Findings from the Coronavirus (COVID-19) Infection Survey for England.

In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. The number of cases in the UK increased significantly at the end of 2021. On January 13, 2023, the number of confirmed cases in the UK amounted to 24,243,393. COVID deaths among highest in Europe There were 202,157 confirmed coronavirus deaths in the UK as of January 13, 2023. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Current infection rate in Europe The current infection rate in the UK was 50 cases per 100,000 population in the last seven days as of January 16. San Marino had the highest seven day rate of infections in Europe at 336.

As of July 30, 2020, there had been more confirmed cases of coronavirus (COVID-19) among women in England compared to men. The data shows that there are few confirmed cases among children, while there have been approximately nine thousand confirmed cases for both men and women aged 80 to 84 years.

As of July 30, there have been 302,301 confirmed coronavirus cases in the UK, and the regional breakdown of cases can be found here. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Headline estimates for England, Wales, Northern Ireland and Scotland. 

In-depth analysis of Winter Coronavirus (COVID-19) Infection Study data looking at trends in self-reported symptoms of coronavirus (COVID-19), including ongoing symptoms and associated risk factors.

The purpose of this dataset is to understand the prevalence of COVID-19 in the UK population, including swab results, antibody tests and demographic information. COVID-19 Infection Survey households have been linked, where a match can be found, to VOA and EPC data to provide additional information on property attributes.

Self-reported COVID-19 infections and other respiratory illnesses, including associated symptoms and health outcomes. Joint study with the UK Health Security Agency. These are official statistics in development.

The number of monthly active and withdrawn participants, and attrition rates, for the Coronavirus (COVID-19) Infection Survey from December 2020 to the end of July 2022.

Cumulative coronavirus (COVID-19) infections percentage of the population of England: experimental and sum-total time series.

Modelled estimates of the proportion of the workforce self-isolating because of coronavirus (COVID-19) by work sector and modelled estimates of the proportion of the working age population (regardless of employment status) self-isolating because of COVID-19 by country.

Estimates from the Schools Infection Survey of pupils testing positive for SARS-CoV-2 antibodies. Including breakdowns by age, sex and region where possible.

Revised vaccination data, by UK country and age, from the Coronavirus (COVID-19) Infection Survey, December 2020 to November 2021.

Potential impact of the coronavirus (COVID-19) pandemic on young people and schools, including analysis of physical activity and eating behaviours, and breakdowns by age and sex where possible. Indicators from the Schools Infection Survey.

The likelihood of new-onset, self-reported long COVID after a second coronavirus (COVID-19) infection compared with a first infection, using data from the COVID-19 Infection Survey. Experimental Statistics.

Indicators from the Schools Infection Survey to understand the impact of the coronavirus (COVID-19) pandemic on young people and schools. Including antibody data, questionnaire analysis, and breakdowns by age, sex and region where possible.

This dataset presents quality report data on the Coronavirus (COVID-19) Infection Survey data collection method change from study worker home visit to remote data collection.

Occupational registration data was linked to anonymised electronic health records maintained by the Secure Anonymised Information Linkage (SAIL) Databank in a privacy-protecting trusted research environment. We examined records for all linked care workers from 1st March 2016 to 30th November 2021.

Domiciliary Care Workers (DCWs) are employed in both public and private sectors to support adults at home. The support they provide varies but often includes personal care, which demands close contact between care worker and the person being supported. Since the start of the COVID-19 pandemic, people working across the care sectors in England and Wales have experienced higher rates of death involving COVID-19 infection. Social care workers, in both residential and domiciliary care settings, have been particularly badly affected, with rates of death involving COVID-19 approximately double that for health care workers.

We do not fully understand the full impact on domiciliary care worker mortality, how COVID-19 has affected worker health more broadly, and the risk factors which contribute to these. Existing evidence on deaths from the ONS relies on occupational classification. However, for many individuals reported as dying with some COVID-19 involvement, information on occupation is missing (18% and 40% missing for males and females respectively). The impact of COVID-19 on the health of domiciliary care workers (DCWs) is therefore likely to be considerable, including on COVID-19 infection itself, mental health, and respiratory illnesses. We aim to generate rapid high-quality evidence based on the views of care workers and by linking care workers' registration data to routine health data. We can use this information to inform public health interventions for safer working practice and additional support for care workers.

Our study will use a combination of research methods. We will use existing administrative data involving carer professional registration records as well as health care records. Our analysis of these data will be guided in part by qualitative interviews that we will conduct with domiciliary care workers in Wales. The interviews will address the experiences of care workers during the course of the pandemic.

Registration data for care workers in Wales will be securely transferred from the regulatory body, Social Care Wales (SCW) to the Secured Anonymised Information Linkage (SAIL) Databank at Swansea University. These data will be combined with anonymised health records made available from the SAIL databank. Information which could be used to identify individual care workers will be removed in this process. We expect that this will create a research database of all domiciliary care workers in Wales, approximately 17,000 individuals. From this group we will also identify about 30 care workers to be approached via SCW to take part in a qualitative interview. The interview sample will be chosen so that it includes workers from a variety of backgrounds.

In our analysis, we will describe the socio-demographic characteristics of the group of care workers in the research database, for example, their average age. We will establish the number of care workers with both suspected and confirmed COVID-19 infection. Will explore how infection with COVID-19 has impacted on key health outcomes, including whether workers were admitted to hospital or died. We will also explore the health of care workers before and during COVID-19 pandemic. We will use the information gained from interviews with care workers to guide the way we analyse the health records of the care workers. Finally, we will examine how well the results from our analysis of care workers in Wales can be used inform what may be happening for workers in other countries in the UK.

To ensure that our findings will be of most use to those working in social care, we will work with an Implementation Reference Group. The group will include key stakeholders such as representatives from regulators from across the UK. Working with this group, we will provide rapid recommendations to drive public health initiatives for care worker safety. This may include changes in working practices and longer-term service planning to support care worker health needs.

Antibody and swabs data broken down by population characteristics, from the Coronavirus (COVID-19) Infection Survey. Experimental Statistics.