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 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.

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.

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.

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.

Hormone replacement therapy and cancer mortality in women with 17 site-specific cancers: a cohort study using linked medical records.

BACKGROUND: There is limited evidence on the safety of Hormone Replacement Therapy (HRT) in women with cancer. Therefore, we systematically examined HRT use and cancer-specific mortality in women with 17 site-specific cancers. METHODS: Women newly diagnosed with 17 site-specific cancers from 1998 to 2019, were identified from general practitioner (GP) records, hospital diagnoses or cancer registries in Scotland, Wales and England. Breast cancer patients were excluded because HRT is contraindicated in breast cancer patients. The primary outcome was time to cancer-specific mortality. Time-dependent Cox regression models were used to calculate adjusted hazard ratios (HR) and 95% confidence intervals (95% CIs) for cancer-specific mortality by systemic HRT use. RESULTS: The combined cancer cohorts contained 182,589 women across 17 cancer sites. Overall 7% of patients used systemic HRT after their cancer diagnosis. There was no evidence that HRT users, compared with non-users, had higher cancer-specific mortality at any cancer site. In particular, no increase was observed in common cancers including lung (adjusted HR = 0.98 95% CI 0.90, 1.07), colorectal (adjusted HR = 0.79 95% CI 0.70, 0.90), and melanoma (adjusted HR = 0.77 95% CI 0.58, 1.02). CONCLUSIONS: We observed no evidence of increased cancer-specific mortality in women with a range of cancers (excluding breast) receiving HRT.

A 3-year review of deaths in people under community justice supervision in Wales: a cross-sectional analysis.

BACKGROUND: Despite little fluctuation in the numbers of people under community justice supervision in England and Wales, the number of deaths in this population has more than doubled between 2013-14 and 2020-21, from 560 to 1343 deaths. Contributing factors and causes of mortality are somewhat unknown. The aim of this study was to understand the number and the leading causes of people dying while under community justice supervision in Wales, UK, between April 1, 2018, and March 31, 2021. METHODS: Public Health Wales in collaboration with HM Prison and Probation Service in Wales were provided with identifiable data (name, date of birth, date of death, and the Probation Delivery Unit) of 306 individuals (aged ≥18 years) who had died during this time period while under community justice supervision. Following de-duplication and matching of National Health Service (NHS) numbers using the Welsh Demographic System, 266 deaths were linked to the live Office for National Statistics (ONS) Death Registry to obtain the cause of death. Deaths were grouped based on the International Classification of Diseases (ICD)-10 code assigned as their underlying cause of death. FINDINGS: In this cross-sectional study, the mortality rate overall was higher in women than in men (7·5 vs 5·6 deaths per 1000 population), despite the majority of deaths being in men, with less than 40 deaths in women. Mortality rates were nearly double in those aged 50 years and older (9·4 deaths per 1000 population) than in those aged 18-49 years (5·0 deaths per 1000 population). Drugs or alcohol were considered a primary cause of death for just under half of all deaths (n=115; 43%), with opiates being the most commonly named substance (n=63; 24%). 70 drug-related deaths involved poly-drug use. Accidental drug-related deaths were four times higher in those aged 18-49 years than in those aged 50 years and older (2·3 vs 0·6 deaths per 1000 population). Diseases of the circulatory system accounted for 13% (n=34) of all deaths and were 5 times higher in those aged 50 years and older than those aged 18-49 years (2·2 vs 0·4 deaths per 1000 population). INTERPRETATION: This study provides valuable insight into the leading causes of death among this cohort, notably deaths associated with substance misuse in younger age groups and with circulatory disease in older age groups. The increase in substance misuse-related deaths reflects recent national UK trends. Further research is required to understand which of these deaths were preventable. FUNDING: None.

Profiles of tobacco smokers and ex-smokers in a large-scale random sample survey across Wales: an unsupervised machine-learning cluster analysis.

BACKGROUND: The Welsh government recently set a target to be smoke-free by 2030, which means reducing the prevalence of tobacco smoking in adults to 5% by then. The goal is to improve health and population life expectancy. To support this strategy, we identified profile groups with different sets of socioeconomic and demographic characteristics within the population of smokers. We compared these profiles to those identified in the ex-smoker population to provide a broader understanding of smokers and inform targeting of interventions and policy. METHODS: We did a cross-sectional study using data from the National Survey for Wales. This survey is a random sample telephone survey of individuals aged 16 years and older across Wales carried out from Sept 1, 2021 to Jan 31, 2022, weighted to be representative of the Welsh population. For the smoking subgroup, we did a weighted hierarchical cluster analysis with multiple imputation to impute missing data and repeated it for ex-smokers. In total, 63 survey variables were used in the analysis. These variables included smoking history, e-cigarette use, sociodemographics, lifestyle factors, individual-level deprivation, general health and long-term conditions, mental health, and wellbeing. FINDINGS: Among the 6407 respondents (weighted proportions: 49% male, 51% female; 28% aged 16-34 years, 46% aged 35-44 years, 26% aged ≥65 years; 95% white, 5% other ethnicity), 841 (13%) smoked and 2136 (33%) were ex-smokers. Four distinctive profiles of smokers were identified, the groups were of relatively comparable size and characterised by similarities described as (1) high-risk alcohol drinkers and without children; (2) single, mostly in social housing, and poor health and mental health; (3) mostly single, younger, tried e-cigarettes, and poor mental health; (4) older couples and poor health; when comparing the groups with each other. Cluster quality and validation statistics were considered fair: silhouette coefficient=0·09, Dunn index (Dunn2)=1·06. Generally, ex-smoker clusters differed from smoking clusters because of themes related to increased sickness, better affluence, employment, and older age (≥75 years). INTERPRETATION: This study suggests that not all smokers are the same, and they do not fall into one coherent group. Smoking cessation interventions to improve the health of ageing populations might need a different approach to consider a wider context or motivations to inform targeted quitting. It is acknowledged that smoking might be underreported because of perceived social unacceptability. FUNDING: Public Health Wales.

Influenza: cause or excuse? An analysis of flu's influence on worsening mortality trends in England and Wales, 2010-19.

BACKGROUND: England and Wales experienced a stagnation of previously improving life expectancy during the 2010s. Public bodies cited influenza as an important cause. SOURCES OF DATA: We used data from the Office for National Statistics to examine mortality attributed directly to influenza and to all influenza-like diseases for the total population of England and Wales 2010-19. Several combinations of ICD-10 codes were used to address the possibility of under-counting influenza deaths. AREAS OF AGREEMENT: Deaths from influenza and influenza-like diseases declined between 2010 and 2019, while earlier improvements in mortality from all causes of death were stalling and, with some causes, worsening. Our findings support existing research showing that influenza is not an important cause of the stalling of mortality rates 2010-19. AREAS OF CONTROVERSY: Influenza was accepted by many as an important cause of stalling life expectancy for much of the 2010s, while few in public office have accepted austerity as a key factor in the changes seen during that time. GROWING POINTS: This adds to the mounting evidence that austerity damaged health prior to COVID-19 and left the population more vulnerable when it arrived. AREAS FOR DEVELOPING TIMELY RESEARCH: Future research should explore why so many in public office were quick to attribute the change in trends in overall mortality in the UK in this period to influenza, and why many continue to do so through to 2023 and to deny the key role of austerity in harming population health.

Service implications of the revised 2022 National Institute for Health and Care Excellence (NICE) follow-up guidelines for stage IA-IIC melanoma.

BACKGROUND: The 2022 National Institute for Health and Care Excellence melanoma guideline update made significant changes to follow-up. The aim of this study was to assess the impact these changes will have on a national melanoma cohort over a 5-year follow-up interval. METHODS: Anonymized, individual-level, population-scale, linkable primary and secondary care National Health Service data for an 18-year interval (2000-2018) in Wales, UK were analysed. These data were used to predict the number of patients over a 10-year interval (2020-2030) that would be diagnosed with melanoma. Follow-up schedules for the 2015 and 2022 National Institute for Health and Care Excellence melanoma guidelines were then used to calculate the number of clinician-led appointments, the number of radiological investigations, and the total healthcare cost between 2025 and 2030, corresponding to a 5-year patient follow-up interval, for those with stage IA-IIC melanoma. RESULTS: Between 2025 and 2030 it is predicted that implementation of the 2022 guidelines would lead to 21 122 (range 19 194-23 083) fewer clinician-led appointments for patients with stage IA-IIC melanoma. However, there would be a significant increase in the number of radiological investigations (7812; range 7444-8189). These changes would lead to a €2.74 million (€1.87 million-€3.61 million) reduction in the total cost of follow-up over the interval 2025-2030. CONCLUSION: Melanoma follow-up guideline changes will result in a substantial reduction in the number of clinical follow-up appointments, but a significant additional burden to radiological services. The overall cost of follow-up at a national level will be reduced.

Biomarkers of peanut allergy in children over time.

BACKGROUND: Various biomarkers are used to define peanut allergy (PA). We aimed to observe changes in PA resolution and persistence over time comparing biomarkers in PA and peanut sensitised but tolerant (PS) children in a population-based cohort. METHODS: Participants were recruited from the EAT and EAT-On studies, conducted across England and Wales, and were exclusively breastfeed babies recruited at 3 months old and followed up until 7-12 years old. Clinical characteristics, skin prick test (SPT), sIgE to peanut and peanut components and mast cell activation tests (MAT) were assessed at 12 months, 36 months and 7-12 years. PA status was determined at the 7-12 year time point. RESULTS: The prevalence of PA was 2.1% at 7-12 years. Between 3 and 7-12 year, two children developed PA and one outgrew PA. PA children had larger SPT, higher peanut-sIgE, Ara h 2-sIgE and MAT (all p < .001) compared to PS children from 12 months onwards. SPT, peanut-sIgE, Ara h 2-sIgE and MAT between children with persistent PA, new PA, outgrown PA and PS were statistically significant from 12 months onwards (p < .001). Those with persistent PA had SPT, peanut-sIgE and Ara h 2-sIgE that increased over time and MAT which was highest at 36 months. New PA children had increased SPT and peanut-sIgE from 36 months to 7-12 years, but MAT remained low. PS children had low biomarkers across time. CONCLUSIONS: In this cohort, few children outgrow or develop new PA between 36 months and 7-12 years. Children with persistent PA have raised SPT, peanut-sIgE, Ara h 2-sIgE and MAT evident from infancy that consistently increase over time.

Algorithmic approach to finding people with multiple sclerosis using routine healthcare data in Wales.

BACKGROUND: Identification of multiple sclerosis (MS) cases in routine healthcare data repositories remains challenging. MS can have a protracted diagnostic process and is rarely identified as a primary reason for admission to the hospital. Difficulties in identification are compounded in systems that do not include insurance or payer information concerning drug treatments or non-notifiable disease. AIM: To develop an algorithm to reliably identify MS cases within a national health data bank. METHOD: Retrospective analysis of the Secure Anonymised Information Linkage (SAIL) databank was used to identify MS cases using a novel algorithm. Sensitivity and specificity were tested using two existing independent MS datasets, one clinically validated and population-based and a second from a self-registered MS national registry. RESULTS: From 4 757 428 records, the algorithm identified 6194 living cases of MS within Wales on 31 December 2020 (prevalence 221.65 (95% CI 216.17 to 227.24) per 100 000). Case-finding sensitivity and specificity were 96.8% and 99.9% for the clinically validated population-based cohort and sensitivity was 96.7% for the self-declared registry population. DISCUSSION: The algorithm successfully identified MS cases within the SAIL databank with high sensitivity and specificity, verified by two independent populations and has important utility in large-scale epidemiological studies of MS.

Modelling Disease Progression of Multiple Sclerosis in a South Wales Cohort.

OBJECTIVES: The objective of this study was to model multiple sclerosis (MS) disease progression and compare disease trajectories by sex, age of onset, and year of diagnosis. STUDY DESIGN AND SETTING: Longitudinal EDSS scores (20,854 observations) were collected for 1,787 relapse-onset MS patients at MS clinics in South Wales and modelled using a multilevel model (MLM). The MLM adjusted for covariates (sex, age of onset, year of diagnosis, and disease-modifying treatments), and included interactions between baseline covariates and time variables. RESULTS: The optimal model was truncated at 30 years after disease onset and excluded EDSS recorded within 3 months of relapse. As expected, older age of onset was associated with faster disease progression at 15 years (effect size (ES): 0.75; CI: 0.63, 0.86; p: <0.001) and female-sex progressed more slowly at 15 years (ES: -0.43; CI: -0.68, -0.18; p: <0.001). Patients diagnosed more recently (defined as 2007-2011 and >2011) progressed more slowly than those diagnosed historically (<2006); (ES: -0.46; CI: -0.75, -0.16; p: 0.006) and (ES: -0.95; CI: -1.20, -0.70; p: <0.001), respectively. CONCLUSION: We present a novel model of MS outcomes, accounting for the non-linear trajectory of MS and effects of baseline covariates, validating well-known risk factors (sex and age of onset) associated with disease progression. Also, patients diagnosed more recently progressed more slowly than those diagnosed historically.

Health care utilization and mortality for people with epilepsy during COVID-19: A population study.

OBJECTIVE: This study was undertaken to characterize changes in health care utilization and mortality for people with epilepsy (PWE) during the COVID-19 pandemic. METHODS: We performed a retrospective study using linked, individual-level, population-scale anonymized health data from the Secure Anonymised Information Linkage databank. We identified PWE living in Wales during the study "pandemic period" (January 1, 2020-June 30, 2021) and during a "prepandemic" period (January 1, 2016-December 31, 2019). We compared prepandemic health care utilization, status epilepticus, and mortality rates with corresponding pandemic rates for PWE and people without epilepsy (PWOE). We performed subgroup analyses on children (<18 years old), older people (>65 years old), those with intellectual disability, and those living in the most deprived areas. We used Poisson models to calculate adjusted rate ratios (RRs). RESULTS: We identified 27 279 PWE who had significantly higher rates of hospital (50.3 visits/1000 patient months), emergency department (55.7), and outpatient attendance (172.4) when compared to PWOE (corresponding figures: 25.7, 25.2, and 87.0) in the prepandemic period. Hospital and epilepsy-related hospital admissions, and emergency department and outpatient attendances all reduced significantly for PWE (and all subgroups) during the pandemic period. RRs [95% confidence intervals (CIs)] for pandemic versus prepandemic periods were .70 [.69-.72], .77 [.73-.81], .78 [.77-.79], and .80 [.79-.81]. The corresponding rates also reduced for PWOE. New epilepsy diagnosis rates decreased during the pandemic compared with the prepandemic period (2.3/100 000/month cf. 3.1/100 000/month, RR = .73, 95% CI = .68-.78). Both all-cause deaths and deaths with epilepsy recorded on the death certificate increased for PWE during the pandemic (RR = 1.07, 95% CI = .997-1.145 and RR = 2.44, 95% CI = 2.12-2.81). When removing COVID deaths, RRs were .88 (95% CI = .81-.95) and 1.29 (95% CI = 1.08-1.53). Status epilepticus rates did not change significantly during the pandemic (RR = .95, 95% CI = .78-1.15). SIGNIFICANCE: All-cause non-COVID deaths did not increase but non-COVID deaths associated with epilepsy did increase for PWE during the COVID-19 pandemic. The longer term effects of the decrease in new epilepsy diagnoses and health care utilization and increase in deaths associated with epilepsy need further research.

Epilepsy and the risk of COVID-19-related hospitalization and death: A population study.

OBJECTIVE: People with epilepsy (PWE) may be at an increased risk of severe COVID-19. It is important to characterize this risk to inform PWE and for future health and care planning. We assessed whether PWE were at higher risk of being hospitalized with, or dying from, COVID-19. METHODS: We performed a retrospective cohort study using linked, population-scale, anonymized electronic health records from the SAIL (Secure Anonymised Information Linkage) databank. This includes hospital admission and demographic data for the complete Welsh population (3.1 million) and primary care records for 86% of the population. We identified 27 279 PWE living in Wales during the study period (March 1, 2020 to June 30, 2021). Controls were identified using exact 5:1 matching (sex, age, and socioeconomic status). We defined COVID-19 deaths as having International Classification of Diseases, 10th Revision (ICD-10) codes for COVID-19 on death certificates or occurring within 28 days of a positive SARS-CoV-2 polymerase chain reaction (PCR) test. COVID-19 hospitalizations were defined as having a COVID-19 ICD-10 code for the reason for admission or occurring within 28 days of a positive SARS-CoV-2 PCR test. We recorded COVID-19 vaccinations and comorbidities known to increase the risk of COVID-19 hospitalization and death. We used Cox proportional hazard models to calculate hazard ratios. RESULTS: There were 158 (.58%) COVID-19 deaths and 933 (3.4%) COVID-19 hospitalizations in PWE, and 370 (.27%) deaths and 1871 (1.4%) hospitalizations in controls. Hazard ratios for COVID-19 death and hospitalization in PWE compared to controls were 2.15 (95% confidence interval [CI] = 1.78-2.59) and 2.15 (95% CI = 1.94-2.37), respectively. Adjusted hazard ratios (adjusted for comorbidities) for death and hospitalization were 1.32 (95% CI = 1.08-1.62) and 1.60 (95% CI = 1.44-1.78). SIGNIFICANCE: PWE are at increased risk of being hospitalized with, and dying from, COVID-19 when compared to age-, sex-, and deprivation-matched controls, even when adjusting for comorbidities. This may have implications for prioritizing future COVID-19 treatments and vaccinations for PWE.

Opioid-related deaths and their counterpart by occurrence era, age group and coimplicated drugs: Scotland vs. England and Wales.

AIMS: Compare by occurrence era and age group how opioid-related deaths (ORDs) and their counterpart evolved in Scotland vs. England and Wales during 2006-2020. For Scotland, compare coimplication rates between ORDs and non-ORDs for any benzodiazepine, cocaine or gabapentin/pregabalin, and consider whether coimplication in ORDs depended on opioid-specificity. METHODS: Cross-tabulations of drug misuse deaths (DMDs) obtained by 3 yearly occurrence era (2006-2008 to 2018-2020) and age group (under 25, 25-34, 35-44, 45-54, 55+ years) for England and Wales and subdivided by whether at least 1 opiate was mentioned on death certificate (DMD-Os or not); and of Scotland's opioid-related deaths (ORDs vs. non-ORDs) together with (i) coimplication by any benzodiazepine, cocaine or gabapentin/pregabalin; and (ii) opioid-specificity of ORDs. ORD is defined by heroin/morphine, methadone or buprenorphine being implicated in DMD. RESULTS: Per era between 2012-2014 and 2018-2020, Scotland's ORDs increased by 54% and non-ORDs by 34%. Increase in DMD-Os in England and Wales was more modest. Cocaine was implicated in 83% of Scotland's 2690 non-ORDs during 2006-2020; and any benzodiazepine in 53% of 8409 ORDs. However, in 2018-2020, coimplication rates in 2926 ORDs (880 non-ORDs) were 81% (33%) for any benzodiazepine, 30% (74%) for cocaine and 38% (22%) for gabapentin/pregabalin. Coimplication rate in 2018-2020 for any benzodiazepine was lowest at 70% (616/877) for heroin/morphine ORDs; and, by age group, at 66% (160/241) for ORDs aged 55+ years. CONCLUSIONS: Drug testing to inform users, shared intelligence between police and public health for earlier detection of changes in supply and monitoring of prescribed daily-dose of methadone are urgent.

The influence of socioeconomic deprivation on outcomes in transplant patients infected with SARS-CoV-2 in Wales.

INTRODUCTION: SARS-CoV-2 infection has had a significant impact on vulnerable individuals including transplant patients. Socioeconomic deprivation negatively affects outcomes of many health conditions. The aim of this study was to evaluate the effect of socioeconomic deprivation on the incidence and severity of SARS-CoV-2 infection among Welsh transplant patients. METHODS: This study is a retrospective, cross-sectional study on the transplant population of Wales. The Welsh Index of Multiple Deprivation (WIMD) was used to assess the influence of socioeconomic deprivation on outcomes of Welsh transplant patients who developed SARS-CoV-2 infection. Outcome measures were the incidence of SARS-CoV-2 infection, rates of hospital and ICU admission, development of acute kidney injury (AKI) and mortality. A logistic binomial regression analysis was used to correlate the various risk factors with the incidence of SARS-CoV-2 infection. RESULTS: Two hundred and sixty-six (25%) of regular follow up patients had SARS-CoV-2 infection; of these 55 (20.7%) were admitted, 15 (5.6%) to ICU, 37 (13.9%) developed AKI, and 23 (8.6%) died. In a regression analysis, patients of younger age were associated with more (p = .001) and those with SPK (simultaneous pancreas kidney) transplant less chance of infection (p = .038), whereas social deprivation was not associated with the chance of infection (p = .14). In regression analysis increased social deprivation was associated with higher chance of AKI post SARS-CoV-2 (p = .049). CONCLUSIONS: Socioeconomic deprivation did not affect the rates or severity of SARS-CoV-2 infection apart from the degree of AKI in Welsh Transplant patients. Adherence to the preventive measures for this high-risk population must continue to remain a priority.

Enabling the examination of long-term mortality trends by educational level for England and Wales in a time-consistent and internationally comparable manner.

BACKGROUND: Studying long-term trends in educational inequalities in health is important for monitoring and policy evaluation. Data issues regarding the allocation of people to educational groups hamper the study and international comparison of educational inequalities in mortality. For the UK, this has been acknowledged, but no satisfactory solution has been proposed. OBJECTIVE: To enable the examination of long-term mortality trends by educational level for England and Wales (E&W) in a time-consistent and internationally comparable manner, we propose and implement an approach to deal with the data issues regarding mortality data by educational level. METHODS: We employed 10-year follow-ups of individuals aged 20+ from the Office for National Statistics Longitudinal Study (ONS-LS), which include education information from each decennial census (1971-2011) linked to individual death records, for a 1% representative sample of the E&W population. We assigned the individual cohort data to single ages and calendar years, and subsequently obtained aggregate all-cause mortality data by education, sex, age (30+), and year (1972-2017). Our data adjustment approach optimised the available education information at the individual level, and adjusts-at the aggregate level-for trend discontinuities related to the identified data issues, and for differences with country-level mortality data for the total population. RESULTS: The approach resulted in (1) a time-consistent and internationally comparable categorisation of educational attainment into the low, middle, and high educated; (2) the adjustment of identified data-quality related discontinuities in the trends over time in the share of personyears and deaths by educational level, and in the crude and the age-standardised death rate by and across educational levels; (3) complete mortality data by education for ONS-LS members aged 30+ in 1972-2017 which aligns with country-level mortality data for the total population; and (4) the estimation of inequality measures using established methods. For those aged 30+ , both absolute and relative educational inequalities in mortality first increased and subsequently decreased. CONCLUSION: We obtained additional insights into long-term trends in educational inequalities in mortality in E&W, and illustrated the potential effects of different data issues. We recommend the use of (part of) the proposed approach in other contexts.

A genetically related cluster of Salmonella Typhimurium cases in humans associated with ruminant livestock and related food chains, United Kingdom, August 2021-December 2022.

Following an outbreak of Salmonella Typhimurium in Wales in July 2021 associated with sheep meat and offal, further genetically related cases were detected across the UK. Cases were UK residents with laboratory-confirmed Salmonella Typhimurium in the same 5-single-nucleotide polymorphism (SNP) single-linkage cluster with specimen date between 01/08/2021-2031/12/2022. We described cases using routine (UK) and enhanced (Wales only) surveillance data. Exposures in cases in Wales were compared with non-Typhimurium Salmonella case-controls. Environmental Health Practitioners and the Food Standards Agency investigated supply chains of food premises reported by ≥2 cases. Animal, carcass, and environmental samples taken for diagnostic or monitoring purposes for gastrointestinal pathogens were included in microbiological investigations. We identified 142 cases: 75% in England, 23% in Wales and 3% in Scotland. Median age was 32 years, and 59% were male. Direct contact with sheep was associated with becoming a case (aOR: 14, 95%CI: 1.4-145) but reported by few (6/32 cases). No single food item, premises, or supplier linked all cases. Multi-agency collaboration enabled the identification of isolates in the same 5-SNP single-linkage cluster from a sheep carcass at an English abattoir and in ruminant, wildlife, poultry, and environmental samples, suggesting multiple vehicles and pathways of infection.

The spectrum of co-existing disease in children with established kidney failure using registry and linked electronic health record data.

BACKGROUND: Children with established kidney failure may have additional medical conditions influencing kidney care and outcomes. This cross-sectional study aimed to examine the prevalence of co-existing diseases captured in the electronic hospital record compared to UK Renal Registry (UKRR) data and differences in coding. METHODS: The study population comprised children aged < 18 years receiving kidney replacement therapy (KRT) in England and Wales on 31/12/2016. Comorbidity data at KRT start was examined in the hospital record and compared to UKRR data. Agreement was assessed by the kappa statistic. Associations between patient and clinical factors and likelihood of coding were examined using multivariable logistic regression. RESULTS: A total of 869 children (62.5% male) had data linkage for inclusion. UKRR records generally reported a higher prevalence of co-existing disease than electronic health records; congenital, non-kidney disease was most commonly reported across both datasets. The highest sensitivity in the hospital record was seen for congenital heart disease (odds ratio (OR) 0.65, 95% confidence interval (CI) 0.51, 0.78) and malignancy (OR 0.63, 95% CI 0.41, 0.85). At best, moderate agreement (kappa ≥ 0.41) was seen between the datasets. Factors associated with higher odds of coding in hospital records included age, while kidney disease and a higher number of comorbidities were associated with lower odds of coding. CONCLUSIONS: Health records generally under-reported co-existing disease compared to registry data with fair-moderate agreement between datasets. Electronic health records offer a non-selective overview of co-existing disease facilitating audit and research, but registry processes are still required to capture paediatric-specific variables pertinent to kidney disease.