Numbers and characteristics of those considered as potential “key workers” in the response to coronavirus (COVID-19), UK. Labour Force Survey and Annual Population Survey.

New insights on the characteristics of non-British nationals and non-UK-born in the workforce between 2017 and 2019, including those who could be considered as key workers in the response to the coronavirus (COVID-19) pandemic.

Given the outbreak of the coronavirus, SARS-CoV-2 (COVID-19), pandemic during March 2020, lockdown measures taken by governments have forced many families, especially those who have children, to re-arrange domestic and market work division. In this study, I investigate the factors associated with partnered and employed individuals’ involvement with housework during the COVID-19 lockdown in the United Kingdom. Drawing evidence from the first wave of the Covid-19 Survey from the Five National Longitudinal Studies dataset with using OLS regressions, this study found that daily working hours, socioeconomic status, and partner’s key worker status are important indicators of daily time spent on housework. Furthermore, interaction analysis showed that women living with a key worker partner not only did more housework than women whose partner was working in a regular job, but they also did more housework than men living with a key worker partner during the lockdown. Policy implications of regulating maximum daily working hours and key worker status are discussed in the context of re-arranging paid and unpaid work between couples during the first lockdown in the United Kingdom.

Citation: Sönmez, I ̇brahim. 2021. A Missed Opportunity for Men? Partnered and Employed Individuals’ Involvement with Housework during the COVID-19 Lockdown in the UK. SocialSciences10: 135. https:// doi.org/10.3390/socsci10040135

COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2) data is required by NHS Digital to support COVID-19 requests for linkage, analysis and dissemination to other organisations. These requests are often urgent and in support of direct care and service monitoring, planning and research. These are all functions that NHS Digital have been asked to deliver as a national resource in response to COVID-19, through the recent direction from the SoS.

Antigen test results relate to subjects who have had swab testing in the community at drive through test centres, walk in centres, home kits returned by posts, care homes, prisons etc.

The dataset is composed of:

• Patient identity and contact details

• Testing centre and laboratory details

• Test results • Test kit types (manufacturer)

The data cover the UK and is collected under SoS Covid Direction under s254 of the HSCA 2012 and s255 requests from devolved administrations for Scotland, Northern Ireland and Wales. This is an expansion of the original scope which only included data for welsh patients tested in other parts of the UK.

Data is currently available for dissemination through the NHS Digital DARS service for England. If your extract is to include data from the devolved administrations their approval will also be required.

Timescales for dissemination can be found under 'Our Service Levels' at the following link: https://digital.nhs.uk/services/data-access-request-service-dars/data-access-request-service-dars-process

Datasets and interview transcripts from a Q-methodology study with 54 individuals with a range of different experiences of, and expertise in relation to, the COVID-19 pandemic. Participants included, for example, seldom-heard and low-income individuals, health practitioners, health and social policy academics and relevant policy makers, key workers, furloughed staff, and individuals directed to shield by the NHS. Participants from England and Scotland rank ordered 60 statements onto a quasi-normal shaped grid according to their point of view in 2021. The dataset includes data from the Q sorts (n=54), socio-demographic survey (n=54) and post-sort qualitative interviews (n=53).

Amongst those hit hardest by COVID-19, and the associated social and economic measures put in place to combat it, will be people in low-income settings, and, within that group, those in hard-to-reach groups continually threatened by financial exclusion. People in such situations already live in precarious financial situations which could be amongst the most vulnerable to measures such as social distancing and self-isolation. A Q study was conducted, with a focus on perceptions of COVID-19 and the societal responses to which study participants have been subjected. Q methodology is an established approach to study subjective opinion and beliefs. The views of seldom-heard individuals were complemented and compared with those of a wide range of other participants, for example, health practitioners, health and social policy academics and relevant policy makers, key workers, furloughed staff, and individuals directed to shield by the NHS. We purposively selected 54 individuals with a range of different experiences of, and expertise in relation to, the COVID-19 pandemic. Participants rank ordered 60 statements onto a quasi-normal shaped grid according to their point of view. These data will be useful in enhancing the acceptability of, adherence to and effective delivery of evidence-based strategies for future prevention and containment.

The policy timeline was developed as a dataset for the Freelancers in the Dark Project by Ali FitzGibbon and Laura Harris with support from Alexandra Young. Using public statements, media coverage and online reporting, it marks dates of relevance to the experience of theatre freelancers between January 2020 (when certain early reporting of COVID-19 began to emerge) and March 2022, the 2 year anniversary of the UK outbreak and lockdowns and end of the research project. The timeline was published using the open-source tool developed by knight lab. An early version was published in June 2021 and contributions invited. The final version was completed on 28 June 2022. Events are labelled according to their place of relevance: UK, England, Wales, Scotland, Northern Ireland or Global. The raw dataset (in MS Excel) can be filtered to support searches for particular changes to guidance, key campaigns from freelancers, trade unions, etc.

COVID-19 threatens the performing arts; closures of theatres and outlawing of public gatherings have proven financially devastating to the industry across the United Kingdom and, indeed, the world. The pandemic has sparked a wide range of industry-led strategies designed to alleviate financial consequences and improve audience capture amidst social distancing. COVID-19 has affected all levels of the sector but poses an existential threat to freelancers--Independent Arts Workers (IAWs)--who make up 60% of industry workforce in the UK (EU Labour Force Survey 2017). The crisis has put a spotlight on the vulnerable working conditions, economic sustainability, mental wellbeing, and community support networks of IAWs. IAWs are often overlooked by the industry and researchers, however it is their very precarity that makes them pioneers of adaptability responsible for key innovation within the sector. IAWs may prove essential for the industry's regrowth post-COVID-19. An investigation is necessary into the impact of COVID-19 on IAWs and the wide-ranging creative solutions developing within the industry to overcome them.

There has been increasing pressure to gather 'robust, real-time data' to investigate the financial, cultural, and social potential long-term consequences of COVID-19 on the UK theatre industry. The impact of the pandemic on IAWs is particularly complex and wide-ranging. A TRG Arts survey stated that 60% of IAWs predict their income will 'more than halve in 2020' while 50% have had 100% of their work cancelled. Industry researchers from TRG Arts and Theatres Trust have launched investigations examining the financial impact of COVID-19 on commercial venues and National Portfolio Organisations, but there has been insufficient research into the consequences for IAWs (eg. actors, directors, producers, writers, theatre makers, technicians) and the smaller SMEs beyond income loss and project cancellation data. In May 2020, Vicky Featherstone of the Royal Court Theatre, stated the importance of support for the 'massive freelance and self-employed workforce' she believed has been 'taken for granted' by the industry. Our study fills this gap by capturing and analysing not only the economic impact, but the social and cultural transformations caused by COVID-19 by and for IAWs. We will compare regional responses across England, Wales, Northern Ireland and Scotland as well as variations across racial and socio-economic groups. Our aims are to document and investigate the impact of COVID-19 on IAWs, identify inequalities in the sector, investigate changes in the type of work produced post-COVID-19, and help develop strategies for how the sector can move forward from this crisis. We will investigate connections between the financial consequences of COVID-19 and creative strategies for industry survival including social support networks, communication initiatives between arts venues and IAWs, and the development of mixed-media work in the wake of the pandemic. Our study scrutinizes the economic, cultural, and social impact of COVID-19 on IAWs and the organisations that serve them with the aim of informing strategies for sector recovery.

The data in this dataset relates to the status of persons employed in Wales, breaking the total down into those who are self-employed or employees and those who are in full time or part time. As the data come from a survey, the results are sample-based estimates and therefore subject to differing degrees of sampling variability, i.e. the true value for any measure lies in a differing range about the estimated value. This range or sampling variability increases as the detail in the data increases, for example individual local authority data are subject to higher variability than Wales data. LFS data is collected throughout the year, and is available from the ONS in a variety of ways. This dataset contains the latest annual results, as referred to in the second bullet below. Key data on the labour market is updated every month showing the position for the latest three months, for the UK and each of the UK countries and English regions. Note these data are seasonally adjusted and also that no sub-regional (i.e. local authority) data are published by the ONS to a monthly timetable. Annual results covering the periods described earlier are also available from the ONS, providing more detailed data from the LFS, including data for sub-Wales geographies. These annual datasets use results from the samples for the quarterly surveys used for the key series, together with results from additional persons sampled to provide a more robust (boosted) dataset, with estimates subject to much lower sampling variability. Quarterly results are also available, again providing more detailed data from the LFS than the key series, including data for sub-Wales geographies. However, although these data are available earlier than the data taken from the annual datasets, data for sub-Wales geographies taken from the quarterly datasets are no longer included on StatsWales as the results are far less robust than those which come from the annual datasets. Note that as data are taken from the ANNUAL Labour Force Survey datasets they do NOT exactly match annual averages derived from the 4 QUARTERLY datasets in the relevant 12 month period covered due to differences in the sampling structure.

Pay level risk faced by different occupations, based on ability to work from home and whether or not they are a key worker, UK, 2020. Annual Survey of Hours and Earnings.

COVID-19 Key Worker Testing Results data is required by NHS Digital to support COVID-19 requests for linkage, analysis and dissemination to other organisations who require the data in a timely manner.

Estimates of the risk of hospital admission for coronavirus (COVID-19) and death involving COVID-19 by vaccination status, overall and by age group, using anonymised linked data from Census 2021. Experimental Statistics.

Outcome definitions

For this analysis, we define a death as involving COVID-19 if either of the ICD-10 codes U07.1 (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified) is mentioned on the death certificate. Information on cause of death coding is available in the User Guide to Mortality Statistics. We use date of occurrance rather than date of registration to give the date of the death.

We define COVID-109 hospitalisation as an inpatient episode in Hospital Episode Statistics where the primary diagnosis was COVID-19, identified by the ICD-19 codes (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified). Where an individual had experienced more than one COVID-19 hospitalisation, the earliest that occurred within the study period was used. We define the date of COVID-19 hospitalisation as the start of the hospital episode.

ICD-10 code

U07.1 :

COVID-19, virus identified

U07.2:

COVID-19, virus not identified

Vaccination status is defined by the dose and the time since the last dose received

Unvaccinated:

no vaccination to less than 21 days post first dose

First dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post first dose or less than 21 days post second dose

First dose 3+ months:

more than or equal to 91 days post first dose to less than 21 days post second dose

Second dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post second dose or less than 21 days post third dose

Second dose 3-6 months:

more than or equal to 91 days post second dose to earliest of less than 182 days post second dose or less than 21 days post third dose

Second dose 6+ months:

more than or equal to 182 days post second dose to less than 21 days post third dose

Third dose 21 days to 3 months:

more than or equal to 21 days post third dose to less than 91 days post third dose

Third dose 3+ months:

more than or equal to 91 days post third dose

Model adjustments

Three sets of model adjustments were used

Age adjusted:

age (as a natural spline)

Age, socio-demographics adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status)

Fully adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status), plus health-related characteristics (disability, self-reported health, care home residency, number of QCovid comorbidities (grouped), BMI category, frailty flag and hospitalisation within the last 21 days.

Age

Age in years is defined on the Census day 2021 (21 March 2021). Age is included in the model as a natural spline with boundary knots at the 10th and 90th centiles and internal knots at the 25th, 50th and 75th centiles. The positions of the knots are calculated separately for the overall model and for each age group for the stratified model.

Second Generation Surveillance System (SGSS) data contains SARS-CoV-2 testing (swab samples, PCR test method) offered to those in hospital and NHS key workers (i.e. Pillar 1) and includes positive tests results only.

Second Generation Surveillance System (SGSS) is the national laboratory reporting system used in England to capture routine laboratory data on infectious diseases and antimicrobial resistance. The SARS-CoV-2 testing started in UK laboratories on 24/02/2020, with the SGSS data reflecting testing (swab samples, PCR test method) offered to those in hospital and NHS key workers (i.e. Pillar 1). The CPRD-SGSS linked data currently contain positive tests results only.

A different perspective on wearing face masks and Personal Protective Equipment (PPE) in public places or at work.

Refugees are forced to leave their homeland due to threats to their lives. Therefore, they are always anxious. This refugee, who is also a key worker, feels good about wearing a mask. It’s not just a protection from the virus but from other possible threats – even threatening looks or aggression because of the colour of your skin. When the world is in lockdown, it’s the safest moment to go out for refugees and asylum seekers.

This material is part of the Covid Chronicles from the Margins project, funded by The Open University and the International Institute of Social Studies in the Hague. The project aims to highlight the impact of the pandemic on refugees, asylum seekers and undocumented migrants.

This item can also be found on our website.

Summary for Local Authorities: Green Belt Policy in ScotlandPolicy Framework:Green belts are designated in National Planning Framework 4 (NPF4) to manage urban expansion, support regeneration, and protect settlement identity.Local Development Plans (LDPs) determine where green belts are necessary and define their boundaries.Key Purposes of Green Belts:Direct Development – Encourage sustainable growth in suitable areas.Protect Settlement Character – Maintain the landscape and identity of towns and cities.Enhance Access to Open Space – Support public amenity and environmental benefits.Development Restrictions & Exceptions:Generally, development is not permitted in green belts.Exceptions include: Agriculture, forestry, and horticulture. Essential housing for key rural workers. Outdoor recreation, tourism, and leisure activities. Infrastructure (where essential) and cemeteries. Developments must demonstrate necessity, minimise impact, and align with green belt purposes.

Set out below is the information the council is required to publish under the Trade Union (Facility Time Publication Requirements) Regulations 2017 for its central and education (maintained schools) functions.The Council recognises 9 trade unions with which we continue to work in partnership to deliver services and outcomes to support the community of Leicester. These trade unions support a central workforce of nearly 6000 employees and an education workforce of a similar number, acting as the collective voice of our individual employees to inform key decision making within the Council.We continue to support the trade unions in having an active presence in the workplace through releasing representatives to undertake trade union duties and activities. It is these representatives who make a real contribution, working alongside our managers to support employees to deliver valuable outcomes for the people of Leicester.Our joint initiative to reduce absence has seen absence rates continue to drop in the last 12 months, contributing towards savings made by the Council.