A survey carried out in the United Kingdom in September 2021 found that 52 percent of respondents did not take any action after encountering what they believed to be false or misleading information on the COVID-19 outbreak. Whilst this figure was lower than the share who said the same in the 2020 survey, taking no action remained the most common response to fake coronavirus news. Meanwhile, 16 percent used a fact checking site or tool to determine whether or not the information they found was true, and 14 percent turned to family or friends for help in confirming the legitimacy of news they suspected to be false.

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

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 20 times or more per day in the last week. This marked an increase of two percent from the share who said the same in the survey wave held in September 2020. Meanwhile, 24 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.

Some 33 percent of respondents in the United States were satisfied with their fellow citizens’ response to the coronavirus pandemic on May 31, 2020. Are people satisfied with the media’s response to the coronavirus? As of March to May 2020, all over the world, people were watching news coverage more than usual due to the coronavirus outbreak. A lot of respondents seem to want to keep in-line with the latest trends of a pandemic that has effectively crippled many of the world’s biggest economies. Consumers of several age groups between 16 and 64 are watching news with a greater frequency which also means a greater scrutiny for the media outlets. In the U.S., where millions of people have filed for unemployment benefits since the corona outbreak, more than one third of respondents were satisfied with media’s response to COVID-19 as of May 3rd, 2020. However, a considerable share of respondents in the U.S. believe that media has overstated news related to coronavirus outbreak in the U.S. That goes for audiences from both democrat and republican-supporting groups as they believe that the media outlets have either slightly or greatly exaggerated news about COVID-19.

A survey carried out in the United Kingdom in September 2021 revealed that the main source used for news on COVID-19 among consumers aged 16 to 24 years old was the BBC, with 51 percent saying that they went to a BBC platform for coronavirus updates in the last week. The same share of respondents in that age group also used social media for COVID-19 information, whereas older consumers were more likely to read newspapers.

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

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.

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

The results of a survey published by Brandwatch in March 2020 reveals where people in the United Kingdom (UK) are getting their information on the coronavirus (COVID-19) outbreak. News outlets are the most popular source of information with 69 percent, followed by social media. The fact that so many people are finding coronavirus information and advice on social media will be a concern for many, considering how easily fake news can travel. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

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

A survey carried out in the United Kingdom in September 2021 revealed that 36 percent of respondents between the ages of 16 and 24 had come across news or information about the coronavirus that they thought was false or misleading in the last week, compared to just 17 percent of those aged 65 or above. Younger consumers were also the least likely to say that they had not seen any fake news on COVID-19 or were unsure whether or not they had, whilst a higher share of older consumers admitted that they did not know if they had encounted misleading information about the pandemic in the week running to the survey.

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

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.

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

A survey carried out in the United Kingdom in September 2021 showed that the most trusted source of news about the COVID-19 pandemic was the NHS, with 91 percent of those aged 16 years or older saying that they trusted information directly from the National Health Service. By contrast, just 21 percent said the same about Facebook.

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

The Kroger company profile including COVID-19 impact report analyses the financials, key performance indicators, market shares, competitive landscape, additional metrics, news and initiatives of the retailer. Read More

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.

There is an urgent need to understand the factors that mediate and mitigate the impact of the Covid-19 pandemic on behaviour and wellbeing. However, the onset of the outbreak was unexpected and the rate of acceleration so rapid as to preclude the planning of studies that can address these critical issues. Coincidentally, in January 2020, just prior to the outbreak in the UK, my team launched a study that collected detailed (~50 minute) cognitive and questionnaire assessments from >200,000 members of the UK public as part of a collaboration with the BBC. This placed us in a unique position to examine how aspects of mental health subsequently changed as the pandemic arrived in the UK. Therefore, we collected data from a further ~120,000 people in May, including additional detailed measures of self-perceived pandemic impact and free text descriptions of the main positives, negatives and pragmatic measures that people found helped them maintain their wellbeing. In this data archive, we include the survey data from January and May 2020 examining impact of Covid-19 on mood, wellbeing and behaviour in the UK population. This data is reported in a preprint article, where we apply a novel fusion of psychometric, multivariate and machine learning analyses to this unique dataset, in order to address some of the most pressing questions regarding wellbeing during the pandemic in a data-driven manner. The preprint is available on this URL. https://www.medrxiv.org/content/10.1101/2020.06.18.20134635v1 Recruitment Starting from December 26th 2019, participants were recruited to the study website, where they completed cognitive tests and a detailed questionnaire. Articles describing the study were placed on the BBC2 Horizon, BBC Home page, BBC News Home page and circulated on mobile news meta-apps from January 1st 2020. To maximise representativeness of the sample there were no inclusion/exclusion criteria. Analyses here exclude data from participants under 16 years old, as they completed a briefer questionnaire, and those who responded to the questionnaire unfeasibly fast (<4 minutes). Cognitive test data will be reported separately. The study was approved by the Imperial College Research Ethics Committee (17IC4009). Data collection Data were collected via our custom server system, which produces study-specific websites (https://gbws.cognitron.co.uk) on the Amazon EC2. Questionnaires and tests were programmed in Javascript and HTML5. They were deliverable via personal computers, tablets and smartphones. The questionnaire included scales quantifying sociodemographic, lifestyle, online technology use, personality, and mental health (Supplement 1). Participants could enrol for longitudinal follow up, scheduled for 3, 6 and 12 months. People returning to the site outside of these timepoints were navigated to a different URL. On May 2nd 2020, the questionnaire was augmented - in light of the Covid-19 pandemic - with an extended mood scale, and an instrument comprising 47 items quantifying self-perceived effects on mood, behaviour and outlook (Pandemic General Impact Scale PD-GIS-11). Questions regarding pre-existing psychiatric and neurological conditions, lockdown context, having the virus, and free text fields were added. This coincided with further promotion via BBC2 Horizon and BBC Homepage.

Target Corporation profile including COVID-19 impact report analyses the financials, key performance indicators, market shares, competitive landscape, additional metrics, news and initiatives of the retailer. Read More