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

Context

Within the current response of a pandemic caused by the SARS-CoV-2 coronavirus, which in turn causes the disease, called COVID-19. It is necessary to join forces to minimize the effects of this disease.

Therefore, the intention of this dataset is to save data scientists time:

• Gather the data at the country level, encoding the country with its ISO code to allow easy access to other data
• Perform pre-processing of data, calculations of increments and other indicators that can facilitate modeling.
• Add the response of the governments over time so that it can be taken into account in the modeling.
• Daily update.

This dataset is not intended to be static, so suggestions for expanding it are welcome. If someone considers it important to add information, please let me know.

Content

The data contained in this dataset comes mainly from the following sources:

Source: Center for Systems Science and Engineering (CSSE) at Johns Hopkins University https://github.com/CSSEGISandData/COVID-19 Provided by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE): https://systems.jhu.edu/

Source: OXFORD COVID-19 GOVERNMENT RESPONSE TRACKER https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker Hale, Thomas and Samuel Webster (2020). Oxford COVID-19 Government Response Tracker. Data use policy: Creative Commons Attribution CC BY standard.

The original data is updated daily.

The features it includes are:

• Country Name

• Country Code ISO 3166 Alpha 3

• Date

• Incidence data:

  • confirmed
  • deaths
  • recoveries

• Daily increments:

  • confirmed_inc
  • deaths_inc
  • recoveries_inc

• Empirical Contagion Rate - ECR

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3508582%2F3e90ecbcdf76dfbbee54a21800f5e0d6%2FECR.jpg?generation=1586861653126435&alt=media" alt="">

• GOVERNMENT RESPONSE TRACKER - GRTStringencyIndex

  OXFORD COVID-19 GOVERNMENT RESPONSE TRACKER - Stringency Index

• Indices from Start Contagion

  • Days since the first case of contagion is overcome
  • Days since 100 cases are exceeded

• Percentages over the country's population:

  • confirmed_PopPct
  • deaths_PopPct
  • recoveries_PopPct

The method of obtaining the data and its transformations can be seen in the notebook:

Notebook COVID-19 Data by country with Government Response

Photo by Markus Spiske on Unsplash

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

Provisional counts of the number of deaths registered in England and Wales, including deaths involving coronavirus (COVID-19), by local authority, health board and place of death in the latest weeks for which data are available. The occurrence tabs in the 2021 edition of this dataset were updated for the last time on 25 October 2022.

This dataset contains daily data trackers for the COVID-19 pandemic, aggregated by month and starting 18.3.20. The first release of COVID-19 data on this platform was on 1.6.20. Updates have been provided on a quarterly basis throughout 2023/24. No updates are currently scheduled for 2024/25 as case rates remain low. The data is accurate as at 8.00 a.m. on 8.4.24. Some narrative for the data covering the latest period is provided here below: Diagnosed cases / episodes • As at 3.4.24 CYC residents have had a total 75,556 covid episodes since the start of the pandemic, a rate of 37,465 per 100,000 of population (using 2021 Mid-Year Population estimates). The cumulative rate in York is similar to the national (37,305) and regional (37,059) averages. • The latest rate of new Covid cases per 100,000 of population for the period 28.3.24 to 3.4.24 in York was 1.49 (3 cases). The national and regional averages at this date were 1.67 and 2.19 respectively (using data published on Gov.uk on 5.4.24).

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.

This is the real-time JSON version of the COVID-19 Coronavirus Dataset Worldwide dataset, furthermore, the collection methodology can be read through: https://www.ecdc.europa.eu/en/covid-19/data-collection

Context

The worldwide situation about the COVID-19 (by 2019-03-23), data provided by the European Centre for Disease Prevention and Control and published on the EU Open Data Portal.

Content

The dataset contains the latest available public data on COVID-19 including a daily situation update, the epidemiological curve and the global geographical distribution (EU/EEA and the UK, worldwide). On 12 February 2020, the novel coronavirus was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) while the disease associated with it is now referred to as COVID-19. ECDC is closely monitoring this outbreak and providing risk assessments to guide EU Member States and the EU Commission in their response activities.

Acknowledgements

Official link: https://data.europa.eu/euodp/en/data/dataset/covid-19-coronavirus-data

Inspiration

What applications can we develop to understand COVID-19 current and prospective behavior better?

Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

Understanding Society (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society COVID-19 Study, 2020-2021 is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they took place every other month until March 2021 and the final wave was fielded in September 2021. They complement the annual interviews of the Understanding Society study. The data can be linked to data on the same individuals from previous waves of the annual interviews (SN 6614) using the personal identifier pidp. However, the most recent pre-pandemic (2019) annual interviews for all respondents who have taken part in the COVID-19 Study are included as part of this data release. Please refer to the User Guide for further information on linking in this way and for geographical information options.

Latest edition information

For the eleventh edition (December 2021), revised April, May, June, July, September, November 2020, January 2021 and March 2021 data files for the adult survey have been deposited. These files have been amended to address issues identified during ongoing quality assurance activities. All documentation has been updated to explain the revisions, and users are advised to consult the documentation for details. In addition new data from the September 2021 web survey have been deposited.

Daily Coronavirus (Covid-19) positive tests in Leicester City Council and surrounding districts.Data for the most recent 4-5 days is likely to be incomplete.Please note automatic updates to this dataset were discontinued on 12th December 2023.

As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

Number of weekly Covid-19 related hospital admissions to University Hospitals Leicester (UHL) for Leicester residents. Data where the count is less than 3 admissions have been suppressed to "..". Data is updated weekly and previous week data is subject to change when data is refreshed.Note: This dataset will soon be archived and not subject to updates. A replacement dataset is currently under development.

Background: The current propagation models of COVID-19 are poorly consistent with existing epidemiological data and with evidence that the SARS-CoV-2 genome is mutating, for potential aggressive evolution of the disease.Objectives: We looked for fundamental variables that were missing from current analyses. Among them were regional climate heterogeneity, viral evolution processes versus founder effects, and large-scale virus containment measures.Methods: We challenged regional versus genetic evolution models of COVID-19 at a whole-population level, over 168,089 laboratory-confirmed SARS-CoV-2 infection cases in Italy, Spain, and Scandinavia at early time-points of the pandemic. Diffusion data in Germany, France, and the United Kingdom provided a validation dataset of 210,239 additional cases.Results: Mean doubling time of COVID-19 cases was 6.63 days in Northern versus 5.38 days in Southern Italy. Spain extended this trend of faster diffusion in Southern Europe, with a doubling time of 4.2 days. Slower doubling times were observed in Sweden (9.4 days), Finland (10.8 days), and Norway (12.95 days). COVID-19 doubling time in Germany (7.0 days), France (7.5 days), and the United Kingdom (7.2 days) supported the North/South gradient model. Clusters of SARS-CoV-2 mutations upon sequential diffusion were not found to clearly correlate with regional distribution dynamics.Conclusion: Acquisition of mutations upon SARS-CoV-2 spreading failed to explain regional diffusion heterogeneity at early pandemic times. Our findings indicate that COVID-19 transmission rates are rather associated with a sharp North/South climate gradient, with faster spreading in Southern regions. Thus, warmer climate conditions may not limit SARS-CoV-2 infectivity. Very cold regions may be better spared by recurrent courses of SARS-CoV-2 infection.

Abstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.LFS response to COVID-19From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2024 ReweightingIn February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.End User Licence and Secure Access QLFS dataTwo versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).The Secure Access version contains more detailed variables relating to:age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent childfamily unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of familynationality and country of originfiner detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;health: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressother additional detailed variables may also be included.The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. Weighting variablesUsers should note that this quarter includes the 2023 person and income weights, PWT23 and PIWT23. Main Topics:The QLFS questionnaire comprises a 'core' of questions which are included in every survey, together with some 'non-core' questions which vary from quarter to quarter.The questionnaire can be split into two main parts. The first part contains questions on the respondent's household, family structure, basic housing information and demographic details of household members. The second part contains questions covering economic activity, education and health, and also may include a few questions asked on behalf of other government departments (for example the Department for Work and Pensions and the Home Office). Until 1997, the questions on health covered mainly problems which affected the respondent's work. From that quarter onwards, the questions cover all health problems. Detailed questions on income have also been included in each quarter since 1993. The basic questionnaire is revised each year, and a new version published, along with a transitional version that details changes from the previous year's questionnaire. Four sampling frames are used. See documentation for details.

The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.

LFS response to COVID-19

From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.

Occupation data for 2021 and 2022 data files

The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.

2024 Reweighting

In February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.

End User Licence and Secure Access QLFS data

Two versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).

The Secure Access version contains more detailed variables relating to:

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• finer detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address
• other additional detailed variables may also be included.

The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

Latest edition information

For the second edition (January 2025), the 2018 person weight (PWT18) was replaced with the 2024 person weight (PWT24). Only the person weight has been replaced with a 2024 version; the 2018 income weight (PIWT18) remains.

Abstract copyright UK Data Service and data collection copyright owner.Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991. Understanding Society (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991. The Understanding Society COVID-19 Study, 2020-2021 is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they took place every other month until March 2021 and the final wave was fielded in September 2021. They complement the annual interviews of the Understanding Society study. The data can be linked to data on the same individuals from previous waves of the annual interviews (SN 6614) using the personal identifier pidp. However, the most recent pre-pandemic (2019) annual interviews for all respondents who have taken part in the COVID-19 Study are included as part of this data release. Please refer to the User Guide for further information on linking in this way and for geographical information options. Latest edition information For the eleventh edition (December 2021), revised April, May, June, July, September, November 2020, January 2021 and March 2021 data files for the adult survey have been deposited. These files have been amended to address issues identified during ongoing quality assurance activities. All documentation has been updated to explain the revisions, and users are advised to consult the documentation for details. In addition new data from the September 2021 web survey have been deposited.

Excess mortality for England & Wales calculated for the “Russian influenza” pandemic (1890–1892 in the UK) and COVID-19 (2020 and 2021 only).

These indicators are designed to accompany the SHMI publication. 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. There has been a fall in the number of spells for some trusts due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Contextual indicators on the number of provider spells which are excluded from the SHMI due to them being related to COVID-19 and on the number of provider spells as a percentage of pre-pandemic activity (January 2019 – December 2019) are produced to support the interpretation of the SHMI. These indicators are being published as experimental statistics. 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. There is a shortfall in the number of records for Frimley Health NHS Foundation Trust (trust code RDU) and Tameside and Glossop Integrated Care NHS Foundation Trust (trust code RMP). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. A number of trusts are currently engaging in a pilot to submit Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS), rather than the Admitted Patient Care (APC) dataset. As the SHMI is calculated using APC data, this does have the potential to impact on the SHMI value for these trusts. Trusts with SDEC activity removed from the APC data have generally seen an increase in the SHMI value. This is because the observed number of deaths remains approximately the same as the mortality rate for this cohort is very low; secondly, the expected number of deaths decreases because a large number of spells are removed, all of which would have had a small, non-zero risk of mortality contributing to the expected number of deaths. We are working to better understand the planned changes to the recording of SDEC activity and the potential impact on the SHMI. The trusts affected in this publication are: Barts Health NHS Trust (trust code R1H), Cambridge University Hospitals NHS Foundation Trust (trust code RGT), Croydon Health Services NHS Trust (trust code RJ6), Epsom and St Helier University Hospitals NHS Trust (trust code RVR), Frimley Health NHS Foundation Trust (trust code RDU), Imperial College Healthcare NHS Trust (trust code RYJ), Manchester University NHS Foundation Trust (trust code R0A), Norfolk and Norwich University Hospitals NHS Foundation Trust (trust code RM1), and University Hospitals of Derby and Burton NHS Foundation Trust (trust code RTG). 3. 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.

These indicators are designed to accompany the SHMI publication. Information on the main condition the patient is in hospital for (the primary diagnosis) is used to calculate the expected number of deaths used in the calculation of the SHMI. A high percentage of records with an invalid primary diagnosis may indicate a data quality problem. A high percentage of records with a primary diagnosis which is a symptom or sign may indicate problems with data quality or timely diagnosis of patients, but may also reflect the case-mix of patients or the service model of the trust (e.g. a high level of admissions to acute admissions wards for assessment and stabilisation). Contextual indicators on the percentage of provider spells with an invalid primary diagnosis and the percentage of provider spells with a primary diagnosis which is a symptom or sign are produced to support the interpretation of the SHMI. Notes: 1. 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. Activity that is being coded as COVID-19, and therefore excluded, is monitored in the contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there was a fall in the overall number of spells for England from March 2020 due to COVID-19 impacting on activity and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for Frimley Health NHS Foundation Trust (trust code RDU) and Tameside and Glossop Integrated Care NHS Foundation Trust (trust code RMP). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 4. A number of trusts are currently engaging in a pilot to submit Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS), rather than the Admitted Patient Care (APC) dataset. As the SHMI is calculated using APC data, this does have the potential to impact on the SHMI value for these trusts. Trusts with SDEC activity removed from the APC data have generally seen an increase in the SHMI value. This is because the observed number of deaths remains approximately the same as the mortality rate for this cohort is very low; secondly, the expected number of deaths decreases because a large number of spells are removed, all of which would have had a small, non-zero risk of mortality contributing to the expected number of deaths. We are working to better understand the planned changes to the recording of SDEC activity and the potential impact on the SHMI. The trusts affected in this publication are: Barts Health NHS Trust (trust code R1H), Cambridge University Hospitals NHS Foundation Trust (trust code RGT), Croydon Health Services NHS Trust (trust code RJ6), Epsom and St Helier University Hospitals NHS Trust (trust code RVR), Frimley Health NHS Foundation Trust (trust code RDU), Imperial College Healthcare NHS Trust (trust code RYJ), Manchester University NHS Foundation Trust (trust code R0A), Norfolk and Norwich University Hospitals NHS Foundation Trust (trust code RM1), and University Hospitals of Derby and Burton NHS Foundation Trust (trust code RTG). 5. 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.

Abstract copyright UK Data Service and data collection copyright owner.

The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP.

The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.

The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.

Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage.

The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage.

Secure Access FRS data
The Secure Access version of the FRS contains unrounded data and additional variables, and is available from 2005/06 onwards. Prospective users of the Secure Access version of the FRS must fulfil additional requirements beyond those associated with the EUL datasets.

FRS, HBAI and PI
The FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The Secure Access versions are held under SNs 7196 and 9257. The EUL versions of HBAI and PI are held under SNs 5828 and 8503.

Secure Access FRS contents
The Secure Access version of the FRS contains unrounded data and a small number of extra variables that are not available on the standard EUL versions. A full listing of additional variables for the current year is available in the document '9256_frs

FRS and the coronavirus (COVID-19) pandemic

The coronavirus (COVID-19) pandemic had a notable impact on FRS 2020-21, with after-effects also on the 2021-22 survey year. The FRS team published a technical report for the 2020-21 survey to give a full assessment of the impact of the pandemic on the statistics. In line with the Statistics Code of Practice. This is designed to assist users with interpreting the data and to aid transparency over decisions and data quality issues.

Documentation
The Documentation section includes files for the latest year of the FRS only, due to available space. Documentation for previous years is provided alongside the data for access and is also available upon request.

Household characteristics (age, family composition, tenure); some spending, with housing (rent or details of mortgage); household bills including Council Tax, buildings and contents insurance, water and sewerage rates.

Receipt of state support from all state benefits, including Universal Credit and Tax Credits; educational level and grants and loans; children in education; care, both those receiving care and those caring for others; childcare; occupation, employment, self-employment and earnings/wage details, including director dividend if received; income tax payments and refunds; National Insurance contributions; pension contributions; earnings from odd jobs. Doctors and dentists are separately identified from 2021-22.

Health and disability, restrictions on work, children's health; income from personal or occupational/company pension schemes; other income from savings and investments, trusts, royalties or allowances, and other sources; children's earnings.

Material deprivation, household food security (from 2019-20) and household food bank usage (from 2021-22).

In September 2024, the global PMI amounted to 47.5 for new export orders and 48.8 for manufacturing. The manufacturing PMI was at its lowest point in August 2020. It decreased over the last months of 2022 after the effects of the Russia-Ukraine war and rising inflation hit the world economy, and remained around 50 since.