Model estimates of deaths involving the coronavirus (COVID-19) by ethnic group for people in private households in England.

Unequal impact of COVID-19: BAME disproportionality With the whole country and world waking up to the deeply entrenched structural equalities that have impacted the lives of our Black, Asian and other ethnic Minority communities, there is a collective appreciation that we need to go further to dismantle a system, and create new ones. Local and national evidence shows that people from a Black, Asian or minority ethnic background are disproportionately impacted by Covid-19. In response to this, the council implemented this working group to carry out a rapid 6-week programme to gather evidence of the impacts of Covid-19 and develop actions for supporting our residents during this time and beyond. Intensive work has been underway to understand and take action to address the direct and indirect health impacts of Covid-19 on our Black, Asian and other Ethnic Minority communities in Camden, and to ensure that individuals and communities are protected both now and through the next phase of the pandemic, but also to bring about wider systemic change. This document is us working in the open with you and shows the information that was provided by different service areas to the member-led working group for comment and to develop actions going forward. The Black, Asian and other Ethnic Minority Inequalities and Covid-19 Working Group has benefitted from evidence and the lived experience of our residents, VCS partners, professionals and Members in guiding and shaping the Council’s response from bureaucratic to relational. In this document you will find summaries of the data included in these presentation slides and the relevant links to documents.

BackgroundMinority ethnic groups are at increased risk of COVID-19 related mortality or morbidity yet continue to have a disproportionally lower uptake of the vaccine. The importance of adherence to prevention and control measures to keep vulnerable populations and their families safe therefore remains crucial. This research sought to examine the knowledge, perceived risk, and attitudes toward COVID-19 among an ethnically diverse community.MethodsA cross-sectional self-administered questionnaire was implemented to survey ethnic minority participants purposefully recruited from Luton, an ethnically diverse town in the southeast of England. The questionnaire was structured to assess participants knowledge, perceived risk, attitudes toward protective measures as well as the sources of information about COVID-19. The questionnaire was administered online via Qualtrics with the link shared through social media platforms such as Facebook, Twitter, and WhatsApp. Questionnaires were also printed into brochures and disseminated via community researchers and community links to individuals alongside religious, community and outreach organisations. Data were analysed using appropriate statistical techniques, with the significance threshold for all analyses assumed at p = 0.05.Findings1,058 participants (634; 60% females) with a median age of 38 (IQR, 22) completed the survey. National TV and social networks were the most frequently accessed sources of COVID-19 related information; however, healthcare professionals, whilst not widely accessed, were viewed as the most trusted. Knowledge of transmission routes and perceived susceptibility were significant predictors of attitudes toward health-protective practises.Conclusion/recommendationImproving the local information provision, including using tailored communication strategies that draw on trusted sources, including healthcare professionals, could facilitate understanding of risk and promote adherence to health-protective actions.

Counts of coronavirus (COVID-19) related deaths by ethnic group in Wales.

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.

Age-standardised mortality rates (ASMRs) for deaths involving COVID-19 by ethnic group, England.

PIONEER: The impact of ethnicity and multi-morbidity on COVID-related outcomes; a primary care supplemented hospitalised dataset Dataset number 3.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 65million cases and more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) and death. Evidence suggests that older patients, those from some ethnic minority groups and those with multiple long-term health conditions have worse outcomes. This secondary care COVID dataset contains granular demographic and morbidity data, supplemented from primary care records, to add to the understanding of patient factors on disease outcomes.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 and 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – May 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes but also primary care records and clinic letters. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT, MRI, ultrasound).

Available supplementary data: Health data preceding and following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

As of February 4, 2022, in the age group 75 to 84 years old COVID-19 was involved in the deaths of 32,780 males and 23,390 females in the United Kingdom. Furthermore, since the pandemic started over 72 thousand deaths in the UK among those aged 85 years and above involved COVID-19. For further information about the COVID-19 pandemic, please visit our dedicated Facts and Figures page.

The COVID-19 Health Inequalities Monitoring in England (CHIME) tool brings together data relating to the direct impacts of coronavirus (COVID-19) on factors such as mortality rates, hospital admissions, confirmed cases and vaccinations.

By presenting inequality breakdowns – including by age, sex, ethnic group, level of deprivation and region – the tool provides a single point of access to:

• show how inequalities have changed during the course of the pandemic and what the current cumulative picture is
• bring together data in one tool to enable users to access and use the intelligence more easily
• provide indicators with a consistent methodology across different data sets to facilitate understanding
• support users to identify and address inequalities within their areas, and identify priority areas for recovery

In the September 2022 update, data have been updated for deaths, hospital admissions and vaccinations. Data for confirmed cases are no longer being updated in the tool and March 2022 remains the most recent data point.

Confirmed cases for ethnic groups, which had previously only been available to December 2021, have now been updated to March 2022. Two changes have been implemented for confirmed cases by ethnic group. The change in https://ukhsa.blog.gov.uk/2022/02/04/changing-the-covid-19-case-definition/" class="govuk-link">COVID-19 case definition, which was made in February 2022, has now been implemented. The method of assigning an ethnic group for confirmed cases has also changed. These changes have resulted in revisions to the trends reported for confirmed cases for all ethnic groups. Methods of assigning ethnicity for data within CHIME are documented

Changes have also been made to the confirmed case rates presented for all ages, with age-standardised rates replaced by crude mortality rates.

The next updates will be 09:30 on 15 December 2022.

Vaccinations in London Between 8 December 2020 and 15 September 2021 5,838,305 1st doses and 5,232,885 2nd doses have been administered to London residents. Differences in vaccine roll out between London and the Rest of England London Rest of England Priority Group Vaccinations given Percentage vaccinated Vaccinations given Percentage vaccinated Group 1 Older Adult Care Home Residents 21,883 95% 275,964 96% Older Adult Care Home Staff 29,405 85% 381,637 88% Group 2 80+ years 251,021 83% 2,368,284 93% Health Care Worker 174,944 99% 1,139,243 100%* Group 3 75 - 79 years 177,665 90% 1,796,408 99% Group 4 70 - 74 years 252,609 90% 2,454,381 97% Clinically Extremely Vulnerable 278,967 88% 1,850,485 95% Group 5 65 - 69 years 285,768 90% 2,381,250 97% Group 6 At Risk or Carer (Under 65) 983,379 78% 6,093,082 88% Younger Adult Care Home Residents 3,822 92% 30,321 93% Group 7 60 - 64 years 373,327 92% 2,748,412 98% Group 8 55 - 59 years 465,276 91% 3,152,412 97% Group 9 50 - 54 years 510,132 90% 3,141,219 95% Data as at 15 September 2021 for age based groups and as at 12 September 2021 for non-age based groups * The number who have received their first dose exceeds the latest official estimate of the population for this group There is considerable uncertainty in the population denominators used to calculate the percentage vaccinated. Comparing implied vaccination rates for multiple sources of denominators provides some indication of uncertainty in the true values. Confidence is higher where the results from multiple sources agree more closely. Because the denominator sources are not fully independent of one another, users should interpret the range of values across sources as indicating the minimum range of uncertainty in the true value. The following datasets can be used to estimate vaccine uptake by age group for London: ONS 2020 mid-year estimates (MYE). This is the population estimate used for age groups throughout the rest of the analysis. Number of people ages 18 and over on the National Immunisation Management Service (NIMS) ONS Public Health Data Asset (PHDA) dataset. This is a linked dataset combining the 2011 Census, the General Practice Extraction Service (GPES) data for pandemic planning and research and the Hospital Episode Statistics (HES). This data covers a subset of the population. Vaccine roll out in London by Ethnic Group Understanding how vaccine uptake varies across different ethnic groups in London is complicated by two issues: Ethnicity information for recipients is unavailable for a very large number of the vaccinations that have been delivered. As a result, estimates of vaccine uptake by ethnic group are highly sensitive to the assumptions about and treatment of the Unknown group in calculations of rates. For vaccinations given to people aged 50 and over in London nearly 10% do not have ethnicity information available, The accuracy of available population denominators by ethnic group is limited. Because ethnicity information is not captured in official estimates of births, deaths, and migration, the available population denominators typically rely on projecting forward patterns captured in the 2011 Census. Subsequent changes to these patterns, particularly with respect to international migration, leads to increasing uncertainty in the accuracy of denominators sources as we move further away from 2011. Comparing estimated population sizes and implied vaccination rates for multiple sources of denominators provides some indication of uncertainty in the true values. Confidence is higher where the results from multiple sources agree more closely. Because the denominator sources are not fully independent of one another, users should interpret the range of values across sources as indicating the minimum range of uncertainty in the true value. The following population estimates are available by Ethnic group for London:

According to a report conducted in the United Kingdom in 2020, 50 percent of white women and 46 percent of Black and minority women said they had experienced abuse based on their gender. Additionally, 42 percent of Black and minoritized respondents of color reported having experienced abuse based on their ethnic background. Black women and women of color were also more likely to be targeted by online abuse based on their religion and gender identity.

Coronavirus affects some members of the population more than others. Emerging evidence suggests that older people, men, people with health conditions such as respiratory and pulmonary conditions, and people of a Black, Asian Minority Ethnic (BAME) background are at particular risk. There are also a number of other wider public health risk factors that have been found to increase the likelihood of an individual contracting coronavirus. This briefing presents descriptive evidence on a range of these factors, seeking to understand at a London-wide level the proportion of the population affected by each.

A survey carried out in the United Kingdom in September 2021 revealed that ** percent of respondents between the ages of ** and ** had come across news or information about the coronavirus that they thought was false or misleading in the last week, compared to just ** percent of those aged 65 or above. Younger consumers were also the least likely to say that they had not seen any fake news on COVID-19 or were unsure whether or not they had, whilst a higher share of older consumers admitted that they did not know if they had encounted misleading information about the pandemic in the week running to the survey.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

As of February 17, 2022, there had been approximately 139.5 thousand deaths due to COVID-19 recorded in England. When broken down by age, almost 37 percent of these deaths occurred in the age group 80 to 89 years, while a further fifth of deaths were recorded among over 90 year olds. For further information about the COVID-19 pandemic, please visit our dedicated Facts and Figures page.

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.

Between January 1, 2021 and May 31, 2022, there were approximately 30.6 thousand deaths involving COVID-19 among 80 to 89 year olds in England, with over 14 thousand deaths occurring among unvaccinated people in this age group. Across all the age groups in the provided time interval, deaths involving COVID-19 among the unvaccinated population was around double the amount of people who received at least two doses of a vaccine. For further information about the COVID-19 pandemic, please visit our dedicated Facts and Figures page.

Prior to COVID-19, the NHS England Workforce Race Equalities Standard (WRES) found that ethnic minority staff experience considerably greater levels of workplace harassment and discrimination, lower pay, less control and poorer working conditions than White British staff [1]. Since the outbreak, these adverse working conditions have been exacerbated. Ethnic minority staff experience increased exposure to these workplace adversities, placement in more vulnerable positions, and disempowerment from complaining about deleterious working conditions. These ethnic disparities need to be addressed if we are to avoid the social, economic, and moral costs of excessive adverse mental health and occupational outcomes for ethnic minority staff.

This study aims to identify ethnic inequalities in mental health and occupational outcomes amongst NHS staff during the COVID-19 pandemic. Interviews will be conducted with i) participants of the CHECK survey, ii) London healthcare practitioners (HCPs, e.g., nurses and healthcare assistants) who were interviewed as part of the Tackling Inequalities and Discrimination Experiences (TIDES) study before COVID-19, and iii) NHS managers and senior staff nationally. Findings will be used to develop education and training materials to support BAME NHS staff nationally through collaboration with psychologists (KCL Virtual Reality (VR) Lab), medical educators (e.g., Maudsley Learning) and equality and diversity professionals (Challenge Consultancy).

Prior to COVID-19, the NHS England Workforce Race Equalities Standard (WRES) found that ethnic minority staff experience considerably greater levels of workplace harassment and discrimination, lower pay, less control and poorer working conditions than White British staff [1]. Since the outbreak, these adverse working conditions have been exacerbated. Ethnic minority staff experience increased exposure to these workplace adversities, placement in more vulnerable positions, and disempowerment from complaining about deleterious working conditions. These ethnic disparities need to be addressed if we are to avoid the social, economic, and moral costs of excessive adverse mental health and occupational outcomes for ethnic minority staff. This study aims to identify ethnic inequalities in mental health and occupational outcomes amongst NHS staff during the COVID-19 pandemic.

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.