An index of cancer survival to measure progress in cancer control: A tutorial.

BACKGROUND: Cancer survival is a key component to assess the overall effectiveness of healthcare systems in their cancer management efforts. A key supporting tool for planning and decision making was introduced with the development of an index of cancer survival that summarises survival for all adults and cancer types into one single estimate, but the implementation details have not been previously described. METHODS: We detail the construction of the index, including the structure, the calculation of 'sex-age-cancer' specific weights and our proposed modelling strategy to estimate net survival. We provide some practical recommendations through an illustration using a synthetic dataset ('Replica') that we generated for this purpose. An example of R code usage to estimate the index using our approach is provided. RESULTS: The 'Replica' contains 500 000 artificial cancer records that mimic a cohort of adult cancer patients diagnosed with cancer in England between 1980 and 2004. Using this dataset, we estimated an index of cancer survival at one, five, and ten years after diagnosis for five selected periods of diagnosis, and provide an example of interpretation of these results. DISCUSSION: We propose a flexible penalised regression modelling strategy to estimate the index's 'sex-age-cancer' specific cancer survival components that minimises the estimation challenge of these components. This tutorial will support researchers in constructing an index of cancer survival for their own setting, facilitating the enrichment of existing toolkits of cancer indicators to more effectively measure progress against cancer in their respective regions/countries.

The hidden toll of the pandemic: Excess mortality in non-COVID-19 hospital patients.

Seasonal infectious diseases can cause demand and supply pressures that reduce the ability of healthcare systems to provide high-quality care. This may generate negative spillover effects on the health outcomes of patients seeking medical help for unrelated reasons. Separating these indirect burdens from the direct consequences for infected patients is usually impossible due to a lack of suitable data and an absence of population testing. However, this paper finds robust empirical evidence of excess mortality among non-COVID-19 patients in an integrated public healthcare system: the English National Health Service (NHS). Analysing the forecast error in the NHS' model for predicted mortality, we find at least one additional excess death among patients who sought medical help for reasons unrelated to COVID-19 for every 42 COVID-19-related deaths in the population. We identify COVID-19 pressures as a key driver of non-COVID-19 excess mortality in NHS hospitals during the pandemic, and characterize the hospital populations and medical conditions that were disproportionately affected. Our findings have substantive relevance in shaping our understanding of the wider burden of COVID-19, and other seasonal diseases more generally, and can contribute to debates on optimal public health policy.

A Bayesian spatio-temporal model of COVID-19 spread in England.

Exploring the spatio-temporal variations of COVID-19 transmission and its potential determinants could provide a deeper understanding of the dynamics of disease spread. This study aimed to investigate the spatio-temporal spread of COVID-19 infections in England, and examine its associations with socioeconomic, demographic and environmental risk factors. We obtained weekly reported COVID-19 cases from 7 March 2020 to 26 March 2022 at Middle Layer Super Output Area (MSOA) level in mainland England from publicly available datasets. With these data, we conducted an ecological study to predict the COVID-19 infection risk and identify its associations with socioeconomic, demographic and environmental risk factors using a Bayesian hierarchical spatio-temporal model. The Bayesian model outperformed the ordinary least squares model and geographically weighted regression model in terms of prediction accuracy. The spread of COVID-19 infections over space and time was heterogeneous. Hotspots of infection risk exhibited inconsistent clustering patterns over time. Risk factors found to be positively associated with COVID-19 infection risk were: annual household income [relative risk (RR) = 1.0008, 95% Credible Interval (CI) 1.0005-1.0012], unemployment rate [RR = 1.0027, 95% CI 1.0024-1.0030], population density on the log scale [RR = 1.0146, 95% CI 1.0129-1.0164], percentage of Caribbean population [RR = 1.0022, 95% CI 1.0009-1.0036], percentage of adults aged 45-64 years old [RR = 1.0031, 95% CI 1.0024-1.0039], and particulate matter ( PM 2.5 ) concentrations [RR = 1.0126, 95% CI 1.0083-1.0167]. The study highlights the importance of considering socioeconomic, demographic, and environmental factors in analysing the spatio-temporal variations of COVID-19 infections in England. The findings could assist policymakers in developing tailored public health interventions at a localised level.

Impact of interventions to reduce nosocomial transmission of SARS-CoV-2 in English NHS Trusts: a computational modelling study.

BACKGROUND: Prior to September 2021, 55,000-90,000 hospital inpatients in England were identified as having a potentially nosocomial SARS-CoV-2 infection. This includes cases that were likely missed due to pauci- or asymptomatic infection. Further, high numbers of healthcare workers (HCWs) are thought to have been infected, and there is evidence that some of these cases may also have been nosocomially linked, with both HCW to HCW and patient to HCW transmission being reported. From the start of the SARS-CoV-2 pandemic interventions in hospitals such as testing patients on admission and universal mask wearing were introduced to stop spread within and between patient and HCW populations, the effectiveness of which are largely unknown. MATERIALS/METHODS: Using an individual-based model of within-hospital transmission, we estimated the contribution of individual interventions (together and in combination) to the effectiveness of the overall package of interventions implemented in English hospitals during the COVID-19 pandemic. A panel of experts in infection prevention and control informed intervention choice and helped ensure the model reflected implementation in practice. Model parameters and associated uncertainty were derived using national and local data, literature review and formal elicitation of expert opinion. We simulated scenarios to explore how many nosocomial infections might have been seen in patients and HCWs if interventions had not been implemented. We simulated the time period from March-2020 to July-2022 encompassing different strains and multiple doses of vaccination. RESULTS: Modelling results suggest that in a scenario without inpatient testing, infection prevention and control measures, and reductions in occupancy and visitors, the number of patients developing a nosocomial SARS-CoV-2 infection could have been twice as high over the course of the pandemic, and over 600,000 HCWs could have been infected in the first wave alone. Isolation of symptomatic HCWs and universal masking by HCWs were the most effective interventions for preventing infections in both patient and HCW populations. Model findings suggest that collectively the interventions introduced over the SARS-CoV-2 pandemic in England averted 400,000 (240,000 - 500,000) infections in inpatients and 410,000 (370,000 - 450,000) HCW infections. CONCLUSIONS: Interventions to reduce the spread of nosocomial infections have varying impact, but the package of interventions implemented in England significantly reduced nosocomial transmission to both patients and HCWs over the SARS-CoV-2 pandemic.

Insomnia symptom prevalence in England: a comparison of cross-sectional self-reported data and primary care records in the UK Biobank.

OBJECTIVES: We aimed to use a large dataset to compare self-reported and primary care measures of insomnia symptom prevalence in England and establish whether they identify participants with similar characteristics. DESIGN: Cross-sectional study with linked electronic health records (EHRs). SETTING: Primary care in England. PARTICIPANTS: 163 748 UK Biobank participants in England (aged 38-71 at baseline) with linked primary care EHRs. OUTCOME MEASURES: We compared the percentage of those self-reporting 'usually' having insomnia symptoms at UK Biobank baseline assessment (2006-2010) to those with a Read code for insomnia symptoms in their primary care records prior to baseline. We stratified prevalence in both groups by sociodemographic, lifestyle, sleep and health characteristics. RESULTS: We found that 29% of the sample self-reported having insomnia symptoms, while only 6% had a Read code for insomnia symptoms in their primary care records. Only 10% of self-reported cases had an insomnia symptom Read code, while 49% of primary care cases self-reported having insomnia symptoms. In both primary care and self-reported data, prevalence of insomnia symptom cases was highest in females, older participants and those with the lowest household incomes. However, while snorers and risk takers were more likely to be a primary care case, they were less likely to self-report insomnia symptoms than non-snorers and non-risk takers. CONCLUSIONS: Only a small proportion of individuals experiencing insomnia symptoms have an insomnia symptom Read code in their primary care record. However, primary care data do provide a clinically meaningful measure of insomnia prevalence. In addition, the sociodemographic characteristics of people attending primary care with insomnia were consistent with those with self-reported insomnia, thus primary care records are a valuable data source for studying risk factors for insomnia. Further studies should replicate our findings in other populations and examine ways to increase discussions about sleep health in primary care.

Socio-economic inequalities in the breadth of internet use before and during the COVID-19 pandemic among older adults in England.

Understanding digital exclusion in older adults during the COVID-19 pandemic could help tailor responses to future outbreaks. This cohort study used data from older adults aged 60+ years in England who participated in wave nine (2018/2019) of the main English Longitudinal Study of Ageing (ELSA) survey, and/or wave one of the ELSA COVID-19 sub-study (June/July 2020). Using latent class analysis and latent transition analysis, we aimed to identify distinct subgroups of older adults characterised by different patterns of internet use pre- and intra-pandemic, explore the extent to which individuals remained in the same subgroup or transitioned to a different subgroup during the COVID-19 pandemic, and examine longitudinal associations of socio-economic factors (education, occupational class, and wealth) with latent class membership. Preliminary tests showed that the types of internet activities differed between men and women; therefore, subsequent analyses were stratified by biological sex. Three clusters (low, medium, and high) were identified in male participants at both timepoints. Among female participants, three clusters were distinguished pre-pandemic and two (low versus high) during the pandemic. The latent classes were characterised by participants' breadth of internet use. Higher education, occupational class, and wealth were associated with greater odds of membership in the medium and/or high classes, versus the low class, in men and women. A high degree of stability in latent class membership was observed over time. However, men experienced a stark decrease in online health information-seeking. Our results highlight that inequality regarding the range of functional and social opportunities provided by the internet prevailed during the pandemic. Policymakers should ensure that digital access and upskilling initiatives are equitable for all.

Factors influencing uptake of protective behaviours by healthcare workers in England during the COVID-19 pandemic: A theory-based mixed-methods study.

BACKGROUND: Hospital infection control policies protect patients and healthcare workers (HCWs) and limit the spread of pathogens, but adherence to COVID-19 guidance varies. We examined hospital HCWs' enactment of social distancing and use of personal protective equipment (PPE) during the COVID-19 pandemic, factors influencing these behaviours, and acceptability and feasibility of strategies to increase social distancing. METHODS: An online, cross-sectional survey (n = 86) and semi-structured interviews (n = 22) with HCWs in two English hospitals during the first wave of the COVID-19 pandemic (May-December 2020). The Capability, Opportunity, Motivation (COM-B) model of behaviour change underpinned survey and topic guide questions. Spearman Rho correlations examined associations between COM-B domains and behaviours. Interviews were analysed using inductive and deductive thematic analysis. Potential strategies to improve social distancing were selected using the Behaviour Change Wheel and discussed in a stakeholder workshop (n = 8 participants). RESULTS: Social distancing enactment was low, with 85% of participants reporting very frequently or always being in close contact with others in communal areas. PPE use was high (88% very frequently or always using PPE in typical working day). Social distancing was associated with Physical Opportunity (e.g., size of physical space), Psychological Capability (e.g., clarity of guidance), and Social Opportunity (e.g., support from managers). Use of PPE was associated with Psychological Capability (e.g., training), Physical Opportunity (e.g., availability), Social Opportunity (e.g., impact on interactions with patients), and Reflective Motivation (e.g., beliefs that PPE is effective). Local champions and team competition were viewed as feasible strategies to improve social distancing. CONCLUSIONS: It is valuable to understand and compare the drivers of individual protective behaviours; when faced with the same level of perceived threat, PPE use was high whereas social distancing was rarely enacted. Identified influences represent targets for intervention strategies in response to future infectious disease outbreaks.

Nemabiome metabarcoding shows a high prevalence of Haemonchus contortus and predominance of Camelostrongylus mentulatus in alpaca herds in the northern UK.

Gastrointestinal nematodes (GINs) are a common threat faced by pastoral livestock. Since their major introduction to the UK in the early 1990s, South American camelids have been cograzed with sheep, horses, and other livestock, allowing exposure to a range of GIN species. However, there have been no molecular-based studies to investigate the GIN populations present in these camelids. In the current study, we sampled nine alpaca herds from northern England and southern Scotland and used high-throughput metabarcoded sequencing to describe their GIN species composition. A total of 71 amplicon sequence variants (ASVs) were identified representing eight known GIN species. Haemonchus contortus was the most prevalent species found in almost all herds in significant proportions. The identification of H. contortus in other livestock species is unusual in the northern UK, implying that alpacas may be suitable hosts and potential reservoirs for infection in other hosts. In addition, the camelid-adapted GIN species Camelostrongylus mentulatus was identified predominantly in herds with higher faecal egg counts. These findings highlight the value of applying advanced molecular methods, such as nemabiome metabarcoding to describe the dynamics of gastrointestinal nematode infections in novel situations. The results provide a strong base for further studies involving cograzing animals to confirm the potential role of alpacas in transmitting GIN species between hosts.

Long term care facilities in England during the COVID-19 pandemic-a scoping review of guidelines, policy and recommendations.

BACKGROUND: The disproportionate effect of COVID-19 on long term care facility (LTCF) residents has highlighted the need for clear, consistent guidance on the management of pandemics in such settings. As research exploring the experiences of LTCFs during the pandemic and the implications of mass hospital discharge, restricting staff movement, and limiting visitation from relatives are emerging, an in-depth review of policies, guidance and recommendations issued during this time could facilitate wider understanding in this area. AIMS: To identify policies, guidance, and recommendations related to LTCF staff and residents, in England issued by the government during the COVID-19 pandemic, developing a timeline of key events and synthesizing the policy aims, recommendations, implementation and intended outcomes. METHOD: A scoping review of publicly available policy documents, guidance, and recommendations related to COVID-19 in LTCFs in England, identified using systematic searches of UK government websites. The main aims, recommendations, implementation and intended outcomes reported in included documents were extracted. Data was analysed using thematic synthesis following a three-stage approach: coding the text, grouping codes into descriptive themes, and development of analytical themes. RESULTS: Thirty-three key policy documents were included in the review. Six areas of recommendations were identified: infection prevention and control, hospital discharge, testing and vaccination, staffing, visitation and continuing routine care. Seven areas of implementation were identified: funding, collaborative working, monitoring and data collection, reducing workload, decision making and leadership, training and technology, and communication. DISCUSSION: LTCFs remain complex settings, and it is imperative that lessons are learned from the experiences during COVID-19 to ensure that future pandemics are managed appropriately. This review has synthesized the policies issued during this time, however, the extent to which such guidance was communicated to LTCFs, and subsequently implemented, in addition to being effective, requires further research. In particular, understanding the secondary effects of such policies and how they can be introduced within the existing challenges inherent to adult social care, need addressing.

Social health and subsequent cognitive functioning in people aged 50 years and older: examining the mediating roles of depressive symptoms and inflammatory biomarkers in two European longitudinal studies.

BACKGROUND: Social health markers, including marital status, contact frequency, network size, and social support, have been shown to be associated with cognition. However, the mechanisms underlying these associations remain poorly understood. We investigated whether depressive symptoms and inflammation mediated associations between social health and subsequent cognition. METHODS: In the English Longitudinal Study of Ageing (ELSA), a nationally representative longitudinal study in England, UK, we sampled 7136 individuals aged 50 years or older living in private households without dementia at baseline or at the intermediate mediator assessment timepoint, who had recorded information on at least one social health marker and potential mediator. We used four-way decomposition to examine to what extent depressive symptoms, C-reactive protein, and fibrinogen mediated associations between social health and subsequent standardised cognition (verbal fluency and delayed and immediate recall), including cognitive change, with slopes derived from multilevel models (12-year slope). We examined whether findings were replicated in the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), a population-based longitudinal study in Sweden, in a sample of 2604 individuals aged 60 years or older living at home or in institutions in Kungsholmen (central Stockholm) without dementia at baseline or at the intermediate mediator assessment timepoint (6-year slope). Social health exposures were assessed at baseline, potential mediators were assessed at an intermediate timepoint (wave 2 in ELSA and 6-year follow-up in SNAC-K); cognitive outcomes were assessed at a single timepoint (wave 3 in ELSA and 12-year follow-up in SNAC-K), and cognitive change (between waves 3 and 9 in ELSA and between 6-year and 12-year follow-ups in SNAC-K). FINDINGS: The study sample included 7136 participants from ELSA, of whom 3962 (55·5%) were women and 6934 (97·2%) were White; the mean baseline age was 63·8 years (SD 9·4). Replication analyses included 2604 participants from SNAC-K, of whom 1604 (61·6%) were women (SNAC-K did not collect ethnicity data); the mean baseline age was 72·3 years (SD 10·1). In ELSA, we found indirect effects via depressive symptoms of network size, positive support, and less negative support on subsequent verbal fluency, and of positive support on subsequent immediate recall (pure indirect effect [PIE] 0·002 [95% CI 0·001-0·003]). Depressive symptoms also partially mediated associations between less negative support and slower decline in immediate recall (PIE 0·001 [0·000-0·002]) and in delayed recall (PIE 0·001 [0·000-0·002]), and between positive support and slower decline in immediate recall (PIE 0·001 [0·000-0·001]). We did not observe mediation by inflammatory biomarkers. Findings of mediation by depressive symptoms in the association between positive support and verbal fluency and between positive support and change in immediate recall were replicated in SNAC-K. INTERPRETATION: The findings of this study provide new insights into mechanisms linking social health with cognition, suggesting that associations between interactional aspects of social health, especially social support, and cognition are partly underpinned by depressive symptoms. FUNDING: EU Joint Programme-Neurodegenerative Disease Research (JPND) and Alzheimer's Society. TRANSLATION: For the Swedish translation of the abstract see Supplementary Materials section.

Cancer incidence, treatment, and survival in the prison population compared with the general population in England: a population-based, matched cohort study.

BACKGROUND: The growing and ageing prison population in England makes accurate cancer data of increasing importance for prison health policies. This study aimed to compare cancer incidence, treatment, and survival between patients diagnosed in prison and the general population. METHODS: In this population-based, matched cohort study, we used cancer registration data from the National Cancer Registration and Analysis Service in England to identify primary invasive cancers and cervical cancers in situ diagnosed in adults (aged ≥18 years) in the prison and general populations between Jan 1, 1998, and Dec 31, 2017. Ministry of Justice and Office for National Statistics population data for England were used to calculate age-standardised incidence rates (ASIR) per year and age-standardised incidence rate ratios (ASIRR) for the 20-year period. Patients diagnosed with primary invasive cancers (ie, excluding cervical cancers in situ) in prison between Jan 1, 2012, and Dec 31, 2017 were matched to individuals from the general population and linked to hospital and treatment datasets. Matching was done in a 1:5 ratio according to 5-year age group, gender, diagnosis year, cancer site, and disease stage. Our primary objectives were to compare the incidence of cancer (1998-2017); the receipt of treatment with curative intent (2012-17 matched cohort), using logistic regression adjusted for matching variables (excluding cancer site) and route to diagnosis; and overall survival following cancer diagnosis (2012-17 matched cohort), using a Cox proportional hazards model adjusted for matching variables (excluding cancer site) and route to diagnosis, with stratification for the receipt of any treatment with curative intent. FINDINGS: We identified 2015 incident cancers among 1964 adults (1556 [77·2%] men and 459 [22·8%] women) in English prisons in the 20-year period up to Dec 31, 2017. The ASIR for cancer for men in prison was initially lower than for men in the general population (in 1998, ASIR 119·33 per 100 000 person-years [95% CI 48·59-219·16] vs 746·97 per 100 000 person-years [742·31-751·66]), but increased to a similar level towards the end of the study period (in 2017, 856·85 per 100 000 person-years [675·12-1060·44] vs 788·59 per 100 000 person-years [784·62-792·57]). For women, the invasive cancer incidence rate was low and so ASIR was not reported for this group. Over the 20-year period, the incidence of invasive cancer for men in prison increased (incidence rate ratio per year, 1·05 [95% CI 1·04-1·06], during 1999-2017 compared with 1998). ASIRRs showed that over the 20-year period, overall cancer incidence was lower in men in prison than in men in the general population (ASIRR 0·76 [95% CI 0·73-0·80]). The difference was not statistically significant for women (ASIRR 0·83 [0·68-1·00]). Between Jan 1, 2012, and Dec 31, 2017, patients diagnosed in prison were less likely to undergo curative treatment than matched patients in the general population (274 [32·3%] of 847 patients vs 1728 [41·5%] of 4165; adjusted odds ratio (OR) 0·72 [95% CI 0·60-0·85]). Being diagnosed in prison was associated with a significantly increased risk of death on adjustment for matching variables (347 deaths during 2021·9 person-years in the prison cohort vs 1626 deaths during 10 944·2 person-years in the general population; adjusted HR 1·16 [95% CI 1·03-1·30]); this association was partly explained by stratification by curative treatment and further adjustment for diagnosis route (adjusted HR 1·05 [0·93-1·18]). INTERPRETATION: Cancer incidence increased in people in prisons in England between 1998 and 2017, with patients in prison less likely to receive curative treatments and having lower overall survival than the general population. The association with survival was partly explained by accounting for differences in receipt of curative treatment and adjustment for diagnosis route. Improved routine cancer surveillance is needed to inform prison cancer policies and decrease inequalities for this under-researched population. FUNDING: UK National Institute for Health and Care Research, King's College London, and Strategic Priorities Fund 2019/20 of Research England via the University of Surrey.

Cohort profile: The Social media, smartphone use and Self-harm in Young People (3S-YP) study-A prospective, observational cohort study of young people in contact with mental health services.

OBJECTIVES: The Social media, Smartphone use and Self-Harm (3S-YP) study is a prospective observational cohort study to investigate the mechanisms underpinning associations between social media and smartphone use and self-harm in a clinical youth sample. We present here a comprehensive description of the cohort from baseline data and an overview of data available from baseline and follow-up assessments. METHODS: Young people aged 13-25 years were recruited from a mental health trust in England and followed up for 6 months. Self-report data was collected at baseline and monthly during follow-up and linked with electronic health records (EHR) and user-generated data. FINDINGS: A total of 362 young people enrolled and provided baseline questionnaire data. Most participants had a history of self-harm according to clinical (n = 295, 81.5%) and broader definitions (n = 296, 81.8%). At baseline, there were high levels of current moderate/severe anxiety (n = 244; 67.4%), depression (n = 255; 70.4%) and sleep disturbance (n = 171; 47.2%). Over half used social media and smartphones after midnight on weekdays (n = 197, 54.4%; n = 215, 59.4%) and weekends (n = 241, 66.6%; n = 263, 72.7%), and half met the cut-off for problematic smartphone use (n = 177; 48.9%). Of the cohort, we have questionnaire data at month 6 from 230 (63.5%), EHR data from 345 (95.3%), social media data from 110 (30.4%) and smartphone data from 48 (13.3%). CONCLUSION: The 3S-YP study is the first prospective study with a clinical youth sample, for whom to investigate the impact of digital technology on youth mental health using novel data linkages. Baseline findings indicate self-harm, anxiety, depression, sleep disturbance and digital technology overuse are prevalent among clinical youth. Future analyses will explore associations between outcomes and exposures over time and compare self-report with user-generated data in this cohort.

Long-term outcomes of SARS-CoV-2 variants and other respiratory infections: evidence from the Virus Watch prospective cohort in England.

This study compared the likelihood of long-term sequelae following infection with SARS-CoV-2 variants, other acute respiratory infections (ARIs) and non-infected individuals. Participants (n=5,630) were drawn from Virus Watch, a prospective community cohort investigating SARS-CoV-2 epidemiology in England. Using logistic regression, we compared predicted probabilities of developing long-term symptoms (>2 months) during different variant dominance periods according to infection status (SARS-CoV-2, other ARI, or no infection), adjusting for confounding by demographic and clinical factors and vaccination status. SARS-CoV-2 infection during early variant periods up to Omicron BA.1 was associated with greater probability of long-term sequalae (adjusted predicted probability (PP) range 0.27, 95% CI = 0.22-0.33 to 0.34, 95% CI = 0.25-0.43) compared with later Omicron sub-variants (PP range 0.11, 95% CI 0.08-0.15 to 0.14, 95% CI 0.10-0.18). While differences between SARS-CoV-2 and other ARIs (PP range 0.08, 95% CI 0.04-0.11 to 0.23, 95% CI 0.18-0.28) varied by period, all post-infection estimates substantially exceeded those for non-infected participants (PP range 0.01, 95% CI 0.00, 0.02 to 0.03, 95% CI 0.01-0.06). Variant was an important predictor of SARS-CoV-2 post-infection sequalae, with recent Omicron sub-variants demonstrating similar probabilities to other contemporaneous ARIs. Further aetiological investigation including between-pathogen comparison is recommended.

Acute and long-term outcomes of SARS-CoV-2 infection in school-aged children in England: Study protocol for the joint analysis of the COVID-19 schools infection survey (SIS) and the COVID-19 mapping and mitigation in schools (CoMMinS) study.

BACKGROUND: The symptom profiles of acute SARS-CoV-2 infection and long-COVID in children and young people (CYP), risk factors, and associated healthcare needs, are poorly defined. The Schools Infection Survey 1 (SIS-1) was a nationwide study of SARS-CoV-2 infection in primary and secondary schools in England during the 2020/21 school year. The Covid-19 Mapping and Mitigation in Schools (CoMMinS) study was conducted in schools in the Bristol area over a similar period. Both studies conducted testing to identify current and previous SARS-CoV-2 infection, and recorded symptoms and school attendance. These research data have been linked to routine electronic health record (EHR) data. AIMS: To better understand the short- and long-term consequences of SARS-CoV-2 infection, and their risk factors, in CYP. METHODS: Retrospective cohort and nested case-control analyses will be conducted for SIS-1 and CoMMinS data linked to EHR data for the association between (1) acute symptomatic SARS-CoV-2 infection and risk factors; (2) SARS-CoV-2 infection and long-term effects on health: (a) persistent symptoms; (b) any new diagnosis; (c) a new prescription in primary care; (d) health service attendance; (e) a high rate of school absence. RESULTS: Our study will improve understanding of long-COVID in CYP by characterising the trajectory of long-COVID in CYP in terms of things like symptoms and diagnoses of conditions. The research will inform which groups of CYP are more likely to get acute- and long-term outcomes of SARS-CoV-2 infection, and patterns of related healthcare-seeking behaviour, relevant for healthcare service planning. Digested information will be produced for affected families, doctors, schools, and the public, as appropriate. CONCLUSION: Linked SIS-1 and CoMMinS data represent a unique and rich resource for understanding the impact of SARS-CoV-2 infection on children's health, benefiting from enhanced SARS-CoV-2 testing and ability to assess a wide range of outcomes.

Risk of not being in employment, education or training (NEET) in late adolescence is signalled by school readiness measures at 4-5 years.

BACKGROUND: Not being in employment, education, or training (NEET) is associated with poor health (physical and mental) and social exclusion. We investigated whether England's statutory school readiness measure conducted at 4-5 years provides a risk signal for NEET in late adolescence. METHODS: We identified 8,118 individuals with school readiness measures at 4-5 years and NEET records at 16-17 years using Connected Bradford, a bank of linked routinely collected datasets. Children were categorised as 'school ready' if they reached a 'Good Level of Development' on the Early Years Foundation Stage Profile. We used probit regression and structural equation modelling to investigate the relationship between school readiness and NEET status and whether it primarily relates to academic attainment. RESULTS: School readiness was significantly associated with NEET status. A larger proportion of young people who were not school ready were later NEET (11%) compared to those who were school ready (4%). Most of this effect was attributable to shared relationships with academic attainment, but there was also a direct effect. Measures of deprivation and Special Educational Needs were also strong predictors of NEET status. CONCLUSIONS: NEET risk factors occur early in life. School readiness measures could be used as early indicators of risk, with interventions targeted to prevent the long-term physical and mental health problems associated with NEET, especially in disadvantaged areas. Primary schools are therefore well placed to be public health partners in early intervention strategies.

The laboratory investigation, management, and infection prevention and control of Candida auris: a narrative review to inform the 2024 national guidance update in England.

The emergent fungal pathogen Candida auris is increasingly recognised as an important cause of healthcare-associated infections globally. It is highly transmissible, adaptable, and persistent, resulting in an organism with significant outbreak potential that risks devastating consequences. Progress in the ability to identify C. auris in clinical specimens is encouraging, but laboratory diagnostic capacity and surveillance systems are lacking in many countries. Intrinsic resistance to commonly used antifungals, combined with the ability to rapidly acquire resistance to therapy, substantially restricts treatment options and novel agents are desperately needed. Despite this, outbreaks can be interrupted, and mortality avoided or minimised, through the application of rigorous infection prevention and control measures with an increasing evidence base. This review provides an update on epidemiology, the impact of the COVID-19 pandemic, risk factors, identification and typing, resistance profiles, treatment, detection of colonisation, and infection prevention and control measures for C. auris. This review has informed a planned 2024 update to the United Kingdom Health Security Agency (UKHSA) guidance on the laboratory investigation, management, and infection prevention and control of Candida auris. A multidisciplinary response is needed to control C. auris transmission in a healthcare setting and should emphasise outbreak preparedness and response, rapid contact tracing and isolation or cohorting of patients and staff, strict hand hygiene and other infection prevention and control measures, dedicated or single-use equipment, appropriate disinfection, and effective communication concerning patient transfers and discharge.