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TwitterThe data includes:
These reports summarise epidemiological data as at 14 December 2020 at 10am.
See the https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-hospital-activity/">detailed data on hospital activity.
See the https://coronavirus.data.gov.uk/">detailed data on the progress of the coronavirus pandemic.
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TwitterAs of January 12, 2023, COVID-19 has been responsible for 202,157 deaths in the UK overall. The North West of England has been the most affected area in terms of deaths at 28,116, followed by the South East of England with 26,221 coronavirus deaths. Furthermore, there have been 22,264 mortalities in London as a result of COVID-19.
For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.
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Provisional counts of the number of deaths and age-standardised mortality rates involving the coronavirus (COVID-19) in England and Wales. Figures are provided by age, sex, geographies down to local authority level and deprivation indices.
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TwitterIn early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. As of December 2023, the South East had the highest number of confirmed first episode cases of the virus in the UK with 3,180,101 registered cases, while London had 2,947,727 confirmed first-time cases. Overall, there has been 24,243,393 confirmed cases of COVID-19 in the UK as of January 13, 2023.
COVID deaths in the UK COVID-19 was responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK had the highest death toll from coronavirus in western Europe. The incidence of deaths in the UK was 297.8 per 100,000 population as January 13, 2023.
Current infection rate in Europe The infection rate in the UK was 43.3 cases per 100,000 population in the last seven days as of March 13, 2023. Austria had the highest rate at 224 cases per 100,000 in the last week.
For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.
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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.
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TwitterIn early-February, 2020, the first cases of the coronavirus (COVID-19) were reported in the United Kingdom (UK). The number of cases in the UK has since risen to 24,243,393, with 1,062 new cases reported on January 13, 2023. The highest daily figure since the beginning of the pandemic was on January 6, 2022 at 275,646 cases.
COVID deaths in the UK COVID-19 has so far been responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK has one of the highest death toll from COVID-19 in Europe. As of January 13, the incidence of deaths in the UK is 298 per 100,000 population.
Regional breakdown The South East has the highest amount of cases in the country with 3,123,050 confirmed cases as of January 11. London and the North West have 2,912,859 and 2,580,090 cases respectively.
For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.
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TwitterOn March 4, 2020, the first death as a result of coronavirus (COVID-19) was recorded in the United Kingdom (UK). The number of deaths in the UK has increased significantly since then. As of January 13, 2023, the number of confirmed deaths due to coronavirus in the UK amounted to 202,157. On January 21, 2021, 1,370 deaths were recorded, which was the highest total in single day in the UK since the outbreak began.
Number of deaths among highest in Europe
The UK has had the highest number of deaths from coronavirus in western Europe. In terms of rate of coronavirus deaths, the UK has recorded 297.8 deaths per 100,000 population.
Cases in the UK The number of confirmed cases of coronavirus in the UK was 24,243,393 as of January 13, 2023. The South East has the highest number of first-episode confirmed cases of the virus in the UK with 3,123,050 cases, while London and the North West have 2,912,859 and 2,580,090 confirmed cases respectively. As of January 16, the UK has had 50 new cases per 100,000 in the last seven days.
For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.
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TwitterAccording to a survey conducted in the United Kingdom (UK) as of April 2022, 246 thousand people in the South East of England were estimated to be suffering long COVID symptoms, the highest number across the regions in the UK. In the North West of England a further 218 thousand people were estimated to have long COVID.
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TwitterThe COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.
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TwitterThis study consists of transcripts of interviews conducted as part of the research project Identity, Inequality and the Media in Brexit-Covid-19-Britain. These transcripts report verbatim on in-depth interviews conducted with interviewees who live in the South West, East Midlands and North East of England. The interviews were designed to explore the ways in which participants perceived and experienced the social and political impacts of COVID-19 and Brexit. They explore the impact of both the pandemic and Brexit on individuals’ daily lives, their sense of belonging (or not) to place and nation, as well as the ways in which individuals engage with the media. Some of the interviews include a discussion of images that the participants felt captured the processes of Brexit and the pandemic. Furthermore, some of the interviews conducted in the South West focussed specifically on the project artist’s representation of the research themes.
The study authors conducted 90 interviews for this research. Of these, 80 are included in the UKDS version due to confidentiality considerations.
The interviews were conducted between October 2020 and July 2021. During this time England was experiencing national lockdowns and varying degrees of social distancing restrictions due to the COVID-19 pandemic.
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Twitterhttps://icoda-research.org/project/dp-priest/https://icoda-research.org/project/dp-priest/
This test dataset consists of one table of variables collected in PRIEST dataset. The PRIEST (Pandemic Respiratory Infection Emergency System Triage) Study for Low and Middle-Income Countries (DP – PRIEST)
To ensure hospitals in low- and middle- income countries are not overwhelmed during the COVID-19 pandemic by developing a risk assessment tool for clinicians to quickly decide whether a patient needs emergency care or can be safely sent home.
Carl Marincowitz and colleagues at the University of Sheffield in the United Kingdom and the University of Cape Town in South Africa have developed a risk assessment tool to help emergency clinicians quickly decide whether a patient with suspected COVID-19 needs emergency care or can be safely treated at home to avoid overburdening hospitals particularly in low- and middle- income countries (LMICs). They have used existing data to which they have access on 50,000 patients with suspected COVID-19 infection who sought emergency care in the United Kingdom, South Africa, and Sudan to develop prediction models for specific COVID-19 related outcomes in all income settings. These prediction models have been used to develop risk stratification tools, which enable providers to identify the right level of care and services for distinct subgroups of patients. These have been developed with input from patient and clinical stakeholders. The team have tested the performance of their risk assessment tools for identifying high-risk patients with existing triage methods.
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This indicator is designed to accompany the SHMI publication. The SHMI includes all deaths reported of patients who were admitted to non-specialist acute trusts in England and either died while in hospital or within 30 days of discharge. Deaths related to COVID-19 are excluded from the SHMI. A contextual indicator on the percentage of deaths reported in the SHMI which occurred in hospital and the percentage which occurred outside of hospital is 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 from March 2020 due to COVID-19 impacting on activity for England 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 East Lancashire Hospitals NHS Trust (trust code RXR) and The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. Due to a problem with the process which links Hospital Episode Statistics (HES) data to the Office for National Statistics (ONS) death registrations data, some in-hospital deaths have been counted as survivals in a small number of trusts. This affects 80 spells in the current time period for Mid and South Essex NHS Foundation Trust (trust code RAJ) meaning that the number of observed deaths has been underestimated and so the results for this trust should be interpreted with caution. For the other trusts, the number of affected spells is 5 or fewer and so the impact will be small. 6. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 7. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.
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Number of excess deaths, including deaths due to coronavirus (COVID-19) and due to other causes. Including breakdowns by age, sex and geography.
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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. A large proportion of records for Mid and South Essex NHS Foundation Trust (trust code RAJ) have missing or incorrect information for the main condition the patient was in hospital for (their primary diagnosis) and this will have affected the calculation of the expected number of deaths. Values for this trust should therefore be interpreted with caution. 2. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. Maidstone and Tunbridge Wells NHS Trust (trust code RWF) has submitted a number of records with a patient classification of ‘day case’ or ‘regular day attender’ and an intended management value of ‘patient to stay in hospital for at least one night’. This mismatch has resulted in the patient classification being updated to ‘ordinary admission’ by the Hospital Episode Statistics (HES) data cleaning rules. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for these trusts should therefore be interpreted with caution. 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.
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TwitterBased on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.
The difficulties of death figures
This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.
Where are these numbers coming from?
The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.
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TwitterThe key results for the data collected on the number and percentage of VTE risk assessments on inpatients aged 16 and over admitted to NHS-funded acute care (NHS trusts, NHS foundation trusts and independent sector providers) in quarter 1 (Q1) 2019/20 are: England continues to achieve the 95% NHS Standard Contract threshold. Of the 3.8 million admitted inpatients aged 16 and over for whom data was reported in this collection, 3.7 million (96%) were risk assessed for VTE on admission. From Q4 2015/16 to Q4 2016/17 the percentage of inpatients risk assessed for VTE was stable at 96%. The results for Q1 2017/18 showed a reduction of 1% with 95% of patients being risk assessed for VTE and this remained static until Q4 2017/18. In Q1 2018/19 the percentage of patients being risk assessed for VTE increased to 96% but decreased again in Q2 2018/19 to 95%. In Q3 2018/19 performance increased to 96% and remained at 96% in Q4 2018/19. From April 2019 the data collection changed to include inpatients aged 16 and over at the time of admission. In Q1 2019/20 the percentage of inpatients risk assessed was 96%. In Q1 2019/20, the percentage of admitted inpatients aged 16 and over at the time of admission risk assessed for VTE was 96% for NHS acute care providers and 98% for independent sector providers. NHS acute care providers carried out about 97% of all VTE risk assessments. Six regions (North East and Yorkshire, North West, Midlands, East of England, London and South East) achieved the 95% NHS Standard Contract operational standard in Q1 2019/20. The South West did not meet the operational standard and risk assessed 94.7% of inpatients. In Q1 2019/20, 80% of providers (240 of the 299 providers) carried out a VTE risk assessment for 95% or more of their admissions (the NHS Standard Contract operational standard). This breaks down as 72% of NHS acute providers (106 of 147) and 88% of independent sector providers (134 of 152). Of the 59 providers (20%) that did not achieve the 95% operational standard in Q1 2019/20, 76% (45 of 59) risk assessed between 90% and 95% of total admissions for VTE. https://improvement.nhs.uk/resources/vte-risk-assessment-q1-201920/
Venous thromboembolism (VTE) risk assessment: Q1 2019/20. The venous thromboembolism (VTE) risk assessment data collection is used to inform a national quality requirement in the NHS Standard Contract for 2019/20, which sets an operational standard of 95% of inpatients (aged 16 and over at the time of admission) undergoing risk assessments each month. https://improvement.nhs.uk/resources/vte-risk-assessment-q1-201920/ The official statistics for VTE risk assessment in England for quarter 1 (Q1) 2019/20 (April to June 2019) produced by NHS Improvement were released on 4 September 2019 according to the arrangements approved by the UK Statistics Authority.
https://improvement.nhs.uk/resources/vte-risk-assessment-q1-201920/
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Patients that are not educated on the signs and symptoms of VTE at hospital discharge. Doctors MUST not forget to explain their patients about the medication, so that many deaths can be avoided.
The incidence of VTE in COVID-19 patients is not well established. Reports have ranged between 1.1% in non-ICU hospital wards to 69% in ICU patients screened with lower extremity ultrasound. Small sample sizes, differences in patient characteristics, co-morbidities, hospital and ICU admission criteria, criteria for diagnostic imaging, and COVID-19 therapies likely contribute to this wide range of estimates. Like other medical patients, those with more severe disease, especially if they have additional risk factors (e.g. older, male, obesity, cancer, history of VTE, comorbid diseases, ICU care), have a higher risk of VTE than those with mild or asymptomatic disease. VTE rate in outpatients has not been reported. https://www.hematology.org/covid-19/covid-19-and-vte-anticoagulation
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TwitterAs of October 3, 2023, there were 2,189,008 confirmed cases of coronavirus (COVID-19) in Scotland. The Greater Glasgow and Clyde health board has the highest amount of confirmed cases at 514,117, although this is also the most populated part of Scotland. The Lothian health board has 368,930 confirmed cases which contains Edinburgh, the capital city of Scotland.
Situation in the rest of the UK Across the whole of the UK there have been 24,243,393 confirmed cases of coronavirus as of January 2023. Scotland currently has fewer cases than four regions in England. As of December 2023, the South East has the highest number of confirmed first-episode cases of the virus in the UK with 3,180,101 registered cases, while London and the North West have 2,947,7271 and 2,621,449 confirmed cases, respectively.
COVID deaths in the UK COVID-19 has so far been responsible for 202,157deaths in the UK as of January 13, 2023, and the UK has had the highest death toll from coronavirus in Western Europe. The incidence of deaths in the UK is 297.8 per 100,000 population.
For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.
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TwitterThe following dashboards provide data on contagious respiratory viruses, including acute respiratory diseases, COVID-19, influenza (flu), and respiratory syncytial virus (RSV) in Massachusetts. The data presented here can help track trends in respiratory disease and vaccination activity across Massachusetts.
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These indicators are designed to accompany the SHMI publication. The SHMI methodology includes an adjustment for admission method. This is because crude mortality rates for elective admissions tend to be lower than crude mortality rates for non-elective admissions. Contextual indicators on the crude percentage mortality rates for elective and non-elective admissions where a death occurred either in hospital or within 30 days (inclusive) of being discharged from hospital 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 from March 2020 due to COVID-19 impacting on activity for England 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 East Lancashire Hospitals NHS Trust (trust code RXR), Northern Care Alliance NHS Foundation Trust (trust code RM3) and The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. Due to a problem with the process which links Hospital Episode Statistics (HES) data to the Office for National Statistics (ONS) death registrations data, some in-hospital deaths have been counted as survivals in a small number of trusts. This affects 89 spells in the current time period for Mid and South Essex NHS Foundation Trust (trust code RAJ) meaning that the number of observed deaths has been underestimated and so the results for this trust should be interpreted with caution. For the other trusts, the number of affected spells is 5 or fewer and so the impact will be small. 6. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 7. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.
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The inequities of the COVID-19 pandemic were clear by April 2020 when data showed that despite being just 3.5% of the population in England, Black people comprised 5.8% of those who died from the virus; whereas White people, comprising 85.3% of the population, were 73.6% of those who died. The disproportionate impact continued with, for example, over-policing: 32% of stop and search in the year ending March 2021 were of Black, Asian and Minority Ethnic (BAME) males aged 15-34, despite them being just 2.6% of the population.
The emergency measures introduced to govern the pandemic worked together to create a damaging cycle affecting Black, Asian and Minority Ethnic families and communities of all ages. Key-workers – often stopped by police on their way to provide essential services – could not furlough or work from home to avoid infection, nor support their children in home-schooling. Children in high-occupancy homes lacked adequate space and/ or equipment to learn; such homes also lacked leisure space for key workers to restore themselves after extended hours at work. Over-policing instilled fear across the generations and deterred BAME people – including the mobile elderly - from leaving crowded homes for legitimate exercise, and those that did faced the risk of receiving a Fixed Penalty Notice and a criminal record.
These insights arose from research by Co-POWeR into the synergistic effects of emergency measures on policing, child welfare, caring, physical activity and nutrition. Using community engagement, a survey with 1000 participants and interviews, focus groups, participatory workshops and community testimony days with over 400 people in total, we explored the combined impact of COVID-19 and discrimination on wellbeing and resilience across BAME FC in the UK. This policy note crystallises our findings into a framework of recommendations relating to arts and media communications, systems and structures, community and individual well-being and resilience. We promote long term actions rather than short term reactions.
In brief, we conclude that ignoring race, gender and class when tackling a pandemic can undermine not only wellbeing across Black, Asian and Minority Ethnic families and communities (BAME FC) but also their levels of trust in government. A framework to protect wellbeing and resilience in BAME FC during public health emergencies was developed by Co-POWeR to ensure that laws and guidance adopted are culturally competent.
Two viruses - COVID-19 and discrimination - are currently killing in the UK (Solanke 2020), especially within BAMEFC who are hardest hit. Survivors face ongoing damage to wellbeing and resilience, in terms of physical and mental health as well as social, cultural and economic (non-medical) consequences. Psychosocial (ADCS 2020; The Children's Society 2020)/ physical trauma of those diseased and deceased, disproportionate job-loss (Hu 2020) multigenerational housing, disrupted care chains (Rai 2016) lack of access to culture, education and exercise, poor nutrition, 'over-policing' (BigBrotherWatch 2020) hit BAMEFC severely. Local 'lockdowns' illustrate how easily BAMEFC become subject to stigmatization and discrimination through 'mis-infodemics' (IOM 2020). The impact of these viruses cause long-term poor outcomes. While systemic deficiencies have stimulated BAMEFC agency, producing solidarity under emergency, BAMEFC vulnerability remains, requiring official support. The issues are complex thus we focus on the interlinked and 'intersectional nature of forms of exclusion and disadvantage', operationalised through the idea of a 'cycle of wellbeing and resilience' (CWAR) which recognises how COVID-19 places significant stress upon BAMEFC structures and the impact of COVID-19 and discrimination on different BAMEFC cohorts across the UK, in whose lives existing health inequalities are compounded by a myriad of structural inequalities. Given the prevalence of multi-generational households, BAMEFC are likely to experience these as a complex of jostling over-lapping stressors: over-policed unemployed young adults are more likely to live with keyworkers using public transport to attend jobs in the front line, serving elders as formal/informal carers, neglecting their health thus exacerbating co-morbidities and struggling to feed children who are unable to attend school, resulting in nutritional and digital deprivation. Historical research shows race/class dimensions to national emergencies (e.g. Hurricane Katrina) but most research focuses on the COVID-19 experience of white families/communities. Co-POWeR recommendations will emerge from culturally and racially sensitive social science research on wellbeing and resilience providing context as an essential strand for the success of biomedical and policy interventions (e.g. vaccines, mass testing). We will enhance official decision-making through strengthening cultural competence in ongoing responses to COVID-19 thereby maximizing success of national strategy. Evidenced recommendations will enable official mitigation of disproportionate damage to wellbeing and resilience in BAMEFC. Empowerment is a core consortium value. Supporting UKRI goals for an inclusive research culture, we promote co-design and co-production to create a multi-disciplinary BAME research community spanning multi-cultural UK to inform policy. CO-POWeR investigates the synergistic effect on different age groups of challenges including policing, child welfare, caring and physical activity and nutrition. WP1 Emergency Powers investigates these vague powers to understand their impact on practices of wellbeing and resilience across BAMEFC. WP2 Children, Young People and their Families investigates implications for children/young people in BAMEFC who experience COVID-19 negatively due to disproportionate socio-economic and psychosocial impacts on their families and communities. WP3 Care, Caring and Carers investigates the interaction of care, caring and carers within BAMEFC to identify how to increase the wellbeing and resilience of older people, and paid and unpaid carers. WP4 Physical Activity and Nutrition investigates improving resilience and wellbeing by tackling vulnerability to underlying health conditions in BAMEFC. WP5 Empowering BAMEFC through Positive Narratives channels research from WP1-4 to coproduce fiction and non-fiction materials tackling the vulnerability of BAMEFC to 'mis infodemics'.
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TwitterThe data includes:
These reports summarise epidemiological data as at 14 December 2020 at 10am.
See the https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-hospital-activity/">detailed data on hospital activity.
See the https://coronavirus.data.gov.uk/">detailed data on the progress of the coronavirus pandemic.