Data acquired with SWATH MS then underwent protein identification using the twin plasma library and the new z-scores merged library. Here is the intensity data for these library searches.

Analysis of populations in the UK by likelihood of having received a third vaccination against COVID-19 using the Coronavirus (COVID-19) Infection Survey. This survey is being delivered in partnership with University of Oxford, University of Manchester, UK Health Security Agency and Wellcome Trust.

Roadside advertising impacts have been affected by the coronavirus outbreak in the United Kingdom (UK). However, in Edinburgh, Greater London, and Greater Manchester on the Thursday and Saturday before Easter, impacts increased compared to the week before. There was a decrease in roadside ad impacts on Good Friday and Easter Sunday. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This review summarizes the economic impacts of the pandemic on ethnic minorities, focusing on the city of Manchester. It utilizes multiple reporting sources to explore various dimensions of the economic shock in the UK, linking this to studies of pre-COVID-19 economic and ethnic composition in Manchester and in the combined authority area of Greater Manchester. We then make inferences about the pandemic's short-term impact specific to the city region. Greater Manchester has seen some of the highest rates of COVID-19 and as a result faced particularly stringent “lockdown” regulations. Manchester is the sixth most deprived Local Authority in England, according to 2019 English Indices of Multiple Deprivation. As a consequence, many neighborhoods in the city were always going to be less resilient to the economic shock caused by the pandemic compared with other, less-deprived, areas. Particular challenges for Manchester include the high rates of poor health, low-paid work, low qualifications, poor housing conditions and overcrowding. Ethnic minority groups also faced disparities long before the onset of the pandemic. Within the UK, ethnic minorities were found to be most disadvantaged in terms of employment and housing–particularly in large urban areas containing traditional settlement areas for ethnic minorities. Further, all Black, Asian, and Minority ethnic (BAME) groups in Greater Manchester were less likely to be employed pre-pandemic compared with White people. For example, people of Pakistani and Bangladeshi ethnic backgrounds, especially women, have the lowest levels of employment in Greater Manchester. Finally, unprecedented cuts to public spending as a result of austerity have also disproportionately affected women of an ethnic minority background alongside disabled people, the young and those with no or low-level qualifications. This environment has created and sustained a multiplicative disadvantage for Manchester's ethnic minority residents through the course of the COVID-19 pandemic.

This dataset comprises of 16 anonymised interview transcripts with older adults aged 65 years and over living in areas of high socioeconomic deprivation in Manchester. These transcripts provide detail about participants' experiences of and attitudes towards engaging in physical activity in the aftermath of the COVID-19 pandemic. They were analysed using reflexive thematic analysis.

Anxiety and depression are the most prevalent classes of mental illnesses; rates of anxiety and depression have been exacerbated due to the COVID-19 pandemic. Vulnerability to anxiety and depression are affected by risk and resilience factors, such as personality constructs. Recent research (e.g., Lyon et al, 2020; 2021) suggests that, out of all 30 NEO-PI-R personality constructs, variance in anxiety and depression are explained by a small number of personality constructs. However it is unclear which mechanisms mediate the relationship between these personality constructs and anxiety and depression. The purpose of this study was to investigate the mediating effect of emotion regulation strategies on the relationship between personality constructs and COVID-related anxiety and depression. Data were collected from a sample of 210 students at the University of Manchester. Measures included a select number of narrow Big Five personality facets which explain variance in anxiety and depression (facets depression, assertiveness, gregariousness, positive emotion and competence), select COPE Inventory strategies associated with coping with pandemics, and COVID-related anxiety and depression. Measures of COPE strategies and mental health were adapted to refer to coping and mental health in response to COVID pandemic.

Demographics table.

Columns indicate whether proteins were identified in all datasets, or only within acute (A1), 3-months post-hospital discharge (R1) or healthy controls (H1). If proteins were absent within a disease group, this is indicated by ‘missing’.

The same data as stored in the "raw data" dataset is reformatted in "pickle" format for use in python plotting. README.txt contains descriptions of the data in each column of the table.

Categorical variables presented as n (%) and continuous as median (IQR).

Multivariable models adjusted by demographics and variables showing significance at univariable analysis. Multivariable model 1: vital signs included as EWS, and not individually. Multivariable Model 2: vital signs included as separate variables, and not including EWS.

The Evidence for Equality National Survey (EVENS) is a national survey that documents the experiences and attitudes of ethnic and religious minorities in Britain. EVENS was developed by the Centre on the Dynamics of Ethnicity (CoDE) in response to the disproportionate impacts of COVID-19 and is the largest and most comprehensive survey of the lives of ethnic and religious minorities in Britain for more than 25 years. EVENS used pioneering, robust survey methods to collect data in 2021 from 14,200 participants of whom 9,700 identify as from an ethnic or religious minority. The EVENS main dataset, which is available from the UK Data Service under SN 9116, covers a large number of topics including racism and discrimination, education, employment, housing and community, health, ethnic and religious identity, and social and political participation.

The EVENS Teaching Dataset provides a selection of variables in an accessible form to support the use of EVENS in teaching across a range of subjects and levels of study. The dataset includes demographic data and variables to support the analysis of:

• racism and belonging
• health and well-being during COVID-19
• political attitudes and trust.

A supplementary dataset for the British Election Study Internet Panel (BESIP), which includes unreleased items that were collected in wave 22 of the panel (December 2021). The items within this dataset capture responses to survey questions about how the UK, Scottish, and Welsh governments were handling the COVID-19 pandemic and Scottish constitutional questions. The dataset also includes ID variables that can be used to link respondents that took part in each of the British, Scottish, and Welsh Election Studies.

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), Manchester University NHS Foundation Trust (trust code R0A), Royal Surrey County Hospital NHS Foundation Trust (trust code RA2), and Wrightington, Wigan and Leigh NHS Foundation Trust (trust code RRF). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. There is a high percentage of invalid diagnosis codes for Hampshire Hospitals NHS Foundation Trust (trust code RN5). Values for this trust should therefore be interpreted with caution. 3. 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). 4. 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.

This statistical release makes available the most recent Improving Access to Psychological Therapies (IAPT) monthly data, including activity, waiting times, and outcomes such as recovery. IAPT is run by the NHS in England and offers NICE-approved therapies for treating people with depression or anxiety. This release also includes experimental statistics from the IAPT Employment Adviser Pilot. Due to the coronavirus illness (COVID-19) disruption, it would seem that this is affecting the quality and coverage of some of our statistics, such as an increase in non-submissions for some datasets. We are also seeing some different patterns in submitted data. We hope this information is helpful and would be grateful if you could spare a couple of minutes to complete a short customer satisfaction survey. Please use the survey in the related links to provide us with any feedback or suggestions for improving the report. Note: Corrections have been made to the M110 (Count_CBTAppts) and M1020 (Count_ConsMediumChatRoomAppts) variables in the Monthly Activity Data file for April 2022 through to December 2022. In addition, Commissioning Region breakdowns have been added to the IAPT Monthly Activity Data File. Where the CCG for Provider DA201 (SURVIVORS MANCHESTER(SALFORD)) was listed as "InvalidCode" ("Unknown"), it has been changed to "14L" ("NHS MANCHESTER CCG").