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The mathematical interpretation of interventions for the mitigation of epidemics in the literature often involves finding the optimal time to initiate an intervention and/or the use of the number of infections to manage impact. Whilst these methods may work in theory, in order to implement effectively they may require information which is not likely to be available in the midst of an epidemic, or they may require impeccable data about infection levels in the community. In reality, testing and cases data can only be as good as the policy of implementation and the compliance of the individuals, which implies that accurately estimating the levels of infections becomes difficult or complicated from the data that is provided. In this paper, we demonstrate a different approach to the mathematical modelling of interventions, not based on optimality or cases, but based on demand and capacity of hospitals who have to deal with the epidemic on a day to day basis. In particular, we use data-driven modelling to calibrate a susceptible-exposed-infectious-recovered-died type model to infer parameters that depict the dynamics of the epidemic in several regions of the UK. We use the calibrated parameters for forecasting scenarios and understand, given a maximum capacity of hospital healthcare services, how the timing of interventions, severity of interventions, and conditions for the releasing of interventions affect the overall epidemic-picture. We provide an optimisation method to capture when, in terms of healthcare demand, an intervention should be put into place given a maximum capacity on the service. By using an equivalent agent-based approach, we demonstrate uncertainty quantification on the likelihood that capacity is not breached, by how much if it does, and the limit on demand that almost guarantees capacity is not breached. [ABSTRACT FROM AUTHOR]

Nurse, Midwives and Allied Health Professionals (AHPs), along with other health and social care colleagues are the backbone of healthcare services. They have played a key role in responding to the increased demands on healthcare during the COVID-19 pandemic. This paper compares cross-sectional data on quality of working life, wellbeing, coping and burnout of nurses, midwives and AHPs in the United Kingdom (UK) at two time points during the COVID-19 pandemic. An anonymous online repeated cross-sectional survey was conducted at two timepoints, Phase 1 (7th May 2020-3rd July 2020); Phase 2 (17th November 2020-1st February 2021). The survey consisted of the Short Warwick-Edinburgh Mental Wellbeing Scale, the Work-Related Quality of Life Scale, and the Copenhagen Burnout Inventory (Phase 2 only) to measure wellbeing, quality of working life and burnout. The Brief COPE scale and Strategies for Coping with Work and Family Stressors scale assessed coping strategies. Descriptive statistics and multiple linear regressions examined the effects of coping strategies and demographic and work-related variables on wellbeing and quality of working life. A total of 1839 nurses, midwives and AHPs responded to the first or second survey, with a final sample of 1410 respondents -586 from Phase 1; 824 from Phase 2, (422 nurses, 192 midwives and 796 AHPs). Wellbeing and quality of working life scores were significantly lower in the Phase 2 sample compared to respondents in Phase 1 (p<0.001). The COVID-19 pandemic had a significant effect on psychological wellbeing and quality of working life which decreased while the use of negative coping and burnout of these healthcare professionals increased. Health services are now trying to respond to the needs of patients with COVID-19 variants while rebuilding services and tackling the backlog of normal care provision. This workforce would benefit from additional support/services to prevent further deterioration in mental health and wellbeing and optimise workforce retention. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been characterized by a social media "infodemic": an overabundance of information whose authenticity may not always be guaranteed. With the potential to lead individuals to harmful decisions for the society, this infodemic represents a severe threat to information security, public health and democracy. In this paper, we assess the interplay between the infodemic and specific aspects of the pandemic, such as the number of cases, the strictness of containment measures, and the news media coverage. We perform a comparative study on three countries that employed different managements of the COVID-19 pandemic in 2020—namely Italy, the United Kingdom, and New Zealand. We first analyze the three countries from an epidemiological perspective to characterize the impact of the pandemic and the strictness of the restrictions adopted. Then, we collect a total of 6 million posts from Facebook to describe user news consumption behaviors with respect to the reliability of such posts. Finally, we quantify the relationship between the number of posts published in each of the three countries and the number of confirmed cases, the strictness of the restrictions adopted, and the online news media coverage about the pandemic. Our results show that posts referring to reliable sources are consistently predominant in the news circulation, and that users engage more with reliable posts rather than with posts referring to questionable sources. Furthermore, our modelling results suggest that factors related to the epidemiological and informational ecosystems can serve as proxies to assess the evolution of the infodemic. [ABSTRACT FROM AUTHOR]

The objective of this paper is to model lost Quality Adjusted Life Years (QALYs) from symptoms arising from COVID-19 disease in the UK population, including symptoms of 'long-COVID'. The scope includes QALYs lost to symptoms, but not deaths, due to acute COVID-19 and long-COVID. The prevalence of symptomatic COVID-19, encompassing acute symptoms and long-COVID symptoms, was modelled using a decay function. Permanent injury as a result of COVID-19 infection, was modelled as a fixed prevalence. Both parts were combined to calculate QALY loss due to COVID-19 symptoms. Assuming a 60% final attack rate for SARS-CoV-2 infection in the population, we modelled 299,730 QALYs lost within 1 year of infection (90% due to symptomatic COVID-19 and 10% permanent injury) and 557,764 QALYs lost within 10 years of infection (49% due to symptomatic COVID-19 and 51% due to permanent injury). The UK Government willingness-to-pay to avoid these QALY losses would be £17.9 billion and £32.2 billion, respectively. Additionally, 90,143 people were subject to permanent injury from COVID-19 (0.14% of the population). Given the ongoing development in information in this area, we present a model framework for calculating the health economic impacts of symptoms following SARS-CoV-2 infection. This model framework can aid in quantifying the adverse health impact of COVID-19, long-COVID and permanent injury following COVID-19 in society and assist the proactive management of risk posed to health. Further research is needed using standardised measures of patient reported outcomes relevant to long-COVID and applied at a population level. [ABSTRACT FROM AUTHOR]

Understanding and monitoring the epidemiological time delay dynamics of SARS-CoV-2 infection provides insights that are key to discerning changes in the phenotype of the virus, the demographics impacted, the efficacy of treatment, and the ability of the health service to manage large volumes of patients. This paper analyses how the pandemic has evolved in the United Kingdom through the temporal changes to the epidemiological time delay distributions for clinical outcomes. Using the most complete clinical data presently available, we have analysed, through a doubly interval censored Bayesian modelling approach, the time from infection to a clinical outcome. Across the pandemic, for the periods that were defined as epidemiologically distinct, the modelled mean ranges from 8.0 to 9.7 days for infection to hospitalisation, 10.3 to 15.0 days for hospitalisation to death, and 17.4 to 24.7 days for infection to death. The time delay from infection to hospitalisation has increased since the first wave of the pandemic. A marked decrease was observed in the time from hospitalisation to death and infection to death at times of high incidence when hospitals and ICUs were under the most pressure. There is a clear relationship between age groups that is indicative of the youngest and oldest demographics having the shortest time delay distributions before a clinical outcome. A statistically significant difference was found between genders for the time delay from infection to hospitalisation, which was not found for hospitalisation to death. The results by age group indicate that younger demographics that require clinical intervention for SARS-CoV-2 infection are more likely to require earlier hospitalisation that leads to a shorter time to death, which is suggestive of the largely more vulnerable nature of these individuals that succumb to infection. The distinction found between genders for exposure to hospitalisation is revealing of gender healthcare seeking behaviours. [ABSTRACT FROM AUTHOR]

Background: One of the few studies to estimate infection risk with SARS-CoV-2 in the general population was the UK Office of National Statistics Infection Survey. This survey provided data that allowed us to describe and interpret apparent risk factors for testing positive for SARS-CoV-2 in a period when variants and COVID-19 controls experienced large changes. Method: The ONS published estimates of likelihood of individuals testing positive in two week monitoring periods between 21st November 2021 and 7th May 2022, relating this positivity to social and behavioural factors. We applied meta-regression to these estimates of likelihood of testing positive to determine whether the monitored potential risk factors remained constant during the pandemic. Results: Some risk factors had consistent relationship with risk of infection (always protective or always linked to higher risk, throughout monitoring period). Other risk factors had variable relationship with risk of infection, with changes seeming to especially correlate with the emergence of Omicron BA.2 dominance. These variable factors were mask-wearing habits, history of foreign travel, household size, working status (retired or not) and contact with children or persons age over 70. Conclusion: Relevance of some risk factors to likelihood of testing positive for SARS-CoV-2 may relate to reinfection risk, variant infectiousness and status of social distancing regulations. [ABSTRACT FROM AUTHOR]

Background: Long-term health conditions can affect labour market outcomes. COVID-19 may have increased labour market inequalities, e.g. due to restricted opportunities for clinically vulnerable people. Evaluating COVID-19's impact could help target support. Aim: To quantify the effect of several long-term conditions on UK labour market outcomes during the COVID-19 pandemic and compare them to pre-pandemic outcomes. Methods: The Understanding Society COVID-19 survey collected responses from around 20,000 UK residents in nine waves from April 2020-September 2021. Participants employed in January/February 2020 with a variety of long-term conditions were matched with people without the condition but with similar baseline characteristics. Models estimated probability of employment, hours worked and earnings. We compared these results with results from a two-year pre-pandemic period. We also modelled probability of furlough and home-working frequency during COVID-19. Results: Most conditions (asthma, arthritis, emotional/nervous/psychiatric problems, vascular/pulmonary/liver conditions, epilepsy) were associated with reduced employment probability and/or hours worked during COVID-19, but not pre-pandemic. Furlough was more likely for people with pulmonary conditions. People with arthritis and cancer were slower to return to in-person working. Few effects were seen for earnings. Conclusion: COVID-19 had a disproportionate impact on people with long-term conditions' labour market outcomes. [ABSTRACT FROM AUTHOR]

Background: The impact of the Covid-19 pandemic on young people's (YP) mental health has been mixed. Systematic reviews to date have focused predominantly on quantitative studies and lacked involvement from YP with lived experience of mental health difficulties. Therefore, our primary aim was to conduct a qualitative systematic review to examine the perceived impact of the Covid-19 pandemic on YP's (aged 10–24) mental health and wellbeing across Europe. Methods and findings: We searched MEDLINE, PsycINFO, Embase, Web of Science, MEDRXIV, OSF preprints, Google, and voluntary sector websites for studies published from 1st January 2020 to 15th November 2022. European studies were included if they reported qualitative data that could be extracted on YP's (aged 10–24) own perspectives of their experiences of Covid-19 and related disruptions to their mental health and wellbeing. Screening, data extraction and appraisal was conducted independently in duplicate by researchers and YP with lived experience of mental health difficulties (co-researchers). Confidence was assessed using the Confidence in the Evidence from Reviews of Qualitative Research (CERQual) approach. We co-produced an adapted narrative thematic synthesis with co-researchers. This study is registered with PROSPERO, CRD42021251578. We found 82 publications and included 77 unique studies in our narrative synthesis. Most studies were from the UK (n = 50; 65%); and generated data during the first Covid-19 wave (March-May 2020; n = 33; 43%). Across the 79,491 participants, views, and experiences of YP minoritised by ethnicity and sexual orientation, and from marginalised or vulnerable YP were limited. Five synthesised themes were identified: negative impact of pandemic information and restrictions on wellbeing; education and learning on wellbeing; social connection to prevent loneliness and disconnection; emotional, lifestyle and behavioural changes; and mental health support. YP's mental health and wellbeing across Europe were reported to have fluctuated during the pandemic. Challenges were similar but coping strategies to manage the impact of these challenges on mental health varied across person, study, and country. Short-term impacts were related to the consequences of changing restrictions on social connection, day-to-day lifestyle, and education set-up. However, YP identified potential issues in these areas going forward, and therefore stressed the importance of ongoing long-term support in education, learning and mental health post-Covid-19. Conclusions: Our findings map onto the complex picture seen from quantitative systematic reviews regarding the impact of Covid-19 on YP's mental health. The comparatively little qualitative data found in our review means there is an urgent need for more high-quality qualitative research outside of the UK and/or about the experiences of minoritised groups to ensure all voices are heard and everyone is getting the support they need following the pandemic. YP's voices need to be prioritised in decision-making processes on education, self-care strategies, and mental health and wellbeing, to drive impactful, meaningful policy changes in anticipation of a future systemic crisis. [ABSTRACT FROM AUTHOR]

Background: Although the romantic partners of diplomatic personnel frequently accompany their spouses to overseas postings and face the challenges of having to adjust to new cultures and separation from friends and family, they have rarely been the focus of academic research. This study explores the lived experiences of the partners/spouses of diplomatic personnel from the United Kingdom's Foreign, Commonwealth and Development Office (FCDO) during the COVID-19 pandemic. Methods: Partners of FCDO staff took part in semi-structured interviews about how COVID-19 had affected their lives and their perceptions of the organisation's response to the pandemic. Thematic analysis was used to analyse the data. Results: Eleven partners of FCDO staff took part, who between them had lived in 14 different countries during the pandemic. The analysis identified six key themes: deployment-specific challenges such as travel restrictions, quarantine and evacuation; children; impacts of the pandemic including financial and psychological; perceptions of the organisational response to COVID-19; support and help-seeking; and suggestions for the future. Overall participants reported experiencing a number of challenges, many of which left them feeling powerless and not in control of their own lives. Participants frequently described a lack of clarity around policies and support. Social support appeared to be valuable, but many participants wanted more support from the organisation and from informal networks. Conclusions: Diplomatic (and similar) organisations could enhance the wellbeing of the partners of their staff through improved communication and support. Keeping families informed about restrictions, requirements, policies and available help during a crisis, and reaching out to them to offer advice and support, would likely be beneficial. It is important that lessons are learned from the COVID-19 crisis in order for organisations to be able to support their employees and families if another prolonged crisis were to occur. [ABSTRACT FROM AUTHOR]

In England (UK), at the start of the COVID-19 pandemic the public were required to reduce their physical contacts to slow the spread of COVID-19. We investigated the factors associated with children having: 1) close contact with family members from outside their household ('non-adherent behaviour'); and 2) low well-being (Revised Child Anxiety and Depression Scale). We conducted an online cross-sectional survey, completed at any location of the participant's choice between 8 and 11 June 2020 in parents (n = 2,010) who were aged eighteen years or over and had a school-aged child (4–18 years old). Parents reported that 15% (n = 309) of children had non-adherent contact and that 26% (n = 519) had low well-being. We used a series of binary logistic regressions to investigate associations between outcomes and child and parent characteristics. Children had higher odds of having non-household contact when they had special educational needs [adjusted odds ratio, 2.19 (95% CI, 1.47 to 3.27)], lower well-being [2.65 (95% CI, 2.03 to 3.46)], were vulnerable to COVID-19 [2.17 (95% CI, 1.45 to 3.25)], lived with someone who was over 70 years old [2.56 (95% CI, 1.55 to 4.24)] and their parent had low well-being [1.94 (95% CI, 1.45 to 2.58)]. Children had higher odds of lower well-being when they had special educational needs [4.13 (95% CI, 2.90 to 5.87)], were vulnerable to COVID-19 [3.06 (95% CI, 2.15 to 4.36)], lived with someone else who was vulnerable to COVID-19 [2.08 (95% CI, 1.64 to 2.64)], or lived with someone who was over 70 years old [2.41 (95% CI, 1.51 to 3.83)]. Many children came into contact with non-household family members, mainly for childcare. Factors relating to COVID-19, children's well-being and education were also important. If school closures are needed in future, addressing these issues may help reduce contact. [ABSTRACT FROM AUTHOR]

Background: The impact of COVID-19 virus on menstrual cycles in unvaccinated women is limited. Objective: To investigate the prevalence of changes to menstrual cycle characteristics, hormonal symptoms and lifestyle changes prior to and during the COVID-19 pandemic. Methods: A retrospective online cross-sectional survey completed by social media users between July 2020 to October 2020. Participants were living in the United Kingdom (UK), premenopausal status and, or over 18 years of age. Main outcome(s) and measures(s): The primary outcome was to assess changes to menstrual cycle characteristics during the pandemic following the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). Secondary outcomes included assessment of hormonal and lifestyle changes. Results: 15,611 social media users completed the survey. Of which, 75% of participants experienced a change in their menstrual cycle, with significantly greater proportions reporting irregular menstrual cycles (P<0·001), bleeding duration more than seven days (P<0·001), longer mean cycle length (P<0·001) and overall bleeding duration (P<0·001). Over half the participants reported worsening of premenstrual symptoms including low mood/depression, anxiety and irritability. When stratified according to COVID-19 infection, there was no significant difference in menstrual cycle changes. Conclusion: The COVID-19 pandemic resulted in considerable variation in menstrual cycle characteristics and hormonal symptoms. This appears to be related to societal and lifestyle changes resulting from the pandemic, rather than to the virus itself. We believe this may have an impact on the individual, as well as national economy, healthcare, and population levels, and therefore suggest this should be taken into consideration by governments, healthcare providers and employers when developing pandemic recovery plans. [ABSTRACT FROM AUTHOR]

The economic landscape of the United Kingdom has been significantly shaped by the intertwined issues of Brexit, COVID-19, and their interconnected impacts. Despite the country's robust and diverse economy, the disruptions caused by Brexit and the COVID-19 pandemic have created uncertainty and upheaval for both businesses and individuals. Recognizing the magnitude of these challenges, academic literature has directed its attention toward conducting immediate research in this crucial area. This study sets out to investigate key economic factors that have influenced various sectors of the UK economy and have broader economic implications within the context of Brexit and COVID-19. The factors under scrutiny include the unemployment rate, GDP index, earnings, and trade. To accomplish this, a range of data analysis tools and techniques were employed, including the Box-Jenkins method, neural network modeling, Google Trend analysis, and Twitter-sentiment analysis. The analysis encompassed different periods: pre-Brexit (2011-2016), Brexit (2016-2020), the COVID-19 period, and post-Brexit (2020-2021). The findings of the analysis offer intriguing insights spanning the past decade. For instance, the unemployment rate displayed a downward trend until 2020 but experienced a spike in 2021, persisting for a six-month period. Meanwhile, total earnings per week exhibited a gradual increase over time, and the GDP index demonstrated an upward trajectory until 2020 but declined during the COVID-19 period. Notably, trade experienced the most significant decline following both Brexit and the COVID-19 pandemic. Furthermore, the impact of these events exhibited variations across the UK's four regions and twelve industries. Wales and Northern Ireland emerged as the regions most affected by Brexit and COVID-19, with industries such as accommodation, construction, and wholesale trade particularly impacted in terms of earnings and employment levels. Conversely, industries such as finance, science, and health demonstrated an increased contribution to the UK's total GDP in the post-Brexit period, indicating some positive outcomes. It is worth highlighting that the impact of these economic factors was more pronounced on men than on women. Among all the variables analyzed, trade suffered the most severe consequences in the UK. By early 2021, the macroeconomic situation in the country was characterized by a simple dynamic: economic demand rebounded at a faster pace than supply, leading to shortages, bottlenecks, and inflation. The findings of this research carry significant value for the UK government and businesses, empowering them to adapt and innovate based on forecasts to navigate the challenges posed by Brexit and COVID-19. By doing so, they can promote long-term economic growth and effectively address the disruptions caused by these interrelated issues. [ABSTRACT FROM AUTHOR]

Introduction: At the start of the COVID-19 pandemic there was an urgent need to identify individuals at highest risk of severe outcomes, such as hospitalisation and death following infection. The QCOVID risk prediction algorithms emerged as key tools in facilitating this which were further developed during the second wave of the COVID-19 pandemic to identify groups of people at highest risk of severe COVID-19 related outcomes following one or two doses of vaccine. Objectives: To externally validate the QCOVID3 algorithm based on primary and secondary care records for Wales, UK. Methods: We conducted an observational, prospective cohort based on electronic health care records for 1.66m vaccinated adults living in Wales on 8th December 2020, with follow-up until 15th June 2021. Follow-up started from day 14 post vaccination to allow the full effect of the vaccine. Results: The scores produced by the QCOVID3 risk algorithm showed high levels of discrimination for both COVID-19 related deaths and hospital admissions and good calibration (Harrell C statistic: ≥ 0.828). Conclusion: This validation of the updated QCOVID3 risk algorithms in the adult vaccinated Welsh population has shown that the algorithms are valid for use in the Welsh population, and applicable on a population independent of the original study, which has not been previously reported. This study provides further evidence that the QCOVID algorithms can help inform public health risk management on the ongoing surveillance and intervention to manage COVID-19 related risks. [ABSTRACT FROM AUTHOR]

Introduction: Assessment of inpatient mortality risk in COVID-19 patients is important for guiding clinical decision-making. High sensitivity cardiac troponin T (hs-cTnT) is a biomarker of cardiac injury associated with a worse prognosis in COVID-19. We explored how hs-cTnT could potentially be used in clinical practice for ruling in and ruling out mortality in COVID-19. Method: We tested the diagnostic value of hs-cTnT in laboratory-confirmed COVID-19 patients (≥18 years old) admitted to the Royal Berkshire Hospital (UK) between 1st March and 10th May 2020. A normal hs-cTnT was defined as a value within the 99th percentile of healthy individuals (≤14 ng/L), and an elevated hs-cTnT was defined as >14 ng/L. Adverse clinical outcome was defined as inpatient mortality related to COVID-19. Results: A total of 191 COVID-19 patients (62% male; age 66±16 years) had hs-cTnT measured on admission. Of these patients, 124 (65%) had elevated hs-cTnT and 67 (35%) had normal hs-cTnT. On a group level, patients with elevated hs-cTnT had worse inpatient survival (p = 0.0014; Kaplan-Meier analysis) and higher risk of inpatient mortality (HR 5.84 [95% CI 1.29–26.4]; p = 0.02; Cox multivariate regression) compared to patients with normal hs-cTnT. On a per-patient level, a normal hs-cTnT had a negative predictive value of 94% (95% CI: 85–98%) for ruling out mortality, whilst an elevated hs-cTnT had a low positive predictive value of 38% (95% CI: 39–47%) for ruling in mortality. Conclusions: In this study cohort of COVID-19 patients, the potential clinical utility of hs-cTnT appears to rest in ruling out inpatient mortality. This finding, if prospectively validated in a larger study, may allow hs-cTnT to become an important biomarker to facilitate admission-avoidance and early safe discharge. [ABSTRACT FROM AUTHOR]

The main drivers of COVID-19 disease severity and the impact of COVID-19 on long-term health after recovery are yet to be fully understood. Medical imaging studies investigating COVID-19 to date have mostly been limited to small datasets and post-hoc analyses of severe cases. The UK Biobank recruited recovered SARS-CoV-2 positive individuals (n = 967) and matched controls (n = 913) who were extensively imaged prior to the pandemic and underwent follow-up scanning. In this study, we investigated longitudinal changes in body composition, as well as the associations of pre-pandemic image-derived phenotypes with COVID-19 severity. Our longitudinal analysis, in a population of mostly mild cases, associated a decrease in lung volume with SARS-CoV-2 positivity. We also observed that increased visceral adipose tissue and liver fat, and reduced muscle volume, prior to COVID-19, were associated with COVID-19 disease severity. Finally, we trained a machine classifier with demographic, anthropometric and imaging traits, and showed that visceral fat, liver fat and muscle volume have prognostic value for COVID-19 disease severity beyond the standard demographic and anthropometric measurements. This combination of image-derived phenotypes from abdominal MRI scans and ensemble learning to predict risk may have future clinical utility in identifying populations at-risk for a severe COVID-19 outcome. [ABSTRACT FROM AUTHOR]

Despite undeniable hardship, the onset of the COVID-19 pandemic also saw an outpour of community solidarity and mutual aid towards those in need. This study explored why people participated in mutual aid during the pandemic as well as the factors that contributed to continued involvement and/or its decline. We conducted remote interviews with 17 people in South-east England who had been involved in volunteering and local community mutual aid support groups during the first UK lockdown from March to May 2020. Using thematic analysis, we identified two themes: 1) The emergence of social groups and their psychosocial effects, and 2) Enduring connections and barriers to continued participation. Participants often reported an emergent shared identity, preferring the localised nature of these groups and the associated mutual nature of support. They also reported intentions to continue providing such support, should the need arise again, and any barriers to continued involvement in mutual aid were better explained by structural and systemic issues, rather than individual motivational factors. [ABSTRACT FROM AUTHOR]

Throughout the COVID-19 pandemic, valuable datasets have been collected on the effects of the virus SARS-CoV-2. In this study, we combined whole genome sequencing data with clinical data (including clinical outcomes, demographics, comorbidity, treatment information) for 929 patient cases seen at a large UK hospital Trust between March 2020 and May 2021. We identified associations between acute physiological status and three measures of disease severity; admission to the intensive care unit (ICU), requirement for intubation, and mortality. Whilst the maximum National Early Warning Score (NEWS2) was moderately associated with severe COVID-19 (A = 0.48), the admission NEWS2 was only weakly associated (A = 0.17), suggesting it is ineffective as an early predictor of severity. Patient outcome was weakly associated with myriad factors linked to acute physiological status and human genetics, including age, sex and pre-existing conditions. Overall, we found no significant links between viral genomics and severe outcomes, but saw evidence that variant subtype may impact relative risk for certain sub-populations. Specific mutations of SARS-CoV-2 appear to have little impact on overall severity risk in these data, suggesting that emerging SARS-CoV-2 variants do not result in more severe patient outcomes. However, our results show that determining a causal relationship between mutations and severe COVID-19 in the viral genome is challenging. Whilst improved understanding of the evolution of SARS-CoV-2 has been achieved through genomics, few studies on how these evolutionary changes impact on clinical outcomes have been seen due to complexities associated with data linkage. By combining viral genomics with patient records in a large acute UK hospital, this study represents a significant resource for understanding risk factors associated with COVID-19 severity. However, further understanding will likely arise from studies of the role of host genetics on disease progression. [ABSTRACT FROM AUTHOR]

Introduction: Antivirals, such as molnupiravir, and SARS-CoV-2 neutralising monoclonal antibodies (nMAbs), such as sotrovimab, reduced the risk of hospitalisation and death in clinical trials of high-risk non-hospitalised patients with Covid-19. However, the real-world benefits of these drugs are unclear. Aims: To evaluate the characteristics and outcomes of high-risk patients referred for outpatient antiviral or nMAb treatment for symptomatic Covid-19. Methods: The records of patients referred to a large UK Covid Medicines Delivery Unit (CMDU) over nine weeks (December 2021-February 2022) were reviewed. Data were collected on demographics, referral indications, vaccination, deprivation, treatment, complications, hospital admission, and mortality. Results: 1820 patients were referred to the CMDU, with 604 (33.2%) suitable for further assessment. 169 patients received sotrovimab, 80 patients received molnupiravir, 70 patients declined treatment, and 266 were ineligible for treatment because of resolving symptoms. There were trends towards higher proportions of female and white patients, lower deprivation scores, and malignancy- or transplant-related indications in the groups receiving treatment compared with untreated patients. Covid-19-related hospitalisations occurred in 1.2% of the treated group and 3.0% of the untreated group indicating a potential treatment effect, however Covid-related hospitalisations were lower than reported in the original clinical trials (2.2% compared with 7–10%). Conclusion: The referral pathways for outpatient treatment of Covid-19 are inefficient, and the UK system may not be serving all groups equitably. Hospitalisation with Covid-19 was rare regardless of treatment. Ongoing service evaluation is required to ensure efficient use of resources for the outpatient management of Covid-19. [ABSTRACT FROM AUTHOR]

Introduction: As mortality rates from COVID-19 disease fall, the high prevalence of long-term sequelae (Long COVID) is becoming increasingly widespread, challenging healthcare systems globally. Traditional pathways of care for Long Term Conditions (LTCs) have tended to be managed by disease-specific specialties, an approach that has been ineffective in delivering care for patients with multi-morbidity. The multi-system nature of Long COVID and its impact on physical and psychological health demands a more effective model of holistic, integrated care. The evolution of integrated care systems (ICSs) in the UK presents an important opportunity to explore areas of mutual benefit to LTC, multi-morbidity and Long COVID care. There may be benefits in comparing and contrasting ICPs for Long COVID with ICPs for other LTCs. Methods and analysis: This study aims to evaluate health services requirements for ICPs for Long COVID and their applicability to other LTCs including multi-morbidity and the overlap with medically not yet explained symptoms (MNYES). The study will follow a Delphi design and involve an expert panel of stakeholders including people with lived experience, as well as clinicians with expertise in Long COVID and other LTCs. Study processes will include expert panel and moderator panel meetings, surveys, and interviews. The Delphi process is part of the overall STIMULATE-ICP programme, aimed at improving integrated care for people with Long COVID. Ethics and dissemination: Ethical approval for this Delphi study has been obtained (Research Governance Board of the University of York) as have approvals for the other STIMULATE-ICP studies. Study outcomes are likely to inform policy for ICPs across LTCs. Results will be disseminated through scientific publication, conference presentation and communications with patients and stakeholders involved in care of other LTCs and Long COVID. Registration: Researchregistry: https://www.researchregistry.com/browse-the-registry#home/registrationdetails/6246bfeeeaaed6001f08dadc/. [ABSTRACT FROM AUTHOR]

Objectives: The sense of belonging is a fundamental human need. Enacting it through face-to-face social activities was no longer possible during the COVID-19 pandemic. In this study, we investigate how the sense of belonging, and how it is enacted, changed longitudinally amongst older adults in the UK. In addition, we examine the interplay of the sense of belonging and resilience over time. Methods: We employed a longitudinal qualitative research design to explore the experiences of older adults during one year of the COVID-19 pandemic (April 2020-April 2021). The analysis was undertaken with constructivist grounded theory. Findings: Before the pandemic older adults were free to engage in social relationships with family and friends, often enacted within social activity groups where they felt valued and gained positive experiences. During the pandemic face to face enactment of belongingness was reduced; adjustments needed to be made to maintain the sense of belonging. The experience of older adults was heterogeneous. We examine three themes. First, how belongingness was enacted prior to the pandemic. Examples include: family holidays, visiting each other, sports activities, eating with friends and family, and visiting cultural events. Second, how participants adapted and maintained their social involvement. Examples include: distanced face-to-face activities; and learning new technology. Third, for some, a belongingness gap emerged and persisted. There was an irretrievable loss of family members or friends, the closure of social groups, or withdrawal from groups as priorities changed. As a consequence, of challenged belongingness, participants expressed increased loneliness, anxiety, social isolation, frustration and, feelings of depression. For many, the disrupted sense of belonging no longer fostered resilience, and some previously resilient participants were no longer resilient. [ABSTRACT FROM AUTHOR]

We present our agent-based CoronAvirus Lifelong Modelling and Simulation (CALMS) model that aspires to predict the lifelong impacts of Covid-19 on the health and economy of a population. CALMS considers individual characteristics as well as comorbidities in calculating the risk of infection and severe disease. We conduct two sets of experiments aiming at demonstrating the validity and capabilities of CALMS. We run simulations retrospectively and validate the model outputs against hospitalisations, ICU admissions and fatalities in a UK population for the period between March and September 2020. We then run simulations for the lifetime of the cohort applying a variety of targeted intervention strategies and compare their effectiveness against the baseline scenario where no intervention is applied. Four scenarios are simulated with targeted vaccination programmes and periodic lockdowns. Vaccinations are targeted first at individuals based on their age and second at vulnerable individuals based on their health status. Periodic lockdowns, triggered by hospitalisations, are tested with and without vaccination programme in place. Our results demonstrate that periodic lockdowns achieve reductions in hospitalisations, ICU admissions and fatalities of 6-8% compared to the baseline scenario, with an associated intervention cost of £173 million per 1,000 people and targeted vaccination programmes achieve reductions in hospitalisations, ICU admissions and fatalities of 89-90%, compared to the baseline scenario, with an associated intervention cost of £51,924 per 1,000 people. We conclude that periodic lockdowns alone are ineffective at reducing health-related outputs over the long-term and that vaccination programmes which target only the clinically vulnerable are sufficient in providing healthcare protection for the population as a whole. [ABSTRACT FROM AUTHOR]

Studies have reported reduced cognitive function following COVID-19 illness, mostly from hospital settings with short follow-up times. This study recruited non-hospitalized COVID-19 patients from a general population to study prevalence of late cognitive impairment and associations with initial symptoms. We invited patients with PCR-confirmed COVID-19. A postal questionnaire addressed basic demographics, initial COVID-19 symptoms and co-morbidity about 4 months after diagnosis. About 7 months later, we conducted cognitive tests using the Cambridge Neuropsychological Test Automated Battery, comprising four tests for short-term memory, attention and executive function. We present descriptive statistics using z-scores relative to UK population norms and defined impairment as z-score <-1.5. We used multivariable logistic regression with impairment as outcome. Continuous domain scores were analysed by multiple linear regression. Of the initial 458 participants; 305 were invited, and 234 (77%) completed cognitive testing. At median 11 (range 8–13) months after PCR positivity, cognitive scores for short term memory, visuospatial processing, learning and attention were lower than norms (p≤0.001). In each domain, 4–14% were cognitively impaired; 68/232 (29%) were impaired in ≥ 1 of 4 tests. There was no association between initial symptom severity and impairment. Multivariable linear regression showed association between spatial working memory and initial symptom load (6–9 symptoms vs. 0–5, coef. 4.26, 95% CI: 0.65; 7.86). No other dimension scores were associated with symptom load. At median 11 months after out-of-hospital SARS-Cov-2 infection, minor cognitive impairment was seen with little association between COVID-19 symptom severity and outcome. [ABSTRACT FROM AUTHOR]

Making use of a state space framework, we present a stochastic generalization of the SIRD model, where the mortality, infection, and underreporting rates change over time. A new format to the errors in the Susceptible-Infected-Recovered-Dead compartments is also presented, that permits reinfection. The estimated trajectories and (out-of-sample) forecasts of all these variables are presented with their confidence intervals. The model only uses as inputs the number of reported cases and deaths, and was applied for the UK from April, 2020 to Sep, 2021 (daily data). The estimated infection rate has shown a trajectory in waves very compatible with the emergence of new variants and adopted social measures. The estimated mortality rate has shown a significant descendant behaviour in 2021, which we attribute to the vaccination program, and the estimated underreporting rate has been considerably volatile, with a downward tendency, implying that, on average, more people are testing than in the beginning of the pandemic. The evolution of the proportions of the population divided into susceptible, infected, recovered and dead groups are also shown with their confidence intervals and forecast, along with an estimation of the amount of reinfection that, according to our model, has become quite significant in 2021. Finally, the estimated trajectory of the effective reproduction rate has proven to be very compatible with the real number of cases and deaths. Its forecasts with confident intervals are also presented. [ABSTRACT FROM AUTHOR]

The covid-19 global pandemic has significantly impacted on the daily lives of people across the world. One consequence of this has been significant distortion to the speed at which time feels like it is passing during day-to-day life in comparison with prior to the pandemic. The current study sought to further understanding of the impact of the pandemic on temporal experience by exploring individual differences in the subjective length of the first 12 months of the pandemic in the UK. Using an online questionnaire, subjective judgments of the perceived length of the preceding 12 months were taken. In addition, measures of affect, task load and satisfaction with current levels of social interaction, physical activity, conformity with regulations, perceived covid risk and shielding status were taken. The results showed that only 9% of participants reported that the preceding 12 months felt like 12 months. The majority of participants (57%) reported that it felt like the pandemic had lasted for longer than 12 months, and this feeling was stronger for those who indicated greater levels of depression and anxiety, reduced physical activity, reduced satisfaction with social interaction and being advised to shield. [ABSTRACT FROM AUTHOR]

Background: Recent studies indicate that vitamin D supplementation may decrease respiratory tract infections, but the association between vitamin D and COVID-19 is still unclear. Objective: To explore the association between vitamin D status and infections, hospitalisation, and mortality due to COVID-19. Methods: We used UK Biobank, a nationwide cohort of 500,000 individuals aged between 40 and 69 years at recruitment between 2006 and 2010. We included people with at least one serum vitamin D test, living in England with linked primary care and inpatient records. The primary exposure was serum vitamin D status measured at recruitment, defined as deficiency at <25 nmol/L, insufficiency at 25–49 nmol/L and sufficiency at ≥ 50 nmol/L. Secondary exposures were self-reported or prescribed vitamin D supplements. The primary outcome was laboratory-confirmed or clinically diagnosed SARS-CoV-2 infections. The secondary outcomes included hospitalisation and mortality due to COVID-19. We used multivariable Cox regression models stratified by summertime months and non-summertime months, adjusting for demographic factors and underlying comorbidities. Results: We included 307,512 participants (54.9% female, 55.9% over 70 years old) in our analysis. During summertime months, weak evidence existed that the vitamin D deficiency group had a lower hazard of being diagnosed with COVID-19 (hazard ratio [HR] = 0.86, 95% confidence interval [CI] = 0.77–0.95). During non-summertime, the vitamin D deficiency group had a higher hazard of COVID-19 compared with the vitamin D sufficient group (HR = 1.14, 95% CI = 1.01–1.30). No evidence was found that vitamin D deficiency or insufficiency was associated with either hospitalisation or mortality due to COVID-19 in any time strata. Conclusion: We found no evidence of an association between historical vitamin D status and hospitalisation or mortality due to COVID-19, along with inconsistent results for any association between vitamin D and diagnosis of COVID-19. However, studies using more recent vitamin D measurements and systematic COVID-19 testing are needed. [ABSTRACT FROM AUTHOR]

Background: Confidence in the central UK Government has declined since the beginning of the COVID-19 pandemic, and while this may be linked to specific government actions to curb the spread of the virus, understanding is still incomplete. Examining public opinion is important, as research suggests that low confidence in government increases the extent of non-compliance with infection-dampening rules (for instance, social distancing); however, the detailed reasons for this association are still unclear. Methods: To understand public opinion on the central UK government during the first phase of the COVID-19 pandemic, we used structural topic modeling, a text mining technique, to extract themes from over 4000 free-text survey responses, collected between 14 October and 26 November 2020. Results: We identified eleven topics, among which were topics related to perceived government corruption and cronyism, complaints about inconsistency in rules and messaging, lack of clear planning, and lack of openness and transparency. Participants reported that elements of the government's approach had made it difficult to comply with guidelines (e.g., changing rules) or were having impacts on mental wellbeing (e.g., inability to plan for the future). Conclusions: Results suggested that consistent, transparent communication and messaging from the government is critical to improving compliance with measures to contain the virus, as well as protecting mental health during health emergencies. [ABSTRACT FROM AUTHOR]

Background: Long Covid is a public health concern that needs defining, quantifying, and describing. We aimed to explore the initial and ongoing symptoms of Long Covid following SARS-CoV-2 infection and describe its impact on daily life. Methods: We collected self-reported data through an online survey using convenience non-probability sampling. The survey enrolled adults who reported lab-confirmed (PCR or antibody) or suspected COVID-19 who were not hospitalised in the first two weeks of illness. This analysis was restricted to those with self-reported Long Covid. Univariate comparisons between those with and without confirmed COVID-19 infection were carried out and agglomerative hierarchical clustering was used to identify specific symptom clusters, and their demographic and functional correlates. Results: We analysed data from 2550 participants with a median duration of illness of 7.6 months (interquartile range (IQR) 7.1–7.9). 26.5% reported lab-confirmation of infection. The mean age was 46.5 years (standard deviation 11 years) with 82.8% females and 79.9% of participants based in the UK. 89.5% described their health as good, very good or excellent before COVID-19. The most common initial symptoms that persisted were exhaustion, chest pressure/tightness, shortness of breath and headache. Cognitive dysfunction and palpitations became more prevalent later in the illness. Most participants described fluctuating (57.7%) or relapsing symptoms (17.6%). Physical activity, stress, and sleep disturbance commonly triggered symptoms. A third (32%) reported they were unable to live alone without any assistance at six weeks from start of illness. 16.9% reported being unable to work solely due to COVID-19 illness. 37.0% reported loss of income due to illness, and 64.4% said they were unable to perform usual activities/duties. Acute systems clustered broadly into two groups: a majority cluster (n = 2235, 88%) with cardiopulmonary predominant symptoms, and a minority cluster (n = 305, 12%) with multisystem symptoms. Similarly, ongoing symptoms broadly clustered in two groups; a majority cluster (n = 2243, 88.8%) exhibiting mainly cardiopulmonary, cognitive symptoms and exhaustion, and a minority cluster (n = 283, 11.2%) exhibiting more multisystem symptoms. Belonging to the more severe multisystem cluster was associated with more severe functional impact, lower income, younger age, being female, worse baseline health, and inadequate rest in the first two weeks of the illness, with no major differences in the cluster patterns when restricting analysis to the lab-confirmed subgroup. Conclusion: This is an exploratory survey of Long Covid characteristics. Whilst this is a non-representative population sample, it highlights the heterogeneity of persistent symptoms, and the significant functional impact of prolonged illness following confirmed or suspected SARS-CoV-2 infection. To study prevalence, predictors and prognosis, research is needed in a representative population sample using standardised case definitions. [ABSTRACT FROM AUTHOR]

Background: The Covid-19 pandemic in the United Kingdom has seen two waves; the first starting in March 2020 and the second in late October 2020. It is not known whether outcomes for those admitted with severe Covid were different in the first and second waves. Methods: The study population comprised all patients admitted to a 1,500-bed London Hospital Trust between March 2020 and March 2021, who tested positive for Covid-19 by PCR within 3-days of admissions. Primary outcome was death within 28-days of admission. Socio-demographics (age, sex, ethnicity), hypertension, diabetes, obesity, baseline physiological observations, CRP, neutrophil, chest x-ray abnormality, remdesivir and dexamethasone were incorporated as co-variates. Proportional subhazards models compared mortality risk between wave 1 and wave 2. Cox-proportional hazard model with propensity score adjustment were used to compare mortality in patients prescribed remdesivir and dexamethasone. Results: There were 3,949 COVID-19 admissions, 3,195 hospital discharges and 733 deaths. There were notable differences in age, ethnicity, comorbidities, and admission disease severity between wave 1 and wave 2. Twenty-eight-day mortality was higher during wave 1 (26.1% versus 13.1%). Mortality risk adjusted for co-variates was significantly lower in wave 2 compared to wave 1 [adjSHR 0.49 (0.37, 0.65) p<0.001]. Analysis of treatment impact did not show statistically different effects of remdesivir [HR 0.84 (95%CI 0.65, 1.08), p = 0.17] or dexamethasone [HR 0.97 (95%CI 0.70, 1.35) p = 0.87]. Conclusion: There has been substantial improvements in COVID-19 mortality in the second wave, even accounting for demographics, comorbidity, and disease severity. Neither dexamethasone nor remdesivir appeared to be key explanatory factors, although there may be unmeasured confounding present. [ABSTRACT FROM AUTHOR]

Epidemiological models used to inform government policies aimed to reduce the contagion of COVID-19, assume that the reproduction number is reduced through Non-Pharmaceutical Interventions (NPIs) leading to physical distancing. Available data in the UK show an increase in physical distancing before the NPIs were implemented and a fall soon after implementation. We aimed to estimate the effect of people's behaviour on the epidemic curve and the effect of NPIs taking into account this behavioural component. We have estimated the effects of confirmed daily cases on physical distancing and we used this insight to design a behavioural SEIR model (BeSEIR), simulated different scenaria regarding NPIs and compared the results to the standard SEIR. Taking into account behavioural insights improves the description of the contagion dynamics of the epidemic significantly. The BeSEIR predictions regarding the number of infections without NPIs were several orders of magnitude less than the SEIR. However, the BeSEIR prediction showed that early measures would still have an important influence in the reduction of infections. The BeSEIR model shows that even with no intervention the percentage of the cumulative infections within a year will not be enough for the epidemic to resolve due to a herd immunity effect. On the other hand, a standard SEIR model significantly overestimates the effectiveness of measures. Without taking into account the behavioural component, the epidemic is predicted to be resolved much sooner than when taking it into account and the effectiveness of measures are significantly overestimated. [ABSTRACT FROM AUTHOR]

This study explored relations between COVID-19 news source, trust in COVID-19 information source, and COVID-19 health literacy in 194 STEM-oriented adolescents and young adults from the US and the UK. Analyses suggest that adolescents use both traditional news (e.g., TV or newspapers) and social media news to acquire information about COVID-19 and have average levels of COVID-19 health literacy. Hierarchical linear regression analyses suggest that the association between traditional news media and COVID-19 health literacy depends on participants' level of trust in their government leader. For youth in both the US and the UK who used traditional media for information about COVID-19 and who have higher trust in their respective government leader (i.e., former US President Donald Trump and UK Prime Minister Boris Johnson) had lower COVID-19 health literacy. Results highlight how youth are learning about the pandemic and the importance of not only considering their information source, but also their levels of trust in their government leaders. [ABSTRACT FROM AUTHOR]

We apply Bayesian inference methods to a suite of distinct compartmental models of generalised SEIR type, in which diagnosis and quarantine are included via extra compartments. We investigate the evidence for a change in lethality of COVID-19 in late autumn 2020 in the UK, using age-structured, weekly national aggregate data for cases and mortalities. Models that allow a (step-like or graded) change in infection fatality rate (IFR) have consistently higher model evidence than those without. Moreover, they all infer a close to two-fold increase in IFR. This value lies well above most previously available estimates. However, the same models consistently infer that, most probably, the increase in IFR preceded the time window during which variant B.1.1.7 (alpha) became the dominant strain in the UK. Therefore, according to our models, the caseload and mortality data do not offer unequivocal evidence for higher lethality of a new variant. We compare these results for the UK with similar models for Germany and France, which also show increases in inferred IFR during the same period, despite the even later arrival of new variants in those countries. We argue that while the new variant(s) may be one contributing cause of a large increase in IFR in the UK in autumn 2020, other factors, such as seasonality, or pressure on health services, are likely to also have contributed. [ABSTRACT FROM AUTHOR]

Background: Novel viral pandemics present significant challenges to global public health. Non-pharmaceutical interventions (e.g. social distancing) are an important means through which to control the transmission of such viruses. One of the key factors determining the effectiveness of such measures is the level of public adherence to them. Research to date has focused on quantitative exploration of adherence and non-adherence, with a relative lack of qualitative exploration of the reasons for non-adherence. Objective: To explore participants' perceptions of non-adherence to COVID-19 policy measures by self and others in the UK, focusing on perceived reasons for non-adherence. Methods: Qualitative study comprising 12 focus groups conducted via video-conferencing between 25th September and 13th November 2020. Participants were 51 UK residents aged 18 and above, reflecting a range of ages, genders and race/ethnicities. Data were analysed using a thematic approach. Results: Participants reported seeing an increase in non-adherence in others over the course of the pandemic. Reports of non-adherence in self were lower than reports of non-adherence in others. Analysis revealed six main themes related to participants' reported reasons for non-adherence in self and others: (1) 'Alert fatigue' (where people find it difficult to follow, or switch off from, information about frequently changing rules or advice) (2) Inconsistent rules (3) Lack of trust in government (4) Learned Helplessness (5) Resistance and rebelliousness (6)The impact of vaccines on risk perception. Participants perceived a number of systemic failures (e.g. unclear policy, untrustworthy policymakers) to strongly contribute to two forms non-adherence—violations and errors. Conclusion: Findings suggest that latent and systemic failures—in the form of policy decisions that are commonly experienced as too changeable, inconsistent and confusing, and policy makers that are commonly perceived as untrustworthy–may play a significant role in creating the conditions that enable or encourage non-adherence. [ABSTRACT FROM AUTHOR]

Background: Data to better understand and manage the COVID-19 pandemic is urgently needed. However, there are gaps in information stored within even the best routinely-collected electronic health records (EHR) including test results, remote consultations for suspected COVID-19, shielding, physical activity, mental health, and undiagnosed or untested COVID-19 patients. Observational and Pragmatic Research Institute (OPRI) Singapore and Optimum Patient Care (OPC) UK established Platform C19, a research database combining EHR data and bespoke patient questionnaire. We describe the demographics, clinical characteristics, patient behavior, and impact of the COVID-19 pandemic using data within Platform C19. Methods: EHR data from Platform C19 were extracted from 14 practices across UK participating in the OPC COVID-19 Quality Improvement program on a continuous, monthly basis. Starting 7th August 2020, consenting patients aged 18–85 years were invited in waves to fill an online questionnaire. Descriptive statistics were summarized using all data available up to 22nd January 2021. Findings: From 129,978 invitees, 31,033 responded. Respondents were predominantly female (59.6%), white (93.5%), and current or ex-smokers (52.6%). Testing for COVID-19 was received by 23.8% of respondents, of which 7.9% received positive results. COVID-19 symptoms lasted ≥4 weeks in 19.5% of COVID-19 positive respondents. Up to 39% respondents reported a negative impact on questions regarding their mental health. Most (67%-76%) respondents with asthma, Chronic Obstructive Pulmonary Disease (COPD), diabetes, heart, or kidney disease reported no change in the condition of their diseases. Interpretation: Platform C19 will enable research on key questions relating to COVID-19 pandemic not possible using EHR data alone. [ABSTRACT FROM AUTHOR]

Public perceptions of pandemic viral threats and government policies can influence adherence to containment, delay, and mitigation policies such as physical distancing, hygienic practices, use of physical barriers, uptake of testing, contact tracing, and vaccination programs. The UK COVID-19 Public Experiences (COPE) study aims to identify determinants of health behaviour using the Capability, Opportunity, Motivation (COM-B) model using a longitudinal mixed-methods approach. Here, we provide a detailed description of the demographic and self-reported health characteristics of the COPE cohort at baseline assessment, an overview of data collected, and plans for follow-up of the cohort. The COPE baseline survey was completed by 11,113 UK adult residents (18+ years of age). Baseline data collection started on the 13th of March 2020 (10-days before the introduction of the first national COVID-19 lockdown in the UK) and finished on the 13th of April 2020. Participants were recruited via the HealthWise Wales (HWW) research registry and through social media snowballing and advertising (Facebook®, Twitter®, Instagram®). Participants were predominantly female (69%), over 50 years of age (68%), identified as white (98%), and were living with their partner (68%). A large proportion (67%) had a college/university level education, and half reported a pre-existing health condition (50%). Initial follow-up plans for the cohort included in-depth surveys at 3-months and 12-months after the first UK national lockdown to assess short and medium-term effects of the pandemic on health behaviour and subjective health and well-being. Additional consent will be sought from participants at follow-up for data linkage and surveys at 18 and 24-months after the initial UK national lockdown. A large non-random sample was recruited to the COPE cohort during the early stages of the COVID-19 pandemic, which will enable longitudinal analysis of the determinants of health behaviour and changes in subjective health and well-being over the course of the pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has necessitated physical distancing which is expected to continue in some form for the foreseeable future. Physical distancing policies have increased reliance on digital forms of social connection and there are widespread concerns about social isolation and mental health in this context. This qualitative study sought to understand how loneliness was experienced during physical distancing in the initial national UK COVID-19 lockdown. Eight individuals who reported feeling lonely during the initial lockdown were interviewed in May 2020. Interviews were analysed using reflexive thematic analysis. Four main themes were identified: (1) Loss of in-person interaction causing loneliness, (2) Constrained freedom, (3) Challenging emotions, and (4) Coping with loneliness. The loss of in-person interaction contributed to feelings of loneliness and digital interaction was viewed as an insufficient alternative. Social freedom could be constrained by distancing policies and by social contacts, contributing to strained personal relationships and feelings of frustration as part of loneliness. Fluctuations in mood and difficult emotions were experienced alongside loneliness, and distraction and seeking reconnection were commonly reported methods of coping, although they were less accessible. These findings indicate that physical distancing measures can impact loneliness due to the limitations they impose on in-person social contact and the perceived insufficiency of digital contact as a substitute. [ABSTRACT FROM AUTHOR]