September 30, 2021. Only articles that were freely accessible online without subscription or paywall restrictions were included. Articles were collected by the research team (specifically AM) between August 2021 and November 2023 and in April 2024 (by AM and AG). These 20 news outlets were selected based on a 2020–2021 survey of 511 U.S. adults, which identified the outlets most commonly used to obtain information about the COVID-19 vaccination program. A full list of news outlets, along with their reported usage and perceived trustworthiness, is provided in Sources_Selection.docx. Online publications were identified using Google search with a custom date range in week-long increments (e.g., 12/01/2020–12/07/2020), using the keyword “vaccine” in combination with the link to the respective news outlet’s website. Search results were manually reviewed by AM according to the following inclusion and exclusion criteria. Inclusion criteria: Articles published on the selected U.S. news outlets websites ending in “.com” or “.co” that relate to the COVID-19 vaccination program; Articles from the selected international news outlets that serve both their country of origin and the U.S. audience (e.g., BBC, The Daily Mail). Exclusion criteria: Articles published on the international news outlets websites that exclusively serve their country of origin (e.g., domains ending in .uk, .ca, etc. without .com, .co); Publications from universities, government agencies, or other organizations not affiliated with major U.S. news outlets (e.g., domains ending in .edu, .gov, .org); Videos without accompanying transcripts; Publications without textual content; Articles referencing vaccines unrelated to COVID-19; Non-English language publications. Selection and Organization of Shared Data The full list of publications is provided in the data file named "News_Outlets_Publications_Full_List." Entries are organized by news outlet (one per tab), then by publication year, month, week, and article title within each tab. For each entry, the list includes the article’s original download date by the research team, file format (e.g., PDF), original link to the publication, and a permanent link record. The list was verified by MC, CA, AV, AG, and AM, with final quality control performed by AM. Each article was assigned a unique identifier in the format: "Article Title – News Outlet Name", ensuring that each entry appears only once in the final dataset. Additional documentation includes this Data Narrative, a document explaining the source selection and an administrative README file.

Context

The 2019–20 coronavirus pandemic is an ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Source: https://en.wikipedia.org/wiki/2019%E2%80%9320_coronavirus_pandemic.

Content

A dataset encompassing all 119,083 mentions of "coronavirus", "covid" and "virus" on a set of major television news stations from January 1, 2020 through the morning of March 10, 2020 using data from the Internet Archive's Television News Archive. Each mention includes the URL of the matching 15 second clip on the Archive's website, the time and date of the match in UTC, the station and show it appeared on, its unique Internet Archive identifier and a preview thumbnail image of the one-minute period containing the clip and the 15 second clip of the spoken word transcript containing the mention, allowing you to understand the context of the mention and the surrounding language.

Acknowledgements

Data from the GDELT project (https://www.gdeltproject.org/) was released under an open license.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1314380%2F6298d5dbc10b64e0d9d63ecd06fb14f8%2FScreen%20Shot%202020-03-13%20at%209.39.22%20AM.png?generation=1584113977874451&alt=media" alt="">

Banner Photo by Fred Kearney on Unsplash

Due to the unprecedented circumstances we are facing during the Coronavirus (COVID-19) pandemic, it may not be possible for us to meet the timescales stipulated with regard to Council Spend Data published monthly. Thank you for your understanding and patience during this difficult and unprecedented period. You can find advice and guidance about accessing information from public bodies from the Information Commissioner’s Office (ICO) at www.ico.org.uk/your-data-matters/official-information Please also see the following information from the ICO at www.ico.org.uk/about-the-ico/news-and-events/news-and-blogs/2020/03/coronavirus-and-personal-data/ Details of Council spending from April 2016 onward. Please click 'Download' to view this data in a spreadsheet. This will enable you to filter the information more easily, for example by month. This dataset is updated monthly.

In recent years behavioural science has quickly become embedded in national level governance. As the contributions of behavioural science to the UK's COVID-19 response policies in early 2020 became apparent, a debate emerged in the British media about its involvement. This served as a unique opportunity to capture public discourse and representation of behavioural science in a fast-track, high-stake context. We aimed at identifying elements which foster and detract from trust and credibility in emergent scientific contributions to policy making. With this in mind, in Study 1 we use corpus linguistics and network analysis to map the narrative around the key behavioural science actors and concepts which were discussed in the 647 news articles extracted from the 15 most read British newspapers over the 12-week period surrounding the first hard UK lockdown of 2020. We report and discuss (1) the salience of key concepts and actors as the debate unfolded, (2) quantified changes in the polarity of the sentiment expressed toward them and their policy application contexts, and (3) patterns of co-occurrence via network analyses. To establish public discourse surrounding identified themes, in Study 2 we investigate how salience and sentiment of key themes and relations to policy were discussed in original Twitter chatter (N = 2,187). In Study 3, we complement these findings with a qualitative analysis of the subset of news articles which contained the most extreme sentiments (N = 111), providing an in-depth perspective of sentiments and discourse developed around keywords, as either promoting or undermining their credibility in, and trust toward behaviourally informed policy. We discuss our findings in light of the integration of behavioural science in national policy making under emergency constraints.

BackgroundThe COVID-19 pandemic propelled immunology into global news and social media, resulting in the potential for misinterpreting and misusing complex scientific concepts.ObjectiveTo study the extent to which immunology is discussed in news articles and YouTube videos in English and Italian, and if related scientific concepts are used to support specific political or ideological narratives in the context of COVID-19.MethodsIn English and Italian we searched the period 11/09/2019 to 11/09/2022 on YouTube, using the software Mozdeh, for videos mentioning COVID-19 and one of nine immunological concepts: antibody-dependent enhancement, anergy, cytokine storm, herd immunity, hygiene hypothesis, immunity debt, original antigenic sin, oxidative stress and viral interference. We repeated this using MediaCloud for news articles.Four samples of 200 articles/videos were obtained from the randomised data gathered and analysed for mentions of concepts, stance on vaccines, masks, lockdown, social distancing, and political signifiers.ResultsVaccine-negative information was higher in videos than news (8-fold in English, 6-fold in Italian) and higher in Italian than English (4-fold in news, 3-fold in videos). We also observed the existence of information bubbles, where a negative stance towards one intervention was associated with a negative stance to other linked ideas. Some immunological concepts (immunity debt, viral interference, anergy and original antigenic sin) were associated with anti-vaccine or anti-NPI (non-pharmacological intervention) views. Videos in English mentioned politics more frequently than those in Italian and, in all media and languages, politics was more frequently mentioned in anti-guidelines and anti-vaccine media by a factor of 3 in video and of 3–5 in news.ConclusionThere is evidence that some immunological concepts are used to provide credibility to specific narratives and ideological views. The existence of information bubbles supports the concept of the “rabbit hole” effect, where interest in unconventional views/media leads to ever more extreme algorithmic recommendations.

Coronavirus (COVID-19) has led to increased demand on general practices, including an increasing number of requests to provide patient data to inform planning and support vital research on the cause, effects, treatments and outcomes for patients of the virus. To support the response to the coronavirus outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients, including from their GP record, for the duration of the coronavirus emergency period, under the COVID-19 Public Health Directions 2020 (COVID-19 Direction). All GP practices in England are legally required to share data with NHS Digital for this purpose under the Health and Social Care Act 2012. More information about this requirement is contained in the Data Provision Notice issued by NHS Digital to GP practices.

This collection will reduce burden on general practices, allowing them to focus on patient care and support the coronavirus response.

Timescales for dissemination of agreed data can be found under 'Our Service Levels' at the following link: https://digital.nhs.uk/services/data-access-request-service-dars/data-access-request-service-dars-process

The project’s main aim is to explore the discursive functions of similes used to communicate the fist waves of Covid-19 pandemic in digital newspapers in 2020. The dataset includes 200 news items (100 English and 100 Spanish) containing both the string ‘TARGET is like SOURCE’ where virus or coronavirus is either the target, that is, the concept that is described (‘(CORONA)VIRUS is like X’), or the source, i.e. the concept that lends its properties for another, usually more abstract, one (‘X is like A VIRUS’).

Objectives: To investigate changes in beliefs and behaviours following news of the Omicron variant and changes to guidance understanding of Omicron-related guidance, and factors associated with engaging with protective behaviours.Design: Series of cross-sectional surveys (1 November to 16 December 2021, five waves of data collection).Setting: Online.Participants: People living in England, aged 16 years or over (n=1622–1902 per wave).Primary and secondary outcome measures: Levels of worry and perceived risk, and engagement with key behaviours (out-of-home activities, risky social mixing, wearing a face covering and testing uptake).Results: Degree of worry and perceived risk of COVID-19 (to oneself and people in the UK) fluctuated over time, increasing slightly around the time of the announcement about Omicron (p

Sex workers face unique challenges and needs in the context of COVID-19, which have attracted considerable attention from journalists writing for mainstream news publications. This database has archived 80 English-language articles published by mainstream publications during February through May 2020. Any ownership of these files is maintained by the copyright holder.

As of November 24, 2024 there were over 274 million confirmed cases of coronavirus (COVID-19) across the whole of Europe since the first confirmed cases in France in January 2020. France has been the worst affected country in Europe with 39,028,437 confirmed cases, followed by Germany with 38,437,756 cases. Italy and the UK have approximately 26.8 million and 25 million cases respectively. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

As of January 18, 2023, Portugal had the highest COVID-19 vaccination rate in Europe having administered 272.78 doses per 100 people in the country, while Malta had administered 258.49 doses per 100. The UK was the first country in Europe to approve the Pfizer/BioNTech vaccine for widespread use and began inoculations on December 8, 2020, and so far have administered 224.04 doses per 100. At the latest data, Belgium had carried out 253.89 doses of vaccines per 100 population. Russia became the first country in the world to authorize a vaccine - named Sputnik V - for use in the fight against COVID-19 in August 2020. As of August 4, 2022, Russia had administered 127.3 doses per 100 people in the country.

The seven-day rate of cases across Europe shows an ongoing perspective of which countries are worst affected by the virus relative to their population. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

Multinomial logistic regression comparing those who did versus those who did not intend to vaccinate (N = 351).