Objectives: To test whether public knowledge and confidence in one's understanding of the local restrictions, motivation to adhere to local restrictions, and self-reported behaviour (going out for exercise, to work, socially) differed according to tier level.Study design: Cross-sectional, nationally representative, online survey of 1728 participants living in England (data collection: 26 to 28 October 2020).Methods: We conducted logistic regression analyses to investigate whether knowledge of restrictions, confidence in knowledge of restrictions, motivation to adhere to restrictions, and self-reported behaviour were associated with personal characteristics and tier.Results: Between 81% (tier 2) and 89% (tier 3) of participants correctly identified which tier they lived in. Knowledge of specific restrictions was variable. 73% were confident that they understood which tier was in place in their local area, whereas 71% were confident they understood the guidance in their local area. Confidence was associated with being older and living in a less deprived area. 73% were motivated to adhere to restrictions in their local area. Motivation was associated with being female and older. People living in tiers with greater restrictions were less likely to report going out to meet people from another household socially; reported rates of going out for exercise and for work did not differ.Conclusions: Although recognition of local tier level was high, knowledge of specific guidance for tiers was variable. There was some indication that nuanced guidance (e.g. behaviour allowed in some settings but not others) was more poorly understood than guidance which was absolute (i.e. behaviour is either allowed or not allowed).

Estimates of the prevalence of self-reported long COVID and associated activity limitation, using UK Coronavirus (COVID-19) Infection Survey data. Experimental Statistics.

According to a survey carried out in the UK in November 2020, 54 percent of respondents supported strict coronavirus measures remaining in place for Christmas, while 33 percent felt restrictions should be eased for a few days for Christmas even if that means stricter rules are needed to be reapplied in January. The highest support for restrictions to remain strict over the festive period is found in the older age groups.

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.

COVID-19 is a infectious Disease which has infected more than 500 people in UK and many more people world-wide.

Acknowledgements Sincere thanks to Public Health England and Local governments. Source of Data: UK Government and Public Health UK

****Notes on the methodology**** This service shows case numbers as reported to Public Health England (PHE), matched to Administrative Geography Codes from the Office of National Statistics. Cases include people who have recovered.

Events are time-stamped on the date that PHE was informed of the new case or death.

The map shows circles that grow or shrink in line with the number of cases in that geographic area.

Data from Scotland, Wales and Northern Ireland is represented on the charts, total indicators and on the country level map layer.

Contains Ordnance Survey data © Crown copyright and database right 2020. Contains National Statistics data © Crown copyright and database right 2020.

Terms of Use No special restrictions or limitations on using the item’s content have been provided.

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.

National and local restrictions and policies affecting London, by date. Supplied as an experimental dataset to provide context for analysis of other social or economic datasets, for instance, footfall and spend data timeseries. Information was mainly gathered from government announcements published by the Prime Minister's Office. The restrictions and policies included are: School closures - complete closures only Pub closures - excluding pubs that serve food Shop closures - non-essential Eating Places closures - including pubs that serve food Stay at home orders Household mixing indoors banned Working from home encouraged Rule of 6 indoors 10pm curfew on hospitality Eat Out to Help Out scheme

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%

Information from a new module of questions included in the Telephone-operated Crime Survey for England and Wales (TCSEW) around perceptions of crime, the police and anti-social behaviour during the coronavirus (COVID-19) pandemic, feelings of safety and experiences of harassment. Data on children’s online activity are also presented. These tables are no longer produced.

According to a survey carried in Great Britain in April 2020, ** percent of Brits thought that the government should have reopening schools as the top priority when it starts to gradually loosen restrictions, while ** percent want the government to encourage non-essential workers to go back to work as the top priority. 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.

Data on how people in the UK spent their time in March 2022 compared with before the coronavirus pandemic, using Time-use survey data from 2022 and Time-use study data from 2014 to 2015. These data also contains estimates on how people spent their time throughout the pandemic and estimates by different demographics, including by sex, ethnicity, income and disability status.

Local authorities have received and distributed funding to support small and medium businesses in England during coronavirus. The datasets cover schemes managed by local authorities: Additional Restrictions Support Grant (ARG) Restart Grant - closed June 2021 Local Restrictions Support Grants (LRSG) and Christmas support payments - closed 2021 Small Business Grants Fund (SBGF) - closed August 2020 Retail, Hospitality and Leisure Business Grants Fund (RHLGF) - closed August 2020 Local Authority Discretionary Grants Fund (LADGF) - closed August 2020 The spreadsheets show the total amount of money that each local authority in England: received from central government distributed to SMEs 20 December 2021 update We have published the latest estimates by local authorities for payments made under this grant programme: Additional Restrictions Grants (up to and including 28 November 2021) The number of grants paid out is not necessarily the same as the number of businesses paid. The data has not received full verification.

Monthly figures on the attitudes of UK and overseas residents arriving in and departing from the UK towards social distancing, mask wearing, and coronavirus (COVID-19) restrictions and the proportion who had been vaccinated, using unweighted results from the International Passenger Survey for the period covering February 2021 to March 2022 and the Civil Aviation Authority’s Departing Passengers Survey for the period covering June 2021 to December 2021 (Experimental Statistics).

This is an indicator designed to accompany the Summary Hospital-level Mortality Indicator (SHMI). 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. This indicator shows the number of provider spells which are coded as COVID-19, and therefore excluded from the SHMI, as a percentage of all provider spells in the SHMI (prior to the exclusion). This indicator is being published as an experimental statistic. 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. Please note that there has been a fall in the number of spells for most trusts between this publication and the previous SHMI publication, ranging from 0 per cent to 5 per cent. This is due to COVID-19 impacting on activity from March 2020 onwards and appears to be an accurate reflection of hospital activity rather than a case of missing data. 2. The data for St Helens and Knowsley Teaching Hospitals NHS Trust (trust code RBN) has incomplete information on secondary conditions that the patients suffers from, and this will have affected the calculation of this indicator. Values for this trust should therefore be interpreted with caution. Please note, this issue was not identified until after this publication was initially released on 13th May 2021. Data quality notices were later added to this publication in July 2021. 3. 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 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. 4. There is a shortfall in the number of records for Mid Cheshire Hospitals NHS Foundation Trust (trust code RBT), meaning that values for this trust are based on incomplete data and should therefore be interpreted with caution. 5. We recommend that values for Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1) are interpreted with caution as there is a possible shortfall in the number of records which is currently under investigation. 6. On 1 April 2021 Western Sussex Hospitals NHS Foundation Trust (trust code RYR) merged with Brighton and Sussex University Hospitals NHS Trust (trust code RXH). The new trust is called University Hospitals Sussex NHS Foundation Trust (trust code RYR). However, as we received notification of this change after data processing for this publication began, separate indicator values have been produced for this publication. The next publication in this series will reflect the updated organisation structure. 7. 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.

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: MRC National Survey of Health and Development, 2020: Special Licence Access contains the data from Waves 1-3 for the 1946 birth cohort study.

The Wave 1 Survey was programmed and administered by CLS/LHA using Qualtrics. The Wave 2 and Wave 3 Survey was programmed and administered by Kantar Public.

Further information may be found on the https://cls.ucl.ac.uk/covid-19-survey/"> CLS COVID-19 survey website.

Latest edition information

For the third edition (June 2021), the Wave 3 data have been added to the study, and the Wave 2 data file replaced with a new version. The documentation has also been updated.

ObjectiveSince the outbreak of COVID-19, public health and social measures to contain its transmission (e.g., social distancing and lockdowns) have dramatically changed people's lives in rural and urban areas globally. To facilitate future management of the pandemic, it is important to understand how different socio-demographic groups adhere to such demands. This study aims to evaluate the influences of restriction policies on human mobility variations associated with socio-demographic groups in England, UK.MethodsUsing mobile phone global positioning system (GPS) trajectory data, we measured variations in human mobility across socio-demographic groups during different restriction periods from Oct 14, 2020 to Sep 15, 2021. The six restriction periods which varied in degree of mobility restriction policies, denoted as “Three-tier Restriction,” “Second National Lockdown,” “Four-tier Restriction,” “Third National Lockdown,” “Steps out of Lockdown,” and “Post-restriction,” respectively. Individual human mobility was measured with respect to the time period people stayed at home, visited places outside the home, and traveled long distances. We compared these indicators across the six restriction periods and across socio-demographic groups.ResultsAll human mobility indicators significantly differed across the six restriction periods, and the influences of restriction policies on individual mobility behaviors are correlated with socio-demographic groups. In particular, influences relating to mobility behaviors are stronger in younger and low-income groups in the second and third national lockdowns.ConclusionsThis study enhances our understanding of the influences of COVID-19 pandemic restriction policies on human mobility behaviors within different social groups in England. The findings can be usefully extended to support policy-making by investigating human mobility and differences in policy effects across not only age and income groups, but also across geographical regions.

Objectives: This study investigated perceived loneliness, anxiety, and depression among young adults in the UK across five timepoints: pre-pandemic (December 2019), two coronavirus disease (COVID-19) lockdowns (March–June 2020, January–April 2021), and two post-lockdown phases (November–December 2021, May 2022). It aimed to assess mental health resilience, defined as a return to baseline levels post-lockdown, and identify critical timepoints where loneliness predicted mental health outcomes.Methods: A total of 158 participants (aged 18–82, predominantly under 25) completed online questionnaires measuring mental health (Patient Health Questionnaire-8 (PHQ-8); General Anxiety Disorder-7 (GAD-7)) and loneliness (DeJong Gierveld Loneliness Scale) at two data collection points, under a cross-sectional design. Retrospective data were collected for pre-pandemic and lockdown periods, while prospective data were gathered post-lockdown. Linear mixed models and regression analyses were used to examine changes in mental health and loneliness over time and to identify predictive relationships.Results: Loneliness and mental health significantly deteriorated during lockdowns, with depression and anxiety scores worsening from pre-pandemic levels. Partial recovery was observed post-lockdown, but scores remained above baseline. Loneliness emerged as a key predictor of mental health outcomes, particularly during post-lockdown phases. The immediate post-lockdown period was identified as a critical window for interventions.Conclusions: COVID-19 lockdowns were associated with heightened loneliness and mental health challenges, with sustained effects post-lockdown. Timely interventions targeting loneliness, especially after periods of social restriction, are essential to mitigate long-term mental health impacts and inform future responses to global crises.

Objectives: To study the prevalence of COVID-19 health protective behaviours before and after rules eased in England on the 19th July 2021.Design: Observational study pre (12th-18th July) and post (26th July-1st August) 19th July, and a cross-sectional online survey (26th to 27th July).Setting: Observations occurred in supermarkets (n = 10), train stations (n = 10), bus stops (n = 10), a coach station (n = 1) and a London Underground station (n = 1). The survey recruited a nationally representative sample.Participants: All adults entering the observed locations during a one-hour period (n = 3819 pre- and n = 2948 post-19th July). In the online survey, 1472 respondents reported having been shopping for groceries/visited a pharmacy and 566 reported having used public transport or having been in a taxi/minicab in the last week.Main outcome measures: We observed whether people wore a face covering, maintained distance from others and cleaned their hands. We investigated self-reports of wearing a face covering while in shops or using public transport.Results: In most locations observed, the proportion of people wearing face coverings, cleaning the hands and maintaining physical distance declined post 19th July. Pre 19th July, 70.2% (95% CI 68.7 to 71.7%) of people were observed to be wearing a face covering versus 55.8% (54.2 to 57.9%) post 19th July. Equivalent rates for physical distancing were 40.9% (39.0 to 42.8%) versus 29.5% (27.4 to 31.7%), and for hand hygiene were 4.4% (3.8 to 5.1%) versus 3.9% (3.2 to 4.6%). Self-reports of “always” wearing face coverings were broadly similar to observed rates.Conclusions: Adherence to protective behaviours was sub-optimal and declined during the relaxation of restrictions, despite appeals to exercise caution. Self-reports of “always” wearing a face covering in specific locations appear valid.

IntroductionThis study investigated older adults' emotional and social experiences of physical activity and exercise during the first Covid-19 lockdown in England.MethodsParticipants were 24 older adults (M = 74 years, SD = 5.0) either physically active or inactive before lockdown. Semi-structured interviews were conducted at the start of the pandemic in England, and when restrictions were lifted eight weeks later.ResultsTemplate analysis revealed three main themes: a Sense of Purpose for Being Physically Active, Routes for Engagement, and Inactive by Force? with different sub-themes for active and inactive participants. The lockdown restrictions emphasised the need to keep physically active in both active and inactive participants, but they perceived barriers differently. Both active and inactive participants found a renewed sense of purpose in walking outdoors for exercise when restrictions eased, enhancing their physical and mental well-being.DiscussionTo reduce barriers and emphasise that exercise is for all ages and all levels of mobility, multi-modal recommendations are presented for educating, promoting, supporting, and enabling older adults to engage in physical activity and exercise.