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.

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 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).

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!

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.

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had been confirmed in almost every country in the world. The virus had infected over 687 million people worldwide, and the number of deaths had reached almost 6.87 million. The most severely affected countries include the U.S., India, and Brazil.

COVID-19: background information COVID-19 is a novel coronavirus that had not previously been identified in humans. The first case was detected in the Hubei province of China at the end of December 2019. The virus is highly transmissible and coughing and sneezing are the most common forms of transmission, which is similar to the outbreak of the SARS coronavirus that began in 2002 and was thought to have spread via cough and sneeze droplets expelled into the air by infected persons.

Naming the coronavirus disease Coronaviruses are a group of viruses that can be transmitted between animals and people, causing illnesses that may range from the common cold to more severe respiratory syndromes. In February 2020, the International Committee on Taxonomy of Viruses and the World Health Organization announced official names for both the virus and the disease it causes: SARS-CoV-2 and COVID-19, respectively. The name of the disease is derived from the words corona, virus, and disease, while the number 19 represents the year that it emerged.

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.

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

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.

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.

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.

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.

Prior to the COVID-19 pandemic, telemedicine had not reached its full potential in the US, with several barriers preventing its widespread uptake, including reimbursement and access issues, lack of awareness, resistance to change, preference for in-person care, and technical and connectivity issues. It is widely anticipated that COVID-19 may be the tipping point for telemedicine as the full potential of the technology is increasingly realized by patients, healthcare systems, and payers. As a result of the pandemic, regulations and policies governing reimbursement and use of telemedicine have changed significantly, leading to expanded access and an unprecedented demand for these services. The report assesses the use of live videoconferencing technologies, which allow the provision of on-demand, virtual, outpatient care during the COVID-19 pandemic as a result of social distancing and lockdown measures.- Read More

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