As of April 2020, the coronavirus (COVID-19) outbreak has affected, in some way, the living arrangements of around a third of healthcare professionals in the United Kingdom (UK). 12 percent of healthcare professionals still live in their home, but avoid contact with other members of their household, while three percent have had another member of the household live away from home due to coronavirus.

The latest number of cases in the UK can be found here. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

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.

The Coronavirus (COVID-19) Press Briefings Corpus is a work in progress to collect and present in a machine readable text dataset of the daily briefings from around the world by government authorities. During the peak of the pandemic, most countries around the world informed their citizens of the status of the pandemic (usually involving an update on the number of infection cases, number of deaths) and other policy-oriented decisions about dealing with the health crisis, such as advice about what to do to reduce the spread of the epidemic.

Usually daily briefings did not occur on a Sunday.

At the moment the dataset includes:

UK/England: Daily Press Briefings by UK Government between 12 March 2020 - 01 June 2020 (70 briefings in total)

Scotland: Daily Press Briefings by Scottish Government between 3 March 2020 - 01 June 2020 (76 briefings in total)

Wales: Daily Press Briefings by Welsh Government between 23 March 2020 - 01 June 2020 (56 briefings in total)

Northern Ireland: Daily Press Briefings by N. Ireland Assembly between 23 March 2020 - 01 June 2020 (56 briefings in total)

World Health Organisation: Press Briefings occuring usually every 2 days between 22 January 2020 - 01 June 2020 (63 briefings in total)

More countries will be added in due course, and we will be keeping this updated to cover the latest daily briefings available.

The corpus is compiled to allow for further automated political discourse analysis (classification).

As of May 2020, nearly 65 percent of survey respondents in Great Britain reported their freedom and independence had been affected by the coronavirus pandemic and subsequent lockdown. A further 58 percent said their personal travel plans had been affected due to the crisis, and 54 percent said it had also meant they were unable to make future plans. The latest number of cases in the UK can be found here. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

Context

I would love to see notebooks! Keep bringin' em.

Content

Worldometer manually analyzes, validates, and aggregates data from thousands of sources in real time and provides global COVID-19 live statistics for a wide audience of caring people around the world.

Our data is also trusted and used by the UK Government, Johns Hopkins CSSE, the Government of Thailand, the Government of Vietnam, the Government of Pakistan, Financial Times, The New York Times, Business Insider, BBC, and many others.

Acknowledgements

Acknowledge Sujay S

Inspiration

Thanks to blogs out there on medium! That made me do this!

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.

Young Lives research has expanded to explore linking geographical data collected during the rounds to external datasets. Matching Young Lives data with administrative and geographic datasets significantly increases the scope for research in several areas, and may allow researchers to identify sources of exogenous variation for more convincing causal analysis on policy and/or early life circumstances.

Young Lives: Data Matching Series, 1900-2021 includes the following linked datasets:

1. Climate Matched Datasets (four YL study countries): Community-level GPS data has been matched with temperature and precipitation data from the University of Delaware. Climate variables are offered at the community level, with a panel data structure spanning across years and months. Hence, each community has a unique value of precipitation (variable PRCP) and temperature (variable TEMP), for each year and month pairing for the period 1900-2017.

2. COVID-19 Matched Dataset (Peru only): The YL Phone Survey Calls data has been matched with external data sources (The Peruvian Ministry of Health and the National Information System of Deaths in Peru). The matched dataset includes the total number of COVID cases per 1,000 inhabitants, the total number of COVID deaths by district and per 1,000 inhabitants; the total number of excess deaths per 1,000 inhabitants and the number of lockdown days in each Young Lives district in Peru during August 2020 to December 2021.

Further information is available in the PDF reports included in the study documentation.

In response to the outbreak of COVID-19, mandatory and voluntary self-isolation measures have been implemented by consumers around the world. Almost every aspect of consumers’ lives has been impacted as a result, including what they purchase, how and where they go shopping, and what they prepare and consume at mealtimes. Read More

In April 2020, a survey of healthcare workers in the United Kingdom (UK) found that majority are worried about their personal health as well as the health of those they live with during the coronavirus (COVID-19) outbreak. 28 percent of healthcare workers reported to be very worried about their personal health, while 37 percent were very worried about the health of those in their household.

The latest number of cases in the UK can be found here. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

The Centre for Longitudinal Studies (CLS) and the MRC Unit for Lifelong Health and Ageing (LHA) have carried out two online surveys of the participants of five national longitudinal cohort studies which have collected insights into the lives of study participants including their physical and mental health and wellbeing, family and relationships, education, work, and finances during the coronavirus pandemic. The Wave 1 Survey was carried out at the height of lockdown restrictions in May 2020 and focussed mainly on how participants’ lives had changed from just before the outbreak of the pandemic in March 2020 until then. The Wave 2 survey was conducted in September/October 2020 and focussed on the period between the easing of restrictions in June through the summer into the autumn. A third wave of the survey was conducted in early 2021.

In addition, CLS study members who had participated in any of the three COVID-19 Surveys were invited to provide a finger-prick blood sample to be analysed for COVID-19 antibodies. Those who agreed were sent a blood sample collection kit and were asked to post back the sample to a laboratory for analysis. The antibody test results and initial short survey responses are included in a single dataset, the COVID-19 Antibody Testing in the National Child Development Study, 1970 British Cohort Study, Next Steps and Millennium Cohort Study, 2021 (SN 8823).

The CLS studies are:

• Millennium Cohort Study (born 2000-02) both cohort members and parents (MCS)
• Next Steps (born 1989-90) (NS)
• 1970 British Cohort Study (BCS70)
• 1958 National Child Development Study (NCDS).

The LHA study is:

• MRC National Survey of Health and Development, 1946 British birth cohort (NSHD)

The content of the MCS, NS, BCS70 and NCDS COVID-19 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The COVID-19 Survey in Five National Longitudinal Cohort Studies: Millennium Cohort Study, Next Steps, 1970 British Cohort Study and 1958 National Child Development Study, 2020-2021 contains the data from waves 1, 2 and 3 for the 4 cohort studies. The data from all four CLS cohorts are included in the same dataset, one for each wave.

The COVID-19 Survey data for the 1946 birth cohort study (NSHD) run by the LHA is held under "https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8732" style="background-color: rgb(255, 255, 255);">SN 8732 and available under Special Licence access conditions.

Latest edition information
For the fourth edition (June 2022), the following minor corrections have been made to the wave 3 data:

• corrections to a small number of cases where CW3_GROW and CW3_GROWB were incorrectly calculated
• recoded values and reformatted the code list for CW3_COVIDVAC as the original value of 3 was removed from the final version of the survey
  

Early epidemiology indicated older members of Britain’s Bangladeshi communities were disproportionately affected by COVID-19 related morbidity and mortality. Bangladeshis were more likely to have comorbidities and live in poorer, overcrowded areas in the UK’s urban centres where viral contagion was more likely. This cross-section of socioeconomic, geographical and health related factors underlined the need for clear messaging about social distancing in a complex and shifting risk scenario – messages that this vulnerable group, who speak an oral language (Sylheti), may not have been able to access directly due to low literacy and English language proficiency.

This study identified the practices adopted by Bangladeshis in East London in response to the pandemic, the underlying attitudes and beliefs and whether and how these had been influenced by messages about social distancing. Drawing on our earlier work, it examined the role of social learning in how messages were accessed and interpreted and whether and how the health interactions of this older group were mediated by friends, family members and acquaintances. Remote interviews with older Bangladeshis and their social contacts who performed this mediating role provided insights into how linguistically and culturally appropriate messaging could build on existing beliefs and practices to promote compliance, and on social mediation as a dissemination strategy. We identified the role of choice of language (English or Sylheti), the differences between written and oral representations of COVID-19 risk, and the manifold ways in which linguistic choices give salience to aspects of a risk scenario.

Early epidemiology indicated older members of Britain’s Bangladeshi communities were disproportionately affected by COVID-19 related morbidity and mortality. Bangladeshis were more likely to have comorbidities and live in poorer, overcrowded areas in the UK’s urban centres where viral contagion was more likely. This cross-section of socioeconomic, geographical and health related factors underlined the need for clear messaging about social distancing in a complex and shifting risk scenario – messages that this vulnerable group, who speak an oral language (Sylheti), may not have been able to access directly due to low literacy and English language proficiency.

This study identified the practices adopted by Bangladeshis in East London in response to the pandemic, the underlying attitudes and beliefs and whether and how these had been influenced by messages about social distancing. Drawing on our earlier work, it examined the role of social learning in how messages were accessed and interpreted and whether and how the health interactions of this older group were mediated by friends, family members and acquaintances. Remote interviews with older Bangladeshis and their social contacts who performed this mediating role provided insights into how linguistically and culturally appropriate messaging could build on existing beliefs and practices to promote compliance, and on social mediation as a dissemination strategy. We identified the role of choice of language (English or Sylheti), the differences between written and oral representations of COVID-19 risk, and the manifold ways in which linguistic choices give salience to aspects of a risk scenario.

Objectives: To investigate factors associated with adherence to self-isolation and lockdown measures due to COVID-19 in the UK. To investigate factors associated with anxiety, depression, and self-reported general health during “lockdown” due to COVID-19 in the UK.Study design: Online cross-sectional survey.Methods: Data were collected between 6th and 7th May 2020. A total of 2240 participants living in the UK aged 18 years or older were recruited from YouGov's online research panel.Results: A total of 217 people (9.7%) reported that they or someone in their household had symptoms of COVID-19 (cough or high temperature/fever) in the last 7 days. Of these people, 75.1% had left the home in the last 24 h (defined as non-adherent). Men were more likely to be non-adherent, as were people who were less worried about COVID-19, and who perceived a smaller risk of catching COVID-19. Adherence was associated with having received help from someone outside your household. Results should be taken with caution as there was no evidence for associations when controlling for multiple analyses. Of people reporting no symptoms in the household, 24.5% had gone out shopping for non-essentials in the last week (defined as non-adherent). Factors associated with non-adherence and with a higher total number of outings in the last week included decreased perceived effectiveness of government ‘lockdown’ measures, decreased perceived severity of COVID-19 and decreased estimates of how many other people were following lockdown rules. Having received help was associated with better adherence.In this sample, 21·9% (n=458, 95% CI [20·1% to 23·7%]) reported probable anxiety (scored three or over on the GAD-2); while 23·5% (n=494, 95% CI [21·7% to 25·3]) reported probable depression (scored three or over on the PHQ-2). Poorer mental health was associated with greater financial hardship during the lockdown, thinking that you would lose contact with friends or family if you followed Government measures, more conflict with household members during the lockdown, less sense of community with people in your neighbourhood, and lower perceived effectiveness of Government measures. Females and those who were younger were likely to report higher levels of anxiety and depression. The majority of participants reported their general health as “good” (as measured by the first item of the SF-36). Poorer self-reported general health was associated with psychological distress, greater worry about COVID-19 and markers of inequality.Conclusions: Adherence to self-isolation is poor. As we move into a new phase of contact tracing and self-isolation, it is essential that adherence is improved. Communications should aim to increase knowledge about actions to take when symptomatic or if you have been in contact with a possible COVID-19 case. They should also emphasise the risk of catching and spreading COVID-19 when out and about and the effectiveness of preventative measures. Using volunteer networks effectively to support people in isolation may promote adherence.Rates of self-reported anxiety and depression in the UK during the lockdown were greater than population norms. Reducing financial hardship, promoting social connectedness, and increasing solidarity with neighbours and household members may help ease rifts within the community which are associated with distress, thereby improving mental health. Reducing inequality may also improve general health.

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.

The UCL COVID-19 Social Study at University College London (UCL) was launched on 21 March 2020. Led by Dr Daisy Fancourt and Professor Andrew Steptoe from the Department of Behavioural Science and Health, the team designed the study to track in real-time the psychological and social impact of the virus across the UK.

The study quickly became the largest in the country, growing to over 70,000 participants and providing rare and privileged insight into the effects of the pandemic on people’s daily lives. Through our participants’ remarkable two-year commitment to the study, 1.2 million surveys were collected over 105 weeks, and over 100 scientific papers and 44 public reports were published.

During COVID-19, population mental health has been affected both by the intensity of the pandemic (cases and death rates), but also by lockdowns and restrictions themselves. Worsening mental health coincided with higher rates of COVID-19, tighter restrictions, and the weeks leading up to lockdowns. Mental health then generally improved during lockdowns and most people were able to adapt and manage their well-being. However, a significant proportion of the population suffered disproportionately to the rest, and stay-at-home orders harmed those who were already financially, socially, or medically vulnerable. Socioeconomic factors, including low SEP, low income, and low educational attainment, continued to be associated with worse experiences of the pandemic. Outcomes for these groups were worse throughout many measures including mental health and wellbeing; financial struggles;self-harm and suicide risk; risk of contracting COVID-19 and developing long Covid; and vaccine resistance and hesitancy. These inequalities existed before the pandemic and were further exacerbated by COVID-19, and such groups remain particularly vulnerable to the future effects of the pandemic and other national crises.

Further information, including reports and publications, can be found on the https://www.covidsocialstudy.org/">UCL COVID-19 Social Study website.

The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data from respondents in Great Britain. Information is gathered on a range of subjects, commissioned both internally by the Office for National Statistics (ONS) and by external clients (other government departments, charities, non-profit organisations and academia).One individual respondent, aged 16 or over, is selected from each sampled private household to answer questions. Data are gathered on the respondent, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. Each regular OPN survey consists of two elements. Core questions, covering demographic information, are asked together with non-core questions that vary depending on the module(s) fielded.The OPN collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living. The OPN has expanded to include questions on other topics of national importance, such as health and the cost of living.For more information about the survey and its methodology, see the gov.uk OPN Quality and Methodology Information (QMI) webpage.Changes over timeUp to March 2018, the OPN was conducted as a face-to-face survey. From April 2018 to November 2019, the OPN changed to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for module customers.In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held under Secure Access conditions in SN 8635, ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access. (See below for information on other Secure Access OPN modules.)From August 2021, as coronavirus (COVID-19) restrictions were lifted across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remained sustainable. Secure Access OPN modulesBesides SN 8635 (which includes the COVID-19 Module), other Secure Access OPN data includes sensitive modules run at various points from 1997-2019, including Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See the individual studies for further details and information on how to apply to use them.

The non-core questions for this month were: Tobacco consumption (Module 210): this module was asked on behalf of HM Revenue and Customs to help estimate the amount of tobacco consumed as cigarettes. Due to the potentially sensitive nature of the data within this module, cases for respondents aged under 18 have been removed. Disability monitoring (Module 363): this module was asked on behalf of the Department for Work and Pensions (DWP) which is interested in information on disability and includes two questions that ask about awareness of the Disability Discrimination Act. The module aims to identify the scale of problems those with long-term illnesses or disabilities have accessing goods, facilities and services. This version of the data does not contain variables M363_3M, M363_6AM, M363_6bM, M363_7M, M363_26, M363_27, M363_28, and M363_29. The Special Licence version of this module is held at the Archive under SN 6793. Road Pricing (Module MAE): this module was asked on behalf of the Department for Transport and asks for opinions on road pricing. Disability (Module MCA): this module was asked on behalf of the Office for National Statistics and seeks information regarding health problems which are long-lasting in nature and cause problems with normal daily activities. Variables MCA_1b1M and MCA_2b2M have been recoded into smaller groupings. Later life (Module MCE): this module was asked on behalf of DWP on behalf of a number of other government departments which are interested in what people think of the support available to help older people to continue to live independently in later life. Health and work (Module MCP): this module was asked by DWP on behalf of the Health, Work and Well-being Delivery Unit. Questions relate to health, well-being and work. This version of the data does not contain variables MCP_14, MCP_15M, MCP_16 and MCP_17 as they are considered disclosive.

There were 11,480 deaths registered in England and Wales for the week ending November 14, 2025, compared with 11,297 in the previous week. During this time period, the two weeks with the highest number of weekly deaths were in April 2020, with the week ending April 17, 2020, having 22,351 deaths, and the following week 21,997 deaths, a direct result of the COVID-19 pandemic in the UK. Death and life expectancy As of 2022, the life expectancy for women in the UK was just over 82.5 years, and almost 78.6 years for men. Compared with 1765, when average life expectancy was under 39 years, this is a huge improvement in historical terms. Even in the more recent past, life expectancy was less than 47 years at the start of the 20th Century, and was under 70 as recently as the 1950s. Despite these significant developments in the long-term, improvements in life expectancy stalled between 2009/11 and 2015/17, and have even gone into decline since 2020. Between 2020 and 2022, for example, life expectancy at birth fell by 23 weeks for females, and 37 weeks for males. COVID-19 in the UK The first cases of COVID-19 in the United Kingdom were recorded on January 31, 2020, but it was not until a month later that cases began to rise exponentially. By March 5 of this year there were more than 100 cases, rising to 1,000 days later and passing 10,000 cumulative cases by March 26. At the height of the pandemic in late April and early May, there were around six thousand new cases being recorded daily. As of January 2023, there were more than 24.2 million confirmed cumulative cases of COVID-19 recorded in the United Kingdom, resulting in 202,156 deaths.