This dataset accompanies the PhD thesis Pupil Competence During the COVID-19-induced School Closures: An Analysis of the Effect of Distance Learning and Remediation Policies Using International Assessment Data in 30 Countries. The dataset compiles country-level data derived from large-scale international student assessments, specifically PISA and PIRLS, covering the period 2000–2022. It was created by harmonising publicly available microdata from the OECD (for PISA) and IEA (for PIRLS), aggregated to the national level. The data were collected and processed using StataNow 18.5. The dataset can be opened in StataNow 18.5 software. Stata .do files are also provided to allow full reproducibility of the data preparation and analysis. The dataset is specifically structured to support advanced statistical modelling, including Latent Growth Curve Modelling (LGCM), Synthetic Control (SC), and Synthetic Difference-in-Differences (SDID), to examine the effects of COVID-19 policies on pupil competence across diverse national contexts. Date Request Form: https://library.soton.ac.uk/datarequest

Cruise traffic at the port of Southampton in the United Kingdom peaked in 2023. Overall, the number of cruise passengers embarking and disembarking at that port reached around 2.65 million in 2023. Between 2020 and 2021, the number of passenger movements dropped dramatically, with travel being severely impacted by the coronavirus (COVID-19) pandemic. Both before and after the impact of the health crisis, Southampton was the leading port in the United Kingdom based on cruise passenger movements.

Dataset supporting the University of Southampton Doctoral Thesis "Navigating tensions in children’s safeguarding" The dataset includes qualitative data consisting of interview and audio diary transcripts. Participants are senior managers involved with children's safeguarding and delivery-level practitioners involved with children's safeguarding processes. Data is available only 'on request' to bone fide researchers with ethical approval. Please complete the attached request form and return it to researchdata@soton.ac.uk

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'.

The SHMI is the ratio between the actual number of patients who die following hospitalisation at the trust and the number that would be expected to die on the basis of average England figures, given the characteristics of the patients treated there. It includes deaths which occurred in hospital and deaths which occurred outside of hospital within 30 days (inclusive) of discharge. Deaths related to COVID-19 are excluded from the SHMI. The SHMI gives an indication for each non-specialist acute NHS trust in England whether the observed number of deaths within 30 days of discharge from hospital was 'higher than expected' (SHMI banding=1), 'as expected' (SHMI banding=2) or 'lower than expected' (SHMI banding=3) when compared to the national baseline. Trusts may be located at multiple sites and may be responsible for 1 or more hospitals. A breakdown of the data by site of treatment is also provided. The SHMI is composed of 142 different diagnosis groups and these are aggregated to calculate the overall SHMI value for each trust. The number of finished provider spells, observed deaths and expected deaths at diagnosis group level for each trust is available in the SHMI diagnosis group breakdown files. For a subset of diagnosis groups, an indication of whether the observed number of deaths within 30 days of discharge from hospital was 'higher than expected', 'as expected' or 'lower than expected' when compared to the national baseline is also provided. Details of the 142 diagnosis groups can be found in Appendix A of the SHMI specification. 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 a new contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there has been a fall in the number of spells for most trusts between this publication and the previous SHMI publication, ranging from 1 per cent to 5 per cent. This is due to COVID-19 impacting on activity from March 2020 onwards and appears to be an accurate reflection of hospital activity rather than a case of missing data. 3. There is a shortfall in the number of records for University Hospital Southampton NHS Foundation Trust (trust code RHM). Values for this trust are based on incomplete data and should therefore be interpreted with caution. 4. 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 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. 5. There is a shortfall in the number of birth records for Pennine Acute Hospitals NHS Trust (trust code RW6). This is likely to have a small impact on the trust level SHMI, but the impact on some diagnosis groups (groups 116 - Congenital anomalies, 117 - Short gestation and slow fetal growth, 118 - Birth related conditions, 119 - Other perinatal conditions and 141 - Livebirths) will be greater and so results for these diagnosis groups should be interpreted with caution. 6. 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. 7. This tool is in Microsoft PowerBI which does not fully support all accessibility needs. If you need further assistance, please contact us for help.