In May 2020, a survey carried out in the UK found that the 80 percent of British respondents overall reported that most people they knew had been obeying the lockdown rules. The respondents were more skeptical of the wider public as only 67 percent that most people in the UK were obeying the lockdown rules.

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.

11th January 2020 Change to vaccination data made available by UK gov - now just cumulative number of vaccines delivered are available for both first and second doses. For the devolved nations the cumulative totals are available for the dates from when given, however for the UK as a whole the total doses given is just on the last date of the index, regardless of when those vaccines were given.

4th January 2020 VACCINATION DATA ADDED - New and Cumulative First Dose Vaccination Data added to UK_National_Total_COVID_Dataset.csv and UK_Devolved_Nations_COVID_Dataset.csv

2nd December 2020:

NEW population, land area and population density data added in file NEW_Official_Population_Data_ONS_mid-2019.csv. This data is scraped from the Office for National Statistics and covers the UK, devolved UK nations, regions and local authorities (boroughs).

20th November 2020:

With European governments struggling with a 'second-wave' of rising cases, hospitalisations and deaths resulting from the SARS-CoV-2 virus (COVID-19), I wanted to make a comparative analysis between the data coming out of major European nations since the start of the pandemic.

I started by creating a Sweden COVID-19 dataset and now I'm looking at my own country, the United Kingdom.

The data comes from https://coronavirus.data.gov.uk/ and I used the Developer's Guide to scrape the data, so it was a fairly simple process. The notebook that scapes the data is public and can be found here. Further information about data collection methodologies and definitions can be found here.

The data includes the overall numbers for the UK as a whole, the numbers for each of the devolved UK nations (Eng, Sco, Wal & NI), English Regions and Upper Tier Local Authorities (UTLA) for all of the UK (what we call Boroughs). I have also included a small table with the populations of the 4 devolved UK nations, used to calculate the death rates per 100,000 population.

As I've said for before - I am not an Epidemiologist, Sociologist or even a Data Scientist. I am actually a Mechanical Engineer! The objective here is to improve my data science skills and maybe provide some useful data to the wider community.

Any questions, comments or suggestions are most welcome! I am open to requests and collaborations! Stay Safe!

Context

Public Health England (PHE) coronavirus cases reported daily. This data shows case numbers as reported to PHE. Cases includes people who have recovered.

Content

DateVal : dd/mm/yyyy CMODateCount : The number of cases reported for the day CumCases: The cumulative number of cases IncreasePercent: The percentage increase in cases from the previous day DeathPercent: The percentage increase/decrease in daily deaths from the previous day CumCases7DayAvg: 7 day moving average of the cumulative number of cases CumDeaths7DayAvg: 7 day moving average of the cumulative number of deaths DailyDeath7DayAvg: 7 day moving average of the daily number of deaths

IncreasePercent and moving 7 day averages are calculated fields added to the original source.

Acknowledgements

https://www.gov.uk/government/publications/covid-19-track-coronavirus-cases https://coronavirus.data.gov.uk/

As of November 2020, a number of vaccines for the coronavirus (COVID-19) were in phase III clinical trials, with a small number further along the development stage. In the United Kingdom, a survey found that only 17 percent of respondents strongly support making a coronavirus immunization compulsory for everyone have, although there is strong support for people to be banned from posting conspiracy theories online about the vaccine.

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.

NHS UK - COVID-19 Daily Deaths

This section contains information on deaths of patients who have died in hospitals in England and had tested positive for COVID-19 at time of death. All deaths are recorded against the date of death rather than the date the deaths were announced. Interpretation of the figures should take into account the fact that totals by date of death, particularly for most recent days, are likely to be updated in future releases. For example as deaths are confirmed as testing positive for COVID-19, as more post-mortem tests are processed and data from them are validated. Any changes are made clear in the daily files.

These figures do not include deaths outside hospital, such as those in care homes. This approach makes it possible to compile deaths data on a daily basis using up to date figures.

Dataset Content

These figures will be updated at 2pm each day and include confirmed cases reported at 5pm the previous day. Confirmation of COVID-19 diagnosis, death notification and reporting in central figures can take up to several days and the hospitals providing the data are under significant operational pressure. This means that the totals reported at 5pm on each day may not include all deaths that occurred on that day or on recent prior days.

The original dataset is sourced directly from the NHS source site, this original dataset is then cleaned and converted to a csv format available for inclusion into a Kaggle notebook.

There are 3 files considered within the data :- 1. Fatalities_by_age_uk 2.Fatalities_by_region_uk 3.Fatalities_by_trust_uk

Data runs from March 1st up to the current day. Any discrepancies will be outlined. The first is cumulative for any previous days leading up to of relevance. The following days are not cumulative and represent the updated value for the date under consideration.

A start kernel is provided to demonstrate using the dataset.

Citations

This dataset is sourced from the NHS statistical work areas:- https://www.england.nhs.uk/statistics/statistical-work-areas/

This dataset has been sourced and provided to aid in the following competition:- https://www.kaggle.com/c/covid19-global-forecasting-week-4

This is a dataset using the data gathered by the university of Oxford here:

https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker

This data was cleaned and organized in such a way s to allow the application of mathematical models that could help us better understand how the different measures impact the actual spread of the disease. Attention: several assumptions were made to fill the blanks, and thus this dataset should be used with care. For more information refer to the notebook.

there are three datasets:

OxCGRT_Download_29_03 is the original one

COVID_gov_complete_29_03 is the reorganized dataset containing all the countries

COVID_gov_restricted_29_03 is the reorganized dataset containing only the countries with a significant amount of information

Introduction

This page comprises the additional datasets used for the COVID-19 Global Forecasting Challenge (currently in week 3). Only datasets that have not been hosted on Kaggle will be uploaded here: * Oxford COVID-19 Government Response Tracker * Assessment Capacities Project COVID-19 Government Measures

UPDATE: Please see my notebook on the COVID-19 Global Forecasting Challenge (Week 3) competition here for merging the data.

Oxford COVID-19 Government Response Tracker

The Oxford COVID-19 Government Response Tracker (OxCGRT) provides a systematic cross-national, cross-temporal measure to understand how government responses have evolved over the full period of the disease’s spread. The project tracks governments’ policies and interventions across a standardized series of indicators and creates a composite index to measure the stringency of these responses. Data is collected and updated in real time by a team of dozens of students and staff at Oxford University. Read the white paper here. Access the OxCGRT website here.

Indicators

The OxCGRT tracks 11 indicators of government response:

1. School closing (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend closing
     • 2 = Require closing
2. Workplace closing (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend closing
     • 2 = Require closing
3. Cancel public events (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend cancelling
     • 2 = Require cancelling
4. Close public transport (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend closing
     • 2 = Require closing
5. Public info campaigns(with geographic scope)
   • Ordinal scale:
     • 0 = No COVID-10 public information campaign
     • 1 = COVID-10 public information campaign
6. Restrictions on internal movement (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend movement restriction
     • 2 = Restricted movement
7. International travel controls
   • Ordinal scale:
     • 0 = No measures
     • 1 = Screening
     • 2 = Quarantine on high-risk regions
     • 3 = Ban on high-risk regions
8. Fiscal measures
   • Value of fiscal stimuli in USD
9. Monetary measures
   • Value of interest rate in %
10. Emergency investment in health care
    • Value of new short-term spending on health in USD
11. Investment in vaccines
    • Value of investment in USD

Indicators with geographic scope are coded in the following way: - 0 = Targeted - 1 = General

The Assessment Capacities Project (ACAPS) COVID-19 Government Measures Dataset

This dataset comprises government measures and descriptions of these measures by country and date. The measures include:

1. Social distancing
2. Movement restrictions
3. Public health measures
4. Social and economic measures
5. Lockdowns

Descriptors of these measures include: - Date of implementation - Specific measure - Penalties for non-compliance - Source (e.g. government, media)

Context

COVID-19 The Government Response Stringency Index

The Government Response Stringency Index is a composite measure based on nine response indicators including school closures, workplace closures, and travel bans, rescaled to a value from 0 to 100 (100 = strictest response).

Content

OxCGRT collects publicly available information on indicators of government response. These indicators take policies such as school closures, travel bans, etc. and record them on an ordinal scale; the remainder are financial indicators such as fiscal or monetary measures.

OxCGRT measures the variation in governments’ responses using its 'COVID-19 Government Response Stringency Index (Stringency Index)'. This composite measure is a simple additive score of nine indicators measured on an ordinal scale, rescaled to vary from 0 to 100. Please note that this measure is for comparative purposes only, and should not necessarily be interpreted as a rating of the appropriateness or effectiveness of a country's response.

Acknowledgements

Data published by Thomas Hale, Sam Webster, Anna Petherick, Toby Phillips, and Beatriz Kira (2020). Oxford COVID-19 Government Response Tracker, Blavatnik School of Government. https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker

Photo by Étienne Godiard on Unsplash

Inspiration

BCG - COVID-19 AI Challenge Improve BCG Data and Provide Insights to "BCG - COVID-19" Clinical Trials

Sample characteristics, and prevalence of loneliness across sociodemographic, COVID-19, social and health factors.

A nationwide survey was conducted during the first UK lockdown to further understanding of the degree to which motives for exercise were associated with physical activity (PA) behaviours and, in turn, how PA behaviours were associated with mental health. A cross-sectional design was employed and data were collected by use of a one-off online survey (N = 392; 18–85 years; MBMI = 25.48; SDBMI = 5.05; 314 women). Exercise motives, PA, and mental health were measured by use of the Behavioural Regulations in Exercise Questionnaire-3, Brunel Lifestyle Physical Activity Questionnaire, and General Health Quesionnaire-12, respectively. Participants were also asked to specify their average step count per day, if they used a mobile device for this purpose (n = 190). Analyses comprised hierarchical regressions and partial correlations. Results indicated that behavioural regulations were more strongly associated with planned PA pre-lockdown, compared to during lockdown. There were no differences observed in explained variance between pre- and during lockdown for unplanned PA and steps per day. Planned and unplanned PA were significant explanatory variables for mental health both pre- and during lockdown, but sedentary behaviour was not. Partial correlations, with BMI and age partialled out, showed that steps per day were not correlated with mental health either pre- or during lockdown. The range of variables used to explain planned and unplanned PA and mental health suggest that people’s motives to exercise were tempered by lockdown. For those who routinely measured their steps per day, the step count was unrelated to their mental health scores both pre- and during lockdown. It appears that engagement in regular PA confers some minor benefits for mental health.

Additional file 1. Stakeholder list.

Multivariable logistic regression analysis of factors associated with loneliness.

On May 10, 2020, the Prime Minister of the British government, Boris Johnson, announced plans for the easing of coronavirus lockdown rules. According to a survey carried out in Great Britain following this announcement, 46 percent of Brits think that the changes go too far in relaxing the rules, while 35 percent believe the balance is about right. 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.

BackgroundThe COVID-19 pandemic brought global disruption to health, society and economy, including to the conduct of clinical research. In the European Union (EU), the legal and ethical framework for research is complex and divergent. Many challenges exist in relation to the interplay of the various applicable rules, particularly with respect to compliance with the General Data Protection Regulation (GDPR). This study aimed to gain insights into the experience of key clinical research stakeholders [investigators, ethics committees (ECs), and data protection officers (DPOs)/legal experts working with clinical research sponsors] across the EU and the UK on the main challenges related to data protection in clinical research before and during the pandemic.Materials and methodsThe study consisted of an online survey and follow-up semi-structured interviews. Data collection occurred between April and December 2021. Survey data was analyzed descriptively, and the interviews underwent a framework analysis.Results and conclusionIn total, 191 respondents filled in the survey, of whom fourteen participated in the follow-up interviews. Out of the targeted 28 countries (EU and UK), 25 were represented in the survey. The majority of stakeholders were based in Western Europe. This study empirically elucidated numerous key legal and ethical issues related to GDPR compliance in the context of (cross-border) clinical research. It showed that the lack of legal harmonization remains the biggest challenge in the field, and that it is present not only at the level of the interplay of key EU legislative acts and national implementation of the GDPR, but also when it comes to interpretation at local, regional and institutional levels. Moreover, the role of ECs in data protection was further explored and possible ways forward for its normative delineation were discussed. According to the participants, the pandemic did not bring additional legal challenges. Although practical challenges (for instance, mainly related to the provision of information to patients) were high due to the globally enacted crisis measures, the key problematic issues on (cross-border) health research, interpretations of the legal texts and compliance strategies remained largely the same.

As of January 3, 2021. it was found that around 65 percent of survey respondents in the United Kingdom had been wearing a face mask outside to protect themselves and others from the coronavirus (COVID-19). The share of people wearing a mask in the UK has increased significantly since March, when only eight percent of respondents were always wearing a face mask outside, while according to the latest survey wave eleven percent reported never wearing a mask. Across the four countries of the UK, there hads been differing timings of regulations to make the wearing of face masks mandatory in public places. Compared to the UK, some other European countries introduced the wearing of face masks earlier into the pandemic.

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.

In the United Kingdom, the revenue of the legal services sector grew more than ********* since 2000, reaching a value of over ** billion British pounds in 2024. Despite the coronavirus (COVID-19) pandemic, the legal services sector was not negatively impacted, unlike many others. The revenue registered in 2020, in fact, was a slight increase when compared to 2019, with the growth of the industry being exponential since then.

This publication provides the most detailed picture available of people who used NHS funded secondary mental health, learning disabilities and autism services in England during the financial year 2021-22. All the analysis included in this publication can be found in the reference data tables, and in the associated machine-readable data file. Information you need to know about the quality of these statistics and how they can be interpreted can be found in the main report. An interactive report is also available allowing you to explore some statistics in further detail. Demographic analysis (age, gender, ethnicity and Index of Multiple Deprivation) is presented for 2021-22. Please consult previous editions of this publication series for demographic analysis for previous years. All annual and monthly publications relating to uses of mental health, learning disabilities and autism services can be found in the related links below. Please note: This publication covers the 2021-22 reporting year and will likely show some of the impacts of COVID-19 however there were no official lockdowns during the period. In places comparisons are made to the 2020-21 reporting year which did feature the impact of the COVID-19 and COVID-19 lockdowns during the pandemic in England. NHS Digital is continually working to improve the relevance and usefulness of content in the Mental Health Bulletin. As a result this annual report includes the addition of a number of new reference tables. These tables have been split out by geographical breakdown and with a focus on inpatients or outpatients. Improvements to the publication page have also been made to improve accessibility.