In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. The number of cases in the UK increased significantly at the end of 2021. On January 13, 2023, the number of confirmed cases in the UK amounted to 24,243,393. COVID deaths among highest in Europe There were 202,157 confirmed coronavirus deaths in the UK as of January 13, 2023. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Current infection rate in Europe The current infection rate in the UK was 50 cases per 100,000 population in the last seven days as of January 16. San Marino had the highest seven day rate of infections in Europe at 336.

Context

Within the current response of a pandemic caused by the SARS-CoV-2 coronavirus, which in turn causes the disease, called COVID-19. It is necessary to join forces to minimize the effects of this disease.

Therefore, the intention of this dataset is to save data scientists time:

• Gather the data at the country level, encoding the country with its ISO code to allow easy access to other data
• Perform pre-processing of data, calculations of increments and other indicators that can facilitate modeling.
• Add the response of the governments over time so that it can be taken into account in the modeling.
• Daily update.

This dataset is not intended to be static, so suggestions for expanding it are welcome. If someone considers it important to add information, please let me know.

Content

The data contained in this dataset comes mainly from the following sources:

Source: Center for Systems Science and Engineering (CSSE) at Johns Hopkins University https://github.com/CSSEGISandData/COVID-19 Provided by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE): https://systems.jhu.edu/

Source: OXFORD COVID-19 GOVERNMENT RESPONSE TRACKER https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker Hale, Thomas and Samuel Webster (2020). Oxford COVID-19 Government Response Tracker. Data use policy: Creative Commons Attribution CC BY standard.

The original data is updated daily.

The features it includes are:

• Country Name

• Country Code ISO 3166 Alpha 3

• Date

• Incidence data:

  • confirmed
  • deaths
  • recoveries

• Daily increments:

  • confirmed_inc
  • deaths_inc
  • recoveries_inc

• Empirical Contagion Rate - ECR

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3508582%2F3e90ecbcdf76dfbbee54a21800f5e0d6%2FECR.jpg?generation=1586861653126435&alt=media" alt="">

• GOVERNMENT RESPONSE TRACKER - GRTStringencyIndex

  OXFORD COVID-19 GOVERNMENT RESPONSE TRACKER - Stringency Index

• Indices from Start Contagion

  • Days since the first case of contagion is overcome
  • Days since 100 cases are exceeded

• Percentages over the country's population:

  • confirmed_PopPct
  • deaths_PopPct
  • recoveries_PopPct

The method of obtaining the data and its transformations can be seen in the notebook:

Notebook COVID-19 Data by country with Government Response

Photo by Markus Spiske on Unsplash

First reported in Wuhan, China, in December 2019, now more than 846,200 confirmed cases of COVID-19 are spread across 187 countries worldwide. The US and several countries in Europe such as Italy, Spain, and Belgium have continued to see a decrease in daily cases. Russia, Brazil, and Latin American countries are seeing increasing trends. India has also seen an increase in the number of new cases reported despite strict distancing measures taken early on.
Special populations analysis covered in the report include the following:
COVID-19 in children may result in systemic multisystem syndrome with severe outcomes.
Childhood routine vaccination rates drop during pandemic.
COVID-19’s impact in pregnant women unclear, though most cases are asymptomatic.
The COVID-19 pandemic could cause an increase in the prevalence of post-traumatic stress disorder (PTSD).
Complications of opioid addiction will be challenging for the management of disease during the COVID-19 pandemic. Read More

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.

COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. 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.

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. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

This open data publication has moved to COVID-19 Statistical Data in Scotland (from 02/11/2022) Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. This dataset provides information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. There is a large amount of data being regularly published regarding COVID-19 (for example, Coronavirus in Scotland - Scottish Government and Deaths involving coronavirus in Scotland - National Records of Scotland. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications. Data visualisation is available to view in the interactive dashboard accompanying the COVID-19 Statistical Report. Please note information on COVID-19 in children and young people of educational age, education staff and educational settings is presented in a new COVID-19 Education Surveillance dataset going forward.

This dataset contains daily data trackers for the COVID-19 pandemic, aggregated by month and starting 18.3.20. The first release of COVID-19 data on this platform was on 1.6.20. Updates have been provided on a quarterly basis throughout 2023/24. No updates are currently scheduled for 2024/25 as case rates remain low. The data is accurate as at 8.00 a.m. on 8.4.24. Some narrative for the data covering the latest period is provided here below: Diagnosed cases / episodes • As at 3.4.24 CYC residents have had a total 75,556 covid episodes since the start of the pandemic, a rate of 37,465 per 100,000 of population (using 2021 Mid-Year Population estimates). The cumulative rate in York is similar to the national (37,305) and regional (37,059) averages. • The latest rate of new Covid cases per 100,000 of population for the period 28.3.24 to 3.4.24 in York was 1.49 (3 cases). The national and regional averages at this date were 1.67 and 2.19 respectively (using data published on Gov.uk on 5.4.24).

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.

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

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.

This report provides an update on the assessment of how the pharmaceutical industry perceives the supply chain disruption caused by the COVID-19 pandemic, including the challenges associated with clinical trials, logistics, API and finished dose manufacturing.
Since the first case was diagnosed in Wuhan, China, in December 2019, COVID-19 cases have continued to rise rapidly across the globe. Read More

The first Coronavirus case in the United Kingdom (UK) was reported in February 28, 2020. Since then the government made repetitive calls on the public to practice social distancing in an effort to stop the spread of the Coronavirus (Covid-19), and finally announced national lockdown on March 23, 2020, forcing many people to work from home. Over this period of time, there was an increase in online home console market share, which went from 45 percent in Week 8 to 61 percent by the end of Week 12, ending March 22, 2020, just the day before national lockdown went into effect. The largest increase in the online home console market share occurred in week 11, or March 9 to March 15, 2020, at 62 percent.

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

Work Package One; A UK survey of people bereaved between 16th March 2020 and 2nd January 2021. Three time points: baseline (n=711), c. 7 months (n=384) and c. 13 months (n=297) post-bereavement. At baseline 88.6 % were female, 43.8% were bereaved by Covid-19, 55.6 % had lost parents, followed by partners (21.4%). 4.7% identified with a minority ethnic background. Validated measures assessed grief and coping response (Adult Attitude to Grief scale), social support (Inventory for Social Support), prolonged grief disorder (PGD) (Traumatic Grief Inventory) and wellbeing (ONS wellbeing measure).

Work Package Two; Semi-structured interviews with sub-sample of survey participants, interviewed between May 2021 and February 2022. 24 participants completed a first interview and 15 completed a second interview around 4 months after their first interview. 19 were female, 10 had lost partners, 11 were bereaved by Covid-19, 6 identified with minority ethnic background.

Work Package Three: Cross-sectional open online survey of UK voluntary sector bereavement services (March-May 2021) (n=147); Qualitative case study interviews with bereavement service providers at a purposive sample of services (14 services, 24 interviews).

COVID-19 is impacting the grief experiences of people bereaved during the pandemic, whilst also affecting the bereavement services that support them. This study aims to investigate the grief experiences, support needs and use of bereavement support by people bereaved during the pandemic, and the adaptations, challenges and innovation involved in delivering equitable bereavement support.

We use qualitative and quantitative methods in three work packages:

(WP1) A UK survey at three time points: baseline, 7 and 13 months post-death. Recruitment via social media, organisations representing minority ethnic groups, and bereavement organisations. Questions investigate the impact of end-of-life and bereavement experiences during COVID-19 and subsequent access to, needs for and experiences of bereavement support. Validated measures assess grief and coping response, social support, prolonged grief disorder (PGD) and wellbeing.

(WP2) Longitudinal semi-structured telephone interviews (2 time-points) with a sample of respondents exploring experiences of grief and bereavement during COVID-19, including bereavement support and unmet needs.

(WP3) An online survey of bereavement service providers identifies service adaptations, key challenges and approaches to delivering accessible bereavement care during the pandemic. Survey findings inform targeted case studies, developed via telephone interviews, to describe innovative practice.

The study identifies ‘real-time’ implications for the delivery of end-of-life care and bereavement support during and beyond the pandemic, to ensure prompt translation into practice.

These indicators are designed to accompany the SHMI publication. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. There has been a fall in the number of spells for some trusts due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Contextual indicators on the number of provider spells which are excluded from the SHMI due to them being related to COVID-19 and on the number of provider spells as a percentage of pre-pandemic activity (January 2019 – December 2019) are produced to support the interpretation of the SHMI. These indicators are being published as experimental statistics. Experimental statistics are official statistics which are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. Notes: 1. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. Maidstone and Tunbridge Wells NHS Trust (trust code RWF) has submitted a number of records with a patient classification of ‘day case’ or ‘regular day attender’ and an intended management value of ‘patient to stay in hospital for at least one night’. This mismatch has resulted in the patient classification being updated to ‘ordinary admission’ by the Hospital Episode Statistics (HES) data cleaning rules. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for these trusts should therefore be interpreted with caution. 2. There is a shortfall in the number of records for Royal Free London NHS Foundation Trust (trust code RAL) and Northern Care Alliance NHS Foundation Trust (trust code RM3). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 3. A proposed merger between Northern Devon Healthcare NHS Trust (trust code RBZ) and Royal Devon and Exeter NHS Foundation Trust (trust code RH8) was due to take place on 1 April 2022. The new trust name and code is yet to be confirmed. Please note that separate indicator values have been produced for these organisations for this publication. When we receive confirmation of the new trust name and code we will reflect the new organisation structure within future publications. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.

Time series of Covid-19 Case Fatality Rate (CFR) for Spain, the United Kingdom, and the United States.

Compared to March 2020, retail sales value of goods sold in predominantly food and household goods stores in Great Britain showed the greatest decline with in fuel stores with 55.2 percent. During the summer months, month-on-month growth in retail sales value was relatively stable across all retail sectors. Clothing, textile, and footwear stores experienced the highest growth in June 2020 with 72.5 percent, following the lifting of the lockdown measures in the United Kingdom.

The first Coronavirus case in the UK was recorded in February 28, 2020, although there had been British nationals abroad who contracted the virus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

Approximately one quarter of the UK population have a migration background (first- or second-generation immigrants). Some ethnic minority groups are more likely to be in atypical or flexible employment than the White British majority. In particular during a time of health and economic crisis, such as the COVID–19 pandemic, those ethnic groups were expected to be economically more vulnerable than other groups. This study shows the increased vulnerability of some ethnic minority groups during COVID–19 by looking at their labour market outcomes compared to White British. Specifically, we ask whether it was their disproportionate presence in flexible employment or in shut-down occupations that made some ethnic minority groups vulnerable to adverse labour market outcomes during the COVID–19 recession? Using the COVID–19 recession in the UK as a case study, we employ weighted linear probability models with 2021 data from the Evidence for Equality National Survey (EVENS) to look at changes in economic indicators across ethnic groups and gender. We report heterogeneity in flexible employment rates within the non-White group and between the non-White and the White British group. By using a conditional decomposition method, we aim to show that those ethnic minority groups who were disproportionately on flexible contracts experienced worse economic effects than the White British group. The collection consists of the Stata Do-File which can be used to reproduce the study.

Was it their disproportionate presence in flexible employment or in shut-down occupations that made some ethnic minority groups vulnerable to adverse labour market outcomes during the COVID–19 recession? Using the COVID–19 recession in the UK as a case study, we employ weighted linear probability models with 2021 data from the Evidence for Equality National Survey (EVENS) to look at changes in economic indicators across ethnic groups and gender. We report heterogeneity in flexible employment rates within the non-White group and between the non-White and the White British group. By using a conditional decomposition method, we conclude that those ethnic minority groups who were disproportionately on flexible contracts experienced worse economic effects than the White British group.

Information on number of COVID vaccinations and payments made to individual branches listed by their ODS code in the same format as FOI 19177: https://opendata.nhsbsa.net/dataset/foi-19177 Can I get an historical extract going back to when the vaccinations first began. Would you also be able to provide this data on an ongoing monthly basis when new data is made available? Response A copy of the information is attached. Regarding your query about making the data available on an on-going basis, there is no current plan to routinely publish this information. Therefore please continue to request the information at regular intervals if you wish to receive this regularly. The NHSBSA makes payments for covid vaccinations to Pharmacies and Primary Care Network (PCN) providers in England. Covid vaccination data is keyed in via Point of Care (POC) Systems and they transferred to the NHSBSA Manage Your Service (MYS) application. Each month, vaccine providers submit claims to request payment based on the data that has been transferred into MYS. To be paid in a timely fashion such claims must be submitted during a specified declaration submission period. Should claims be submitted outside the time windows, payments will be made later. This means that in some cases there is a difference between the number of vaccines that have been 'claimed' and the number that have been 'paid'. Both the number of 'claimed' and 'paid' vaccinations have been reported in this request. When considering the nature of the vaccine data there are several ways it can be reported over time: Administration Month - This is the month in which the vaccine was administered to the patient. Payment Month - This is the month in which the payment was made dispenser of the vaccine. Note that all payments for Pharmacies are paid one month later than those for PCN providers. Keying Month - This is the month in which the vaccine record first appeared on the MYS system. Submission/Claim Month - This is the month in which the claim for payment for a vaccination occurred. For example, suppose that a PCN patient is given a covid vaccination dose 1 in January (Administration Month) and then the paper record of this is misplaced for a while. The record is found and keyed into a POC system during February (Keying Month). The Provider is allowed to claim for keying during February in the first 5 days of March, but they're a little late and authorise the claim on the 7th of March (Submission Month) As the claim is outside the submission window it is not paid in March, it will instead be paid during April (Payment Month). Another example could be a Pharmacy patient given a covid vaccination dose 1 in January (Administration Month), keyed in January (Keying Month), then submitted in February (Submission Month) and then payments are calculated in February, however as this is for a pharmacy the payments are held back and not paid until March (Payment Month). For the purposes of this request, we have chosen to report by Administration Month. Data included in this request is limited to vaccinations carried out by Pharmacies only. The latest data used is a snapshot of the MYS system data that was taken on 7th January 2022. This is the snapshot of data taken after the January submission period that was used to calculate payments The total used for the payment calculation may not match the totals shown in 'live' POC systems or MYS that continue to receive updates after the snapshot used to calculate payments was taken. Vaccination records are limited to those which have been associated with a declaration submission. This may include late submission declarations received after the deadline for declarations such records are not processed until the next month. Please note that some vaccinations attract a supplementary fee, so it is not possible to determine the number of vaccinations by dividing the total paid by the basic Item of Service (IoS) fee. It is possible for new records from old administration months to be entered in the future, thus the totals here for each administration months could change when more data is processed. If you have any queries regarding the data provided, or if you plan on publishing the data, please contact dataandinsightsupport@nhsbsa.nhs.uk ensuring you quote the above reference. This is important to ensure that the figures are not misunderstood or misrepresented. If you plan on producing a press or broadcast story based upon the data please contact nhsbsa.communicationsteam@nhs.net. This is important to ensure that the figures are not misunderstood or misrepresented.