An August 2021 study looked at the measures set forth by visitor attractions in England following the coronavirus (COVID-19) pandemic in 2020. Overall, ** percent of establishments had incorporated at least one safety measure to curb the spread of COVID-19. Providing hand sanitizers was the most common procedure to be used, with ** percent of respondents claiming to have instituted the measure. In contrast, only ***** percent had introduced daily guest health checks, making it the least popular countermeasure to be used by the attractions.

As of April 2020, ** percent of UK citizens surveyed believed social distancing measures were necessary during the coronavirus (COVID-19) pandemic, while ** percent of respondents thought that it was necessary to prevent flights coming into the UK from virus hotspots. Although less than ********** of respondents thought that closing schools was important in response to the coronavirus outbreak.

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 impact of the coronavirus (COVID-19) pandemic on people, households and communities in Great Britain – indicators from the Opinions and Lifestyle Survey (OPN).

In February 2020, it was found that 62 percent of British people surveyed in the United Kingdom (UK) were consciously washing their hands with soap and water as a precaution against coronavirus (COVID-19), while 49 percent of respondents were using hand sanitizer to protect against the virus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

Due to changes in the collection and availability of data on COVID-19, this website will no longer be updated. The webpage will no longer be available as of 11 May 2023. On-going, reliable sources of data for COVID-19 are available via the COVID-19 dashboard and the UKHSA GLA Covid-19 Mobility Report Since March 2020, London has seen many different levels of restrictions - including three separate lockdowns and many other tiers/levels of restrictions, as well as easing of restrictions and even measures to actively encourage people to go to work, their high streets and local restaurants. This reports gathers data from a number of sources, including google, apple, citymapper, purple wifi and opentable to assess the extent to which these levels of restrictions have translated to a reductions in Londoners' movements. The data behind the charts below come from different sources. None of these data represent a direct measure of how well people are adhering to the lockdown rules - nor do they provide an exhaustive data set. Rather, they are measures of different aspects of mobility, which together, offer an overall impression of how people Londoners are moving around the capital. The information is broken down by use of public transport, pedestrian activity, retail and leisure, and homeworking. Public Transport For the transport measures, we have included data from google, Apple, CityMapper and Transport for London. They measure different aspects of public transport usage - depending on the data source. Each of the lines in the chart below represents a percentage of a pre-pandemic baseline. activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Citymapper Citymapper mobility index 2021-09-05 Compares trips planned and trips taken within its app to a baseline of the four weeks from 6 Jan 2020 7.9% 28% 19% Google Google Mobility Report 2022-10-15 Location data shared by users of Android smartphones, compared time and duration of visits to locations to the median values on the same day of the week in the five weeks from 3 Jan 2020 20.4% 40% 27% TfL Bus Transport for London 2022-10-30 Bus journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 34% 24% TfL Tube Transport for London 2022-10-30 Tube journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 30% 21% Pedestrian activity With the data we currently have it's harder to estimate pedestrian activity and high street busyness. A few indicators can give us information on how people are making trips out of the house: activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Walking Apple Mobility Index 2021-11-09 estimates the frequency of trips made on foot compared to baselie of 13 Jan '20 22% 47% 36% Parks Google Mobility Report 2022-10-15 Frequency of trips to parks. Changes in the weather mean this varies a lot. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail & Rec Google Mobility Report 2022-10-15 Estimates frequency of trips to shops/leisure locations. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail and recreation In this section, we focus on estimated footfall to shops, restaurants, cafes, shopping centres and so on. activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Grocery/pharmacy Google Mobility Report 2022-10-15 Estimates frequency of trips to grovery shops and pharmacies. Compared to baseline of 5 weeks from 3 Jan '20 32% 55.00% 45.000% Retail/rec Google Mobility Report 2022-10-15 Estimates frequency of trips to shops/leisure locations. Compared to baseline of 5 weeks from 3 Jan '20 32% 55.00% 45.000% Restaurants OpenTable State of the Industry 2022-02-19 London restaurant bookings made through OpenTable 0% 0.17% 0.024% Home Working The Google Mobility Report estimates changes in how many people are staying at home and going to places of work compared to normal. It's difficult to translate this into exact percentages of the population, but changes back towards ‘normal' can be seen to start before any lockdown restrictions were lifted. This value gives a seven day rolling (mean) average to avoid it being distorted by weekends and bank holidays. name Source Latest Baseline Min/max value in Lockdown 1 Min/max value in Lockdown 2 Min/max value in Lockdown 3 Residential Google Mobility Report 2022-10-15 Estimates changes in how many people are staying at home for work. Compared to baseline of 5 weeks from 3 Jan '20 131% 119% 125% Workplaces Google Mobility Report 2022-10-15 Estimates changes in how many people are going to places of work. Compared to baseline of 5 weeks from 3 Jan '20 24% 54% 40% Restriction Date end_date Average Citymapper Average homeworking Work from home advised 17 Mar '20 21 Mar '20 57% 118% Schools, pubs closed 21 Mar '20 24 Mar '20 34% 119% UK enters first lockdown 24 Mar '20 10 May '20 10% 130% Some workers encouraged to return to work 10 May '20 01 Jun '20 15% 125% Schools open, small groups outside 01 Jun '20 15 Jun '20 19% 122% Non-essential businesses re-open 15 Jun '20 04 Jul '20 24% 120% Hospitality reopens 04 Jul '20 03 Aug '20 34% 115% Eat out to help out scheme begins 03 Aug '20 08 Sep '20 44% 113% Rule of 6 08 Sep '20 24 Sep '20 53% 111% 10pm Curfew 24 Sep '20 15 Oct '20 51% 112% Tier 2 (High alert) 15 Oct '20 05 Nov '20 49% 113% Second Lockdown 05 Nov '20 02 Dec '20 31% 118% Tier 2 (High alert) 02 Dec '20 19 Dec '20 45% 115% Tier 4 (Stay at home advised) 19 Dec '20 05 Jan '21 22% 124% Third Lockdown 05 Jan '21 08 Mar '21 22% 122% Roadmap 1 08 Mar '21 29 Mar '21 29% 118% Roadmap 2 29 Mar '21 12 Apr '21 36% 117% Roadmap 3 12 Apr '21 17 May '21 51% 113% Roadmap out of lockdown: Step 3 17 May '21 19 Jul '21 65% 109% Roadmap out of lockdown: Step 4 19 Jul '21 07 Nov '22 68% 107%

Indicators from the Opinions and Lifestyle Survey (OPN) measuring the impact of the Coronavirus pandemic on people and their plans over the Christmas period. Includes breakdowns by age, sex, region and country.

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

Abstract copyright UK Data Service and data collection copyright owner.

The English Longitudinal Study of Ageing (ELSA) Covid-19 study can be seen as a follow-up study based on the sample of the regular ELSA study (held under SN 5050). ELSA was launched in 2002 with the primary objective of exploring ageing in England through the operationalisation of a longitudinal design, where repeated measures are taken over time from the same sample of study participants, composed of people aged 50 or above.

After the beginning of the Coronavirus Disease 2019 (COVID-19) outbreak at the end of 2019, its classification as global pandemic by the World Health Organisation in March 2020 and the gradual escalation of protective measures in the UK, culminating with the enforcement of a nation-wide lockdown in late March, the ELSA research team identified the need to carry out a new ad-hoc study that measures the socio-economic effects/psychological impact of the lockdown on the aged 50+ population of England.

Further information can be found on the "http://www.elsa-project.ac.uk/covid-19" target="_blank" rel="noopener noreferrer"> ELSA COVID-19 Study webpage.

Acknowledgment statement:

The ELSA COVID-19 Substudy was funded through the Economic and Social Research Council via the UK Research and Innovation Covid-19 Rapid Response call. Funding has also been received from the National Institute of Aging in the US, and a consortium of UK government departments coordinated by the National Institute for Health Research.

Latest edition information

For the third edition (February 2022), revised data files for Waves 1 and 2, with corrected serial numbers (variable idauniq), were deposited. The documentation remains unchanged.

Special Licence version of the ELSA COVID-19 study

Additional variables covering interview week are available under SN 8918, subject to stringent Special Licence access conditions. Users should check whether the standard End User Licence version (this study, SN 8688), is sufficient for their needs before making an application for the Special Licence version.

Health conditions research with ELSA - June 2021

The ELSA Data team have found some issues with historical data measuring health conditions. If you are intending to do any analysis looking at the following health conditions, then please contact elsadata@natcen.ac.uk for advice on how you should approach your analysis. The affected conditions are: eye conditions (glaucoma; diabetic eye disease; macular degeneration; cataract), CVD conditions (high blood pressure; angina; heart attack; Congestive Heart Failure; heart murmur; abnormal heart rhythm; diabetes; stroke; high cholesterol; other heart trouble) and chronic health conditions (chronic lung disease; asthma; arthritis; osteoporosis; cancer; Parkinson's Disease; emotional, nervous or psychiatric problems; Alzheimer's Disease; dementia; malignant blood disorder; multiple sclerosis or motor neurone disease).

Topics covered in the ELSA COVID-19 study include:

• Demographics
• Mental health
• Financial security
• Covid-19-related health
• Employment and work
• Financial situation
• Volunteering and care
• Physical health and health behaviours
• Social connection isolation and technological inclusion
• Income, pensions and retirement

For a full table of topics and questions covered across all the ELSA waves, see the all-waves user guide in the main study (SN 5050) documentation.

Simple strategy for consented studies at the Nightingale hospital, London.

This data was generated as part of an 18 month ESRC funded project,as part of UKRI’s rapid response to COVID-19. The project examines how UK period poverty initiatives mitigated Covid-19 challenges in light of lockdown measures and closure of services, and how they continued to meet the needs of those experiencing period poverty across the UK. Applied social science research methodologies were utilised to collect and analyse data as this project, about the Covid-19 pandemic, was undertaken during an ongoing ‘real world’ pandemic. Data collection was divided into two phases. Phase 1 (October 2020 – February 2021) collected data from period poverty organisations in the UK using semi-structured interviews and an online survey to develop an in-depth understanding of how period poverty organisations were responding to and navigating the Covid-19 Pandemic. Having collected and analysed this data, phase 2 (June – September 2021) used an online survey to collect data from people experiencing period poverty in order to better understand their lived experiences during the pandemic. Our dataset comprises of phase 1 interview transcripts and online survey responses, and phase 2 online survey responses.

Period poverty refers not only to economic hardship with accessing period products, but also to a poverty of education, resources, rights and freedom from stigma for girls and menstruators (1). Since March 2020, and the introduction of lockdown/social distancing measures as a result of the Covid-19 pandemic, more than 1 of every 10 girls (aged 14-21) cannot afford period products and instead must use makeshift products (toilet roll, socks/other fabric, newspaper/paper). Nearly a quarter (22%) of those who can afford products struggle to access them, mostly because they cannot find them in the shops, or because their usual source/s is low on products/closed (2).

Community /non-profit initiatives face new challenges related to Covid-19 lockdown measures as they strive to continue to support those experiencing period poverty. Challenges include accessing stocks of period products, distribution of products given lockdown restrictions, availability of staff/volunteer assistance and the emergence of 'new' vulnerable groups. There is an urgent need to capture how initiatives are adapting to challenges, to continue to support the needs of those experiencing period poverty during the pandemic. This data is crucial to informing current practice, shaping policy, developing strategies within the ongoing crisis and any future crises, and ensuring women and girls' voices are centralised.

The project builds upon existing limited knowledge by providing insight into how UK based initiatives and projects are mitigating challenges linked to Covid-19, by examining how they are continuing to meet the needs of those experiencing period poverty and identifying any gaps in provision.

1. Montgomery P., et al., 2016. Menstruation and the Cycle of Poverty. PLoS ONE 11(12): e0166122.
2. Plan International UK, 2020. The State of Girls' Rights in the UK: Early insights into the impact of the coronavirus pandemic on girls. London: Plan International UK

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)

This preregistration documents an experimental intervention implemented in the second and third waves of a three-wave panel survey measuring public opinion about COVID-19 and the novel coronavirus in the United Kingdom (specifically Great Britain). (This study also includes observational survey data and data on web browsing behavior that will be analyzed as descriptive/exploratory rather than confirmatory.)

Respondents will be randomly assigned to read four articles adapted from U.S. and U.K. fact-checkers debunking four myths about COVID-19 and the novel coronavirus in wave 2 (independent random assignment; probability .5) and/or wave 3 (independent random assignment; probability .5). As a result, they will be exposed to the fact-check articles in wave 2, wave 3, both waves, or neither wave. Respondents who do not receive the fact-check articles in a given wave are instead shown four placebo articles.

This preregistration, which describes the analysis of our experiment, was written with the wave 1 baseline data (which did not include any experimental manipulations) in hand.

After the coronavirus (COVID-19) lockdown measures are lifted, the leaders of the eating and drinking out sector in the United Kingdom planned to increase hygiene and social distancing measures on the premises of their businesses. Some leaders also planned to reduce menu variety.

Abstract This paper aims to analyse the coordination and cooperation in Primary Health Care (PHC) measures adopted by the British government against the spread of the COVID-19. PHC is clearly part of the solution founded by governments across the world to fight against the spread of the virus. Data analysis was performed based on coordination, cooperation, and PHC literature crossed with documentary analysis of the situation reports released by the World Health Organisation and documents, guides, speeches and action plans on the official UK government website. The measures adopted by the United Kingdom were analysed in four periods, which helps to explain the courses of action during the pandemic: pre-first case (January 22- January 31, 2020), developing prevention measures (February 1 -February 29, 2020), first Action Plan (March 1- March 23, 2020) and lockdown (March 24-May 6, 2020). Despite the lack of consensus in essential matters such as Brexit, the nations in the United Kingdom are working together with a high level of cooperation and coordination in decision-making during the COVID-19 pandemic.

The Cancer Awareness Measure (CAM) was developed in 2007-8 to address the absence of a validated measure of general public awareness of cancer (Stubbings, S., Robb, K., Waller, J., Ramirez, A., Austoker, J., Macleod, U., Hion, S., and Wardle, J. (2009) 'Development of a measurement tool to assess public awareness of cancer', British Journal of Cancer, 101(2), S13-S17.).

The survey includes measures of awareness of signs and symptoms of cancer, cancer risk factors, age-related risk, screening programmes and potential barriers to seeing the GP. Since then, Cancer Research UK (CRUK) has significantly revised and updated the survey, including a wider range of questions and collecting data online instead of face-to-face. The CAM was also previously known as the National Awareness and Early Diagnosis Initiative Cancer Awareness Measure (NAEDI-CAM).