Experimental results of the pilot Office for National Statistics (ONS) online time-use study (collected 28 March to 26 April 2020 across Great Britain) compared with the 2014 to 2015 UK time-use study.

Exploring the social impacts on behaviours during the different lockdown periods of the coronavirus (COVID-19) pandemic in the UK. Data are from March 2020 to January 2021.

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.

A survey conducted in the United Kingdom in May 2020 found that the coronavirus pandemic and subsequent lockdown has had a generally negative effect on people's day-to-day feelings. On a possible rating of 1 to 10, four percent of respondents gave their feelings during the lockdown the most negative response possible, while seven percent selected the response '2', which is the second-most negative response.

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 a survey carried out in May 2020, 18 percent of Brits surveyed think that schools in the UK should re-open once new cases of coronavirus infections starts to go down, while 52 percent believe they should re-open under the same circumstances but close down if infections begin to rise again. There was very little support for any of the places to open as normal again on June 1, regardless of the situation, while 25 percent of respondents thought that pubs should not open again until a vaccine for coronavirus is found.

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 May 2020, a survey carried out in Great Britain found that approximately 65 percent of respondents had been worried about their future during the current coronavirus (COVID-19) crisis, while a further 61 percent said they had felt stressed or anxious recently during the lockdown. 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.

This dataset is published in relation to the preprint titled 'Impact of the COVID-19 Lockdown on the Electricity System of Great Britain: A Study on Energy Demand, Generation, Pricing and Grid Stability' which is accepted to the Energies journal. The aim of this study was to assess the effect of the March 2020 lockdown on the electricity system and market. This dataset contains all data used for the analyses and plots presented in the paper which uses Britain as a case study. The dataset primarily contains data from March 2020. However, it additionally has March 2019 data in some subfolders where it was used for comparison in the paper. This dataset is separated into 4 categories following the structure of the paper: (1) Demand, (2) Generation, (3) Forecast and Grid Stability, and (4) Pricing. Please see the README file for more information about the contents, resolution and structure of this dataset. To access any additional data, the Electricity Data Pipeline code presented in our paper can be employed.

Given the paramount impacts of COVID-19 on people’s lives in the capital of the UK, London, it was foreseeable that the city’s crime patterns would have undergone significant transformations, especially during lockdown periods. This study aims to testify the crime patterns’ changes in London, using data from March 2020 to March 2021 to explore the driving forces for such changes, and hence propose data-driven insights for policy makers and practitioners on London’s crime deduction and prevention potentiality in post-pandemic era. (1) Upon exploratory data analyses on the overall crime change patterns, an innovative BSTS model has been proposed by integrating restriction-level time series into the Bayesian structural time series (BSTS) model. This novel method allows the research to evaluate the varied effects of London’s three lockdown periods on local crimes among the regions of London. (2) Based on the predictive results from the BSTS modelling, three regression models were deployed to identify the driving forces for respective types of crime experiencing significant increases during lockdown periods. (3) The findings solidified research hypotheses on the distinct factors influencing London’s specific types of crime by period and by region. In light of the received evidence, insights on a modified policing allocation model and supporting the unemployed group was proposed in the aim of effectively mitigating the surges of crimes in London.

Tables to accompany the ‘Parenting in lockdown: Coronavirus and the effects on work-life balance article

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.

Objectives A key challenge for behaviour change is by-passing the influence of habits. Habits are easily triggered by contextual cues; hence context changes have been suggested to facilitate behaviour change (i.e., habit discontinuity). We examined the impact of a COVID-19 lockdown in England on habitual consumption of sugar-sweetened beverages (SSBs). The lockdown created a naturalistic context change because it removed typical SSB consumption situations (e.g., going out). We hypothesised that SSB consumption would be reduced during lockdown compared to before and after lockdown, especially in typical SSB drinking situations. Design In two surveys among the same participants (N = 211, N = 160; consuming SSBs at least once/week) we assessed the frequency of SSBs and water consumption occasions before (Time 1), during (Time 2) and after lockdown (Time 3), across typical SSB and water drinking situations. We also assessed daily amount consumed in each period, and perceived habitualness of drinking SSBs and water. Results As predicted, participants reported fewer occasions of drinking SSBs during lockdown compared to before and after, especially in typical SSB drinking situations. However, the daily amount of SSBs consumed increased during lockdown, compared to before and after. Exploratory analyses suggest that during lockdown, participants increased their SSB consump¬¬tion at home, especially if they had stronger perceived habitualness of SSB consumption. Conclusion These findings suggest that SSB consumption is easily transferred to other situations when the consumption context changes, especially for individuals with strong consumption habits. Habitual consumption may be hard to disrupt if the behaviour is rewarding.

This data was used to examine how changes to socializing and working during the UK's first national lockdown impacted ongoing thought patterns in daily life. We compared the prevalence of thought patterns (identified using Principal Components Analysis, PCA) between two independent real-world experience-sampling cohorts, collected before- and during lockdown. In both samples, young (18-35 y) and older (55+ y) participants completed experience-sampling measures five times daily for seven days. Dimension reduction (PCA) was applied to these data to identify common “patterns of thought”. Linear mixed modelling compared the prevalence of each thought pattern (i) before- and during lockdown, (ii) in different age groups and (iii) across different social and activity contexts. During lockdown, when people were alone, social thinking was reduced, but on the rare occasions when social interactions were possible, we observed a greater increase in social thinking than prelockdown. Furthermore, lockdown was associated with a reduction in future-directed problem-solving, but this thought pattern was reinstated when individuals engaged in work. Therefore, our study suggests that the lockdown led to significant changes in ongoing thought patterns in daily life and these changes were associated with changes to our daily routine that occurred during lockdown.

For full details of how this data was collected, see Mckeown et al (2021), PNAS, The impact of social isolation and changes in work patterns on ongoing thought during the first COVID-19 lockdown in the United Kingdom.

This is the README file for the scripts of the preprint "Self-Perceived Loneliness and Depression During the COVID-19 Pandemic: a Two-Wave Replication Study" by Carollo et al. (2022)

Access the pre-print here: https://ucl.scienceopen.com/document/read?vid=0769d88b-e572-48eb-9a71-23ea1d32cecf

Abstract: Background: The global COVID-19 pandemic has forced countries to impose strict lockdown restrictions and mandatory stay-at-home orders with varying impacts on individual’s health. Combining a data-driven machine learning paradigm and a statistical approach, our previous paper documented a U-shaped pattern in levels of self-perceived loneliness in both the UK and Greek populations during the first lockdown (17 April to 17 July 2020). The current paper aimed to test the robustness of these results by focusing on data from the first and second lockdown waves in the UK. Methods: We tested a) the impact of the chosen model on the identification of the most time-sensitive variable in the period spent in lockdown. Two new machine learning models - namely, support vector regressor (SVR) and multiple linear regressor (MLR) were adopted to identify the most time-sensitive variable in the UK dataset from wave 1 (n = 435). In the second part of the study, we tested b) whether the pattern of self-perceived loneliness found in the first UK national lockdown was generalizable to the second wave of UK lockdown (17 October 2020 to 31 January 2021). To do so, data from wave 2 of the UK lockdown (n = 263) was used to conduct a graphical and statistical inspection of the week-by-week distribution of self-perceived loneliness scores. Results: In both SVR and MLR models, depressive symptoms resulted to be the most time-sensitive variable during the lockdown period. Statistical analysis of depressive symptoms by week of lockdown resulted in a U-shaped pattern between week 3 to 7 of wave 1 of the UK national lockdown. Furthermore, despite the sample size by week in wave 2 was too small for having a meaningful statistical insight, a qualitative and descriptive approach was adopted and a graphical U-shaped distribution between week 3 and 9 of lockdown was observed. Conclusions: Consistent with past studies, study findings suggest that self-perceived loneliness and depressive symptoms may be two of the most relevant symptoms to address when imposing lockdown restrictions.

In particular, the folder includes the scripts for the pre-processing, training, and post-processing phases of the research.

==== PRE-PROCESSING WAVE 1 DATASET ==== - "01_preprocessingWave1.py": this file include the pre-processing of the variables of interest for wave 1 data; - "02_participantsexcludedWave1.py": this file include the script adopted to implement the exclusion criteria of the study for wave 1 data; - "03_countryselectionWave1.py": this file include the script to select the UK dataset for wave 1.

==== PRE-PROCESSING WAVE 2 DATASET ==== - "04_preprocessingWave1.py": this file include the pre-processing of the variables of interest for wave 2 data; - "05_participantsexcludedWave1.py": this file include the script adopted to implement the exclusion criteria of the study for wave 2 data; - "06_countryselectionWave1.py": this file include the script to select the UK dataset for wave 2.

==== TRAINING ==== - "07_MLR.py": this file includes the script to run the multiple regression model; - "08_SVM.py": this file includes the script to run the support vector regression model.

==== POST-PROCESSING: STATISTICAL ANALYSIS ==== - "09_KruskalWallisTests.py": this file includes the script to run the multipair and the pairwise Kruskal-Wallis tests.

Provisional counts of the number of deaths and annualised age-standardised mortality rates involving the coronavirus (COVID-19) by major occupations, where the infection may have been acquired either before or during the period of lockdown. The deaths have been registered in England and Wales. Figures are provided for males and females.

This statistic illustrates the consumption growth in e-commerce sales during the coronavirus lockdown in Spain in 2020, broken down by category. Fashion and footwear sales experienced a fall in sales of about 70 percent as of March 13. However, by the end of the the lockdown in May, the industry registered a significant increase in sales of about 50 percent.

The database contains the survey on the changes of gender time allocation during two waves of the coronavirus lockdown (self-isolative restrictions) in Russia. Self-isolation included shift to remote work and study, the closure of childcare facilities, restrictions of mobility, etc.

Sample information

The survey was conducted on Yandex.Survey platform. The first wave was conducted on 22-23 th of May, 2020, after 2 months of the beginning of first lockdown. The second wave took place on 17-19th of November, 2020 after 1 month of the second lockdown’start.

Data was collected via online service Yandex.Survey. The platform offers a service for conducting an online survey among 50 million users of the Yandex advertising network with the ability to make a random sample, including a sample by demographic, geographic and some socio-economic characteristics.

The respondents were women of predominantly working/reproductive age (15-55) from Russia. 1411 women took part in the first wave and 1408 in the second. After cleaning data and removing outliers 2795 respondents left.

The coincidence of the distributions with the general population in terms of the main parameters (age, size of the settlement, employment, household composition) is satisfactory. The observed (insignificant) deviations are as follows: the proportion of women aged 30-43, living in cities with a population over one million has increased; decreased - at the age of 50-54 years, living in settlements with a population of less than 100 thousand people working in agriculture.

The female respondents were asked if they spend more or less time household chores and care, including: cleaning, cooking, laundry, shopping, management, child care, other care or nothing. If a woman marked, that she is living with a partner during the lockdown, she was also asked if her partner spends more or less time on each chore.

The survey also includes questions concerning the occupation type (work, work and study, study, child care leave, doesn’t work), if a woman works (or works and studies), how the lockdown effected on her job: shift to remote work, fired, paid leave, unpaid leave, no income on restrictions, continues in-person work, and if a woman lives with a partner the same question was asked considering his work on the lockdown. Further, occupational features were divided into three: income (or husband’s income) means that a woman (or her partner) has her income on the lockdown which includes remote work, in person work, paid leave; gotowork means a woman (in her partner’s case – husb_gotowork) continues in person work; and distant if a woman is working online (husb_distant for her partner). Further, we asked whether a woman has an experience of remote work: no, and it is impossible, no, but it is possible, yes. We also asked about the size and type of her employer (small, medium, large firm or state firm).

The next set of questions considers who a woman is living with on self isolation: alone, children, partner, parents, parents-in-law, others. At last, we asked respondents age, number of children and the age of the youngest child (if the number of children >0).

The database’ structure

Survey's wave variables

Social and demographic variables

age of female respondent

size of the city

number of children

the age of the youngest child

age at last birth

woman lives with her husband

woman lives with children

woman lives with children over 18 years old

woman lives with her parents

woman lives with her husband's parents

woman lives alone

woman lives with someone else

type of activity

how the lockdown effected female occupation

field of employment

type of enterprise where woman works (or does not)

there is wife's income in household

how the lockdown effected her husband's occupation

there is husband's income in household

woman's work experience at a remote location

woman has remote work in the period of lockdown

her husband has remote work in the period of lockdown

her husband has out of home work in the period of lockdown

woman has out of home work in the period of lockdown

her husband is fired or doesn't have income temporarily because of the lockdown

her husband was fired because of the lockdown

Time use variables: the changes in lockdown

WOMAN MORE

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

WOMAN LESS

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

HER HUSBAND MORE

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

HER HUSBAND LESS

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

TOGETHER MORE

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

TOGETHER LESS

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

INSTEAD MORE

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

INSTEAD LESS

childcare

care

cleaning

cooking

laundry

shopping

management

nothing

There are English and Russian versions of variables’ description.

During exploratory data analysis we introduced features instead or together. These new features are restricted to answers of women who live with partners. Whether a woman marks that she spends less(more) time on the chore and her husband spends more(less) time on that exact type of chore, that means he does it instead of his wife. Whether both a woman and her partner spend more (less) time one the chore, it means they do it together.

The variable “type of enterprise” was built on the criteria of credibility and stability during the corona-crisis from a small to a state firm (small, medium, large, state firm). Small and medium enterprises were hit the most by the pandemic (http://doklad.ombudsmanbiz.ru/2020/7.pdf), whether large and especially state firms had more resources to maintain employment and payments.

The survey aims to know the impact of the confinement situation on the population of the city of Madrid after the declaration of the state of alarm due to the COVID-19 pandemic. The study is aimed at households in Madrid according to classification by type of household, and it collects information regarding the composition of the home, description and equipment of the house, consequences of the crisis in relation to economic activity, occupation, income and health, as well as issues related to behavior during confinement and the psychological consequences of it. This dataset provides the microdata from the survey conducted for the study. Further information can be found in the data sheet, questionnaire and study results report .

The coronavirus (COVID-19) pandemic and the lockdowns during this period had an impact on the attitudes of prospective home buyers in the United Kingdom (UK) in different ways. On one hand, there was a large percentage of prospective home buyers of 63 percent that said COVID-19 motivated them to buy homes between March 2020 and March 2021.
However, concerns of financial security and the home buying process being harder were also registered at high rates. 71 percent of prospective home buyers were worried about their financial security, 68 percent reported that lockdowns made it harder to buy homes. This shows that while the motivation and interest in buying homes was large, but the conditions of lockdown and the financial impact of the coronavirus (COVID-19) pandemic were a big barrier towards making purchases.

Reference data to accompany an article on the impact of caring responsibilities during the coronavirus (COVID-19) lockdown