Imbalance of Regulatory and Cytotoxic SARS-CoV-2-Reactive CD4+ T Cells in COVID-19.

The contribution of CD4+ T cells to protective or pathogenic immune responses to SARS-CoV-2 infection remains unknown. Here, we present single-cell transcriptomic analysis of >100,000 viral antigen-reactive CD4+ T cells from 40 COVID-19 patients. In hospitalized patients compared to non-hospitalized patients, we found increased proportions of cytotoxic follicular helper cells and cytotoxic T helper (TH) cells (CD4-CTLs) responding to SARS-CoV-2 and reduced proportion of SARS-CoV-2-reactive regulatory T cells (TREG). Importantly, in hospitalized COVID-19 patients, a strong cytotoxic TFH response was observed early in the illness, which correlated negatively with antibody levels to SARS-CoV-2 spike protein. Polyfunctional TH1 and TH17 cell subsets were underrepresented in the repertoire of SARS-CoV-2-reactive CD4+ T cells compared to influenza-reactive CD4+ T cells. Together, our analyses provide insights into the gene expression patterns of SARS-CoV-2-reactive CD4+ T cells in distinct disease severities.

Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts.

How likely is it to become infected by SARS-CoV-2 after being exposed? Almost everyone wondered about this question during the COVID-19 pandemic. Contact-tracing apps1,2 recorded measurements of proximity3 and duration between nearby smartphones. Contacts-individuals exposed to confirmed cases-were notified according to public health policies such as the 2 m, 15 min guideline4,5, despite limited evidence supporting this threshold. Here we analysed 7 million contacts notified by the National Health Service COVID-19 app6,7 in England and Wales to infer how app measurements translated to actual transmissions. Empirical metrics and statistical modelling showed a strong relation between app-computed risk scores and actual transmission probability. Longer exposures at greater distances had risk similar to that of shorter exposures at closer distances. The probability of transmission confirmed by a reported positive test increased initially linearly with duration of exposure (1.1% per hour) and continued increasing over several days. Whereas most exposures were short (median 0.7 h, interquartile range 0.4-1.6), transmissions typically resulted from exposures lasting between 1 h and several days (median 6 h, interquartile range 1.4-28). Households accounted for about 6% of contacts but 40% of transmissions. With sufficient preparation, privacy-preserving yet precise analyses of risk that would inform public health measures, based on digital contact tracing, could be performed within weeks of the emergence of a new pathogen.

The burden and dynamics of hospital-acquired SARS-CoV-2 in England.

Hospital-based transmission had a dominant role in Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV) epidemics1,2, but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital-community interactions. Using data from acute hospitals in England, we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 inpatients acquired SARS-CoV-2 in hospitals (1% to 2% of all hospital admissions in this period). Analysis of time series data provided evidence that patients who themselves acquired SARS-CoV-2 infection in hospital were the main sources of transmission to other patients. Increased transmission to inpatients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognized scale of hospital transmission, have direct implications for targeting of hospital control measures and highlight the need to design hospitals better equipped to limit the transmission of future high-consequence pathogens.

Context-specific emergence and growth of the SARS-CoV-2 Delta variant.

The SARS-CoV-2 Delta (Pango lineage B.1.617.2) variant of concern spread globally, causing resurgences of COVID-19 worldwide1,2. The emergence of the Delta variant in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 SARS-CoV-2 genomes from England together with 93,649 genomes from the rest of the world to reconstruct the emergence of Delta and quantify its introduction to and regional dissemination across England in the context of changing travel and social restrictions. Using analysis of human movement, contact tracing and virus genomic data, we find that the geographic focus of the expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced more than 1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers reduced onward transmission from importations; however, the transmission chains that later dominated the Delta wave in England were seeded before travel restrictions were introduced. Increasing inter-regional travel within England drove the nationwide dissemination of Delta, with some cities receiving more than 2,000 observable lineage introductions from elsewhere. Subsequently, increased levels of local population mixing-and not the number of importations-were associated with the faster relative spread of Delta. The invasion dynamics of Delta depended on spatial heterogeneity in contact patterns, and our findings will inform optimal spatial interventions to reduce the transmission of current and future variants of concern, such as Omicron (Pango lineage B.1.1.529).

Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7.

SARS-CoV-2 lineage B.1.1.7, a variant that was first detected in the UK in September 20201, has spread to multiple countries worldwide. Several studies have established that B.1.1.7 is more transmissible than pre-existing variants, but have not identified whether it leads to any change in disease severity2. Here we analyse a dataset that links 2,245,263 positive SARS-CoV-2 community tests and 17,452 deaths associated with COVID-19 in England from 1 November 2020 to 14 February 2021. For 1,146,534 (51%) of these tests, the presence or absence of B.1.1.7 can be identified because mutations in this lineage prevent PCR amplification of the spike (S) gene target (known as S gene target failure (SGTF)1). On the basis of 4,945 deaths with known SGTF status, we estimate that the hazard of death associated with SGTF is 55% (95% confidence interval, 39-72%) higher than in cases without SGTF after adjustment for age, sex, ethnicity, deprivation, residence in a care home, the local authority of residence and test date. This corresponds to the absolute risk of death for a 55-69-year-old man increasing from 0.6% to 0.9% (95% confidence interval, 0.8-1.0%) within 28 days of a positive test in the community. Correcting for misclassification of SGTF and missingness in SGTF status, we estimate that the hazard of death associated with B.1.1.7 is 61% (42-82%) higher than with pre-existing variants. Our analysis suggests that B.1.1.7 is not only more transmissible than pre-existing SARS-CoV-2 variants, but may also cause more severe illness.

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.

Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England.

The SARS-CoV-2 lineage B.1.1.7, designated variant of concern (VOC) 202012/01 by Public Health England1, was first identified in the UK in late summer to early autumn 20202. Whole-genome SARS-CoV-2 sequence data collected from community-based diagnostic testing for COVID-19 show an extremely rapid expansion of the B.1.1.7 lineage during autumn 2020, suggesting that it has a selective advantage. Here we show that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S gene target failures (SGTF) in community-based diagnostic PCR testing. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that B.1.1.7 has higher transmissibility than non-VOC lineages, even if it has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with cases of B.1.1.7 including a larger share of under 20-year-olds than non-VOC cases. We estimated time-varying reproduction numbers for B.1.1.7 and co-circulating lineages using SGTF and genomic data. The best-supported models did not indicate a substantial difference in VOC transmissibility among different age groups, but all analyses agreed that B.1.1.7 has a substantial transmission advantage over other lineages, with a 50% to 100% higher reproduction number.

The epidemiological impact of the NHS COVID-19 app.

The COVID-19 pandemic has seen the emergence of digital contact tracing to help to prevent the spread of the disease. A mobile phone app records proximity events between app users, and when a user tests positive for COVID-19, their recent contacts can be notified instantly. Theoretical evidence has supported this new public health intervention1-6, but its epidemiological impact has remained uncertain7. Here we investigate the impact of the National Health Service (NHS) COVID-19 app for England and Wales, from its launch on 24 September 2020 to the end of December 2020. It was used regularly by approximately 16.5 million users (28% of the total population), and sent approximately 1.7 million exposure notifications: 4.2 per index case consenting to contact tracing. We estimated that the fraction of individuals notified by the app who subsequently showed symptoms and tested positive (the secondary attack rate (SAR)) was 6%, similar to the SAR for manually traced close contacts. We estimated the number of cases averted by the app using two complementary approaches: modelling based on the notifications and SAR gave an estimate of 284,000 (central 95% range of sensitivity analyses 108,000-450,000), and statistical comparison of matched neighbouring local authorities gave an estimate of 594,000 (95% confidence interval 317,000-914,000). Approximately one case was averted for each case consenting to notification of their contacts. We estimated that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis). These findings support the continued development and deployment of such apps in populations that are awaiting full protection from vaccines.

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England.

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

Dynamics of SARS-CoV-2 infection hospitalisation and infection fatality ratios over 23 months in England.

The relationship between prevalence of infection and severe outcomes such as hospitalisation and death changed over the course of the COVID-19 pandemic. Reliable estimates of the infection fatality ratio (IFR) and infection hospitalisation ratio (IHR) along with the time-delay between infection and hospitalisation/death can inform forecasts of the numbers/timing of severe outcomes and allow healthcare services to better prepare for periods of increased demand. The REal-time Assessment of Community Transmission-1 (REACT-1) study estimated swab positivity for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in England approximately monthly from May 2020 to March 2022. Here, we analyse the changing relationship between prevalence of swab positivity and the IFR and IHR over this period in England, using publicly available data for the daily number of deaths and hospitalisations, REACT-1 swab positivity data, time-delay models, and Bayesian P-spline models. We analyse data for all age groups together, as well as in 2 subgroups: those aged 65 and over and those aged 64 and under. Additionally, we analysed the relationship between swab positivity and daily case numbers to estimate the case ascertainment rate of England's mass testing programme. During 2020, we estimated the IFR to be 0.67% and the IHR to be 2.6%. By late 2021/early 2022, the IFR and IHR had both decreased to 0.097% and 0.76%, respectively. The average case ascertainment rate over the entire duration of the study was estimated to be 36.1%, but there was some significant variation in continuous estimates of the case ascertainment rate. Continuous estimates of the IFR and IHR of the virus were observed to increase during the periods of Alpha and Delta's emergence. During periods of vaccination rollout, and the emergence of the Omicron variant, the IFR and IHR decreased. During 2020, we estimated a time-lag of 19 days between hospitalisation and swab positivity, and 26 days between deaths and swab positivity. By late 2021/early 2022, these time-lags had decreased to 7 days for hospitalisations and 18 days for deaths. Even though many populations have high levels of immunity to SARS-CoV-2 from vaccination and natural infection, waning of immunity and variant emergence will continue to be an upwards pressure on the IHR and IFR. As investments in community surveillance of SARS-CoV-2 infection are scaled back, alternative methods are required to accurately track the ever-changing relationship between infection, hospitalisation, and death and hence provide vital information for healthcare provision and utilisation.

Illness Trajectories After Revascularization in Patients With Peripheral Artery Disease: A Unified Approach to Understanding the Risk of Major Amputation and Death.

BACKGROUND: The aim of this study was to investigate the illness trajectories of patients with peripheral artery disease (PAD) after revascularization and estimate the independent risks of major amputation and death (from any cause) and their interaction. METHODS: Data from Hospital Episode Statistics Admitted Patient Care were used to identify patients (≥50 years of age) who underwent lower limb revascularization for PAD in England from April 2013 to March 2020. A Markov illness-death model was developed to describe patterns of survival after the initial lower limb revascularization, if and when patients experienced major amputation, and survival after amputation. The model was also used to investigate the association between patient characteristics and these illness trajectories. We also analyzed the relative contribution of deaths after amputation to overall mortality and how the risk of mortality after amputation was related to the time from the index revascularization to amputation. RESULTS: The study analyzed 94 690 patients undergoing lower limb revascularization for PAD from 2013 to 2020. The majority were men (65.6%), and the median age was 72 years (interquartile range, 64-79). One-third (34.8%) of patients had nonelective revascularization, whereas others had elective procedures. For nonelective patients, the amputation rate was 15.2% (95% CI, 14.4-16.0) and 19.9% (19.0-20.8) at 1 and 5 years after revascularization, respectively. For elective patients, the corresponding amputation rate was 2.7% (95% CI, 2.4-3.1) and 5.3% (4.9-5.8). Overall, the risk of major amputation was higher among patients who were younger, had tissue loss, diabetes, greater frailty, nonelective revascularization, and more distal procedures. The mortality rate at 5 years after revascularization was 64.3% (95% CI, 63.2-65.5) for nonelective patients and 33.0% (32.0-34.1) for elective patients. After major amputation, patients were at an increased risk of mortality if they underwent major amputation within 6 months after the index revascularization. CONCLUSIONS: The illness-death model provides an integrated framework to understand patient outcomes after lower limb revascularization for PAD. Although mortality increased with age, the study highlights patients <60 years of age were at increased risk of major amputation, particularly after nonelective revascularization.

Undervaccination and severe COVID-19 outcomes: meta-analysis of national cohort studies in England, Northern Ireland, Scotland, and Wales.

BACKGROUND: Undervaccination (receiving fewer than the recommended number of SARS-CoV-2 vaccine doses) could be associated with increased risk of severe COVID-19 outcomes-ie, COVID-19 hospitalisation or death-compared with full vaccination (receiving the recommended number of SARS-CoV-2 vaccine doses). We sought to determine the factors associated with undervaccination, and to investigate the risk of severe COVID-19 outcomes in people who were undervaccinated in each UK nation and across the UK. METHODS: We used anonymised, harmonised electronic health record data with whole population coverage to carry out cohort studies in England, Northern Ireland, Scotland, and Wales. Participants were required to be at least 5 years of age to be included in the cohorts. We estimated adjusted odds ratios for undervaccination as of June 1, 2022. We also estimated adjusted hazard ratios (aHRs) for severe COVID-19 outcomes during the period June 1 to Sept 30, 2022, with undervaccination as a time-dependent exposure. We combined results from nation-specific analyses in a UK-wide fixed-effect meta-analysis. We estimated the reduction in severe COVID-19 outcomes associated with a counterfactual scenario in which everyone in the UK was fully vaccinated on June 1, 2022. FINDINGS: The numbers of people undervaccinated on June 1, 2022 were 26 985 570 (45·8%) of 58 967 360 in England, 938 420 (49·8%) of 1 885 670 in Northern Ireland, 1 709 786 (34·2%) of 4 992 498 in Scotland, and 773 850 (32·8%) of 2 358 740 in Wales. People who were younger, from more deprived backgrounds, of non-White ethnicity, or had a lower number of comorbidities were less likely to be fully vaccinated. There was a total of 40 393 severe COVID-19 outcomes in the cohorts, with 14 156 of these in undervaccinated participants. We estimated the reduction in severe COVID-19 outcomes in the UK over 4 months of follow-up associated with a counterfactual scenario in which everyone was fully vaccinated on June 1, 2022 as 210 (95% CI 94-326) in the 5-15 years age group, 1544 (1399-1689) in those aged 16-74 years, and 5426 (5340-5512) in those aged 75 years or older. aHRs for severe COVID-19 outcomes in the meta-analysis for the age group of 75 years or older were 2·70 (2·61-2·78) for one dose fewer than recommended, 3·13 (2·93-3·34) for two fewer, 3·61 (3·13-4·17) for three fewer, and 3·08 (2·89-3·29) for four fewer. INTERPRETATION: Rates of undervaccination against COVID-19 ranged from 32·8% to 49·8% across the four UK nations in summer, 2022. Undervaccination was associated with an elevated risk of severe COVID-19 outcomes. FUNDING: UK Research and Innovation National Core Studies: Data and Connectivity.

Genome-Wide Association Study of Obsessive-Compulsive Symptoms including 33,943 individuals from the general population.

While 1-2% of individuals meet the criteria for a clinical diagnosis of obsessive-compulsive disorder (OCD), many more (~13-38%) experience subclinical obsessive-compulsive symptoms (OCS) during their life. To characterize the genetic underpinnings of OCS and its genetic relationship to OCD, we conducted the largest genome-wide association study (GWAS) meta-analysis of parent- or self-reported OCS to date (N = 33,943 with complete phenotypic and genome-wide data), combining the results from seven large-scale population-based cohorts from Sweden, the Netherlands, England, and Canada (including six twin cohorts and one cohort of unrelated individuals). We found no genome-wide significant associations at the single-nucleotide polymorphism (SNP) or gene-level, but a polygenic risk score (PRS) based on the OCD GWAS previously published by the Psychiatric Genetics Consortium (PGC-OCD) was significantly associated with OCS (Pfixed = 3.06 × 10-5). Also, one curated gene set (Mootha Gluconeogenesis) reached Bonferroni-corrected significance (Ngenes = 28, Beta = 0.79, SE = 0.16, Pbon = 0.008). Expression of genes in this set is high at sites of insulin mediated glucose disposal. Dysregulated insulin signaling in the etiology of OCS has been suggested by a previous study describing a genetic overlap of OCS with insulin signaling-related traits in children and adolescents. We report a SNP heritability of 4.1% (P = 0.0044) in the meta-analyzed GWAS, and heritability estimates based on the twin cohorts of 33-43%. Genetic correlation analysis showed that OCS were most strongly associated with OCD (rG = 0.72, p = 0.0007) among all tested psychiatric disorders (N = 11). Of all 97 tested phenotypes, 24 showed a significant genetic correlation with OCS, and 66 traits showed concordant directions of effect with OCS and OCD. OCS have a significant polygenic contribution and share genetic risk with diagnosed OCD, supporting the hypothesis that OCD represents the extreme end of widely distributed OCS in the population.

A mathematical, classical stratification modeling approach to disentangling the impact of weather on infectious diseases: A case study using spatio-temporally disaggregated Campylobacter surveillance data for England and Wales.

Disentangling the impact of the weather on transmission of infectious diseases is crucial for health protection, preparedness and prevention. Because weather factors are co-incidental and partly correlated, we have used geography to separate out the impact of individual weather parameters on other seasonal variables using campylobacteriosis as a case study. Campylobacter infections are found worldwide and are the most common bacterial food-borne disease in developed countries, where they exhibit consistent but country specific seasonality. We developed a novel conditional incidence method, based on classical stratification, exploiting the long term, high-resolution, linkage of approximately one-million campylobacteriosis cases over 20 years in England and Wales with local meteorological datasets from diagnostic laboratory locations. The predicted incidence of campylobacteriosis increased by 1 case per million people for every 5° (Celsius) increase in temperature within the range of 8°-15°. Limited association was observed outside that range. There were strong associations with day-length. Cases tended to increase with relative humidity in the region of 75-80%, while the associations with rainfall and wind-speed were weaker. The approach is able to examine multiple factors and model how complex trends arise, e.g. the consistent steep increase in campylobacteriosis in England and Wales in May-June and its spatial variability. This transparent and straightforward approach leads to accurate predictions without relying on regression models and/or postulating specific parameterisations. A key output of the analysis is a thoroughly phenomenological description of the incidence of the disease conditional on specific local weather factors. The study can be crucially important to infer the elusive mechanism of transmission of campylobacteriosis; for instance, by simulating the conditional incidence for a postulated mechanism and compare it with the phenomenological patterns as benchmark. The findings challenge the assumption, commonly made in statistical models, that the transformed mean rate of infection for diseases like campylobacteriosis is a mere additive and combination of the environmental variables.

A retrospective assessment of forecasting the peak of the SARS-CoV-2 Omicron BA.1 wave in England.

We discuss the invasion of the Omicron BA.1 variant into England as a paradigm for real-time model fitting and projection. Here we use a mixture of simple SIR-type models, analysis of the early data and a more complex age-structure model fit to the outbreak to understand the dynamics. In particular, we highlight that early data shows that the invading Omicron variant had a substantial growth advantage over the resident Delta variant. However, early data does not allow us to reliably infer other key epidemiological parameters-such as generation time and severity-which influence the expected peak hospital numbers. With more complete epidemic data from January 2022 are we able to capture the true scale of the epidemic in terms of both infections and hospital admissions, driven by different infection characteristics of Omicron compared to Delta and a substantial shift in estimated precautionary behaviour during December. This work highlights the challenges of real time forecasting, in a rapidly changing environment with limited information on the variant's epidemiological characteristics.

The impact of health inequity on spatial variation of COVID-19 transmission in England.

Considerable spatial heterogeneity has been observed in COVID-19 transmission across administrative areas of England throughout the pandemic. This study investigates what drives these differences. We constructed a probabilistic case count model for 306 administrative areas of England across 95 weeks, fit using a Bayesian evidence synthesis framework. We incorporate the impact of acquired immunity, of spatial exportation of cases, and 16 spatially-varying socio-economic, socio-demographic, health, and mobility variables. Model comparison assesses the relative contributions of these respective mechanisms. We find that spatially-varying and time-varying differences in week-to-week transmission were definitively associated with differences in: time spent at home, variant-of-concern proportion, and adult social care funding. However, model comparison demonstrates that the impact of these terms is negligible compared to the role of spatial exportation between administrative areas. While these results confirm the impact of some, but not all, static measures of spatially-varying inequity in England, our work corroborates the finding that observed differences in disease transmission during the pandemic were predominantly driven by underlying epidemiological factors rather than aggregated metrics of demography and health inequity between areas. Further work is required to assess how health inequity more broadly contributes to these epidemiological factors.

The Clinical and Economic Burden of Antibiotic Use in Pediatric Patients With Varicella Infection: A Retrospective Cohort Analysis of Real-World Data in England.

BACKGROUND: Varicella is a highly infectious disease, particularly affecting children, that can lead to complications requiring antibiotics or hospitalization. Antibiotic use for varicella management is poorly documented. This study assessed antibiotic use for varicella and its complications in a pediatric population in England. METHODS: Data were drawn from medical records in the Clinical Practice Research Datalink and Hospital Episode Statistics data sets. The study included patients <18 years old with varicella diagnosed during 2014-2018 and 3-month follow-up available. We determined varicella-related complications, medication use, healthcare resource utilization, and costs from diagnosis until 3 months after diagnosis. RESULTS: We identified 114 578 children with a primary varicella diagnosis. Of these, 7.7% (n = 8814) had a varicella-related complication, the most common being ear, nose, and throat related (37.1% [n = 3271]). In all, 25.9% (n = 29 706 of 114 578) were prescribed antibiotics. A higher proportion of patients with complications than without complications were prescribed antibiotics (64.3% [n = 5668 of 8814] vs 22.7% [n = 24 038 of 105 764]). Mean annualized varicella-related costs were £2 231 481 for the study cohort. Overall, antibiotic prescriptions cost approximately £262 007. CONCLUSIONS: This study highlights high antibiotic use and healthcare resource utilization associated with varicella management, particularly in patients with complications. A national varicella vaccination program in England may reduce varicella burden and related complications, medication use, and costs.

Clinical Impact of Serious Respiratory Disease in Children Under the Age of 2 Years During the 2021-2022 Bronchiolitis Season in England, Scotland, and Ireland.

BACKGROUND: Interventions introduced to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a widespread reduction in childhood infections. However, from spring 2021 onwards the United Kingdom and Ireland experienced an unusual out-of-season epidemic of respiratory disease. METHODS: We conducted a prospective observational study (BronchStart), enrolling children 0-23 months of age presenting with bronchiolitis, lower respiratory tract infection, or first episode of wheeze to 59 emergency departments across England, Scotland, and Ireland from May 2021 to April 2022. We combined testing data with national admissions datasets to infer the impact of respiratory syncytial virus (RSV) disease. RESULTS: The BronchStart study collected data on 17 899 presentations for 17 164 children. Risk factors for admission and escalation of care included prematurity and congenital heart disease, but most admissions were for previously healthy term-born children. Of those aged 0-11 months who were admitted and tested for RSV, 1907 of 3912 (48.7%) tested positive. We estimate that every year in England and Scotland 28 561 (95% confidence interval, 27 637-29 486) infants are admitted with RSV infection. CONCLUSIONS: RSV infection was the main cause of hospitalizations in this cohort, but 51.3% of admissions in infants were not associated with the virus. The majority of admissions were in previously healthy term-born infants.

Risks of adverse obstetric outcomes among female survivors of adolescent and young adult cancer in England (TYACSS): a population-based, retrospective cohort study.

BACKGROUND: There are limited data on the risks of obstetric complications among survivors of adolescent and young adult cancer with most previous studies only reporting risks for all types of cancers combined. The aim of this study was to quantify deficits in birth rates and risks of obstetric complications for female survivors of 17 specific types of adolescent and young adult cancer. METHODS: The Teenage and Young Adult Cancer Survivor Study (TYACSS)-a retrospective, population-based cohort of 200 945 5-year survivors of cancer diagnosed at age 15-39 years from England and Wales-was linked to the English Hospital Episode Statistics (HES) database from April 1, 1997, to March 31, 2022. The cohort included 17 different types of adolescent and young adult cancers. We ascertained 27 specific obstetric complications through HES among 96 947 women in the TYACSS cohort. Observed and expected numbers for births and obstetric complications were compared between the study cohort and the general population of England to identify survivors of adolescent and young adult cancer at a heighted risk of birth deficits and obstetric complications relative to the general population. FINDINGS: Between April 1, 1997, and March 31, 2022, 21 437 births were observed among 13 886 female survivors of adolescent and young adult cancer from England, which was lower than expected (observed-to-expected ratio: 0·68, 95% CI 0·67-0·69). Other survivors of genitourinary, cervical, and breast cancer had under 50% of expected births. Focusing on more common (observed ≥100) obstetric complications that were at least moderately in excess (observed-to-expected ratio ≥1·25), survivors of cervical cancer were at risk of malpresentation of fetus, obstructed labour, amniotic fluid and membranes disorders, premature rupture of membranes, preterm birth, placental disorders including placenta praevia, and antepartum haemorrhage. Survivors of leukaemia were at risk of preterm delivery, obstructed labour, postpartum haemorrhage, and retained placenta. Survivors of all other specific cancers had no more than two obstetric complications that exceeded an observed-to-expected ratio of 1·25 or greater. INTERPRETATION: Survivors of cervical cancer and leukaemia are at risk of several serious obstetric complications; therefore, any pregnancy should be considered high-risk and would benefit from obstetrician-led antenatal care. Despite observing deficits in birth rates across all 17 different types of adolescent and young adult cancer, we provide reassurance for almost all survivors of adolescent and young adult cancer concerning their risk of almost all obstetric complications. Our results provide evidence for the development of clinical guidelines relating to counselling and surveillance of obstetrical risk for female survivors of adolescent and young adult cancer. FUNDING: Children with Cancer UK, The Brain Tumour Charity, and Academy of Medical Sciences.

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.